WorldWideScience

Sample records for vehicle uav based

  1. A Hybrid Vehicle Detection Method Based on Viola-Jones and HOG + SVM from UAV Images.

    Science.gov (United States)

    Xu, Yongzheng; Yu, Guizhen; Wang, Yunpeng; Wu, Xinkai; Ma, Yalong

    2016-08-19

    A new hybrid vehicle detection scheme which integrates the Viola-Jones (V-J) and linear SVM classifier with HOG feature (HOG + SVM) methods is proposed for vehicle detection from low-altitude unmanned aerial vehicle (UAV) images. As both V-J and HOG + SVM are sensitive to on-road vehicles' in-plane rotation, the proposed scheme first adopts a roadway orientation adjustment method, which rotates each UAV image to align the roads with the horizontal direction so the original V-J or HOG + SVM method can be directly applied to achieve fast detection and high accuracy. To address the issue of descending detection speed for V-J and HOG + SVM, the proposed scheme further develops an adaptive switching strategy which sophistically integrates V-J and HOG + SVM methods based on their different descending trends of detection speed to improve detection efficiency. A comprehensive evaluation shows that the switching strategy, combined with the road orientation adjustment method, can significantly improve the efficiency and effectiveness of the vehicle detection from UAV images. The results also show that the proposed vehicle detection method is competitive compared with other existing vehicle detection methods. Furthermore, since the proposed vehicle detection method can be performed on videos captured from moving UAV platforms without the need of image registration or additional road database, it has great potentials of field applications. Future research will be focusing on expanding the current method for detecting other transportation modes such as buses, trucks, motors, bicycles, and pedestrians.

  2. A Hybrid Vehicle Detection Method Based on Viola-Jones and HOG + SVM from UAV Images

    Science.gov (United States)

    Xu, Yongzheng; Yu, Guizhen; Wang, Yunpeng; Wu, Xinkai; Ma, Yalong

    2016-01-01

    A new hybrid vehicle detection scheme which integrates the Viola-Jones (V-J) and linear SVM classifier with HOG feature (HOG + SVM) methods is proposed for vehicle detection from low-altitude unmanned aerial vehicle (UAV) images. As both V-J and HOG + SVM are sensitive to on-road vehicles’ in-plane rotation, the proposed scheme first adopts a roadway orientation adjustment method, which rotates each UAV image to align the roads with the horizontal direction so the original V-J or HOG + SVM method can be directly applied to achieve fast detection and high accuracy. To address the issue of descending detection speed for V-J and HOG + SVM, the proposed scheme further develops an adaptive switching strategy which sophistically integrates V-J and HOG + SVM methods based on their different descending trends of detection speed to improve detection efficiency. A comprehensive evaluation shows that the switching strategy, combined with the road orientation adjustment method, can significantly improve the efficiency and effectiveness of the vehicle detection from UAV images. The results also show that the proposed vehicle detection method is competitive compared with other existing vehicle detection methods. Furthermore, since the proposed vehicle detection method can be performed on videos captured from moving UAV platforms without the need of image registration or additional road database, it has great potentials of field applications. Future research will be focusing on expanding the current method for detecting other transportation modes such as buses, trucks, motors, bicycles, and pedestrians. PMID:27548179

  3. Volumetric calculation using low cost unmanned aerial vehicle (UAV) approach

    Science.gov (United States)

    Rahman, A. A. Ab; Maulud, K. N. Abdul; Mohd, F. A.; Jaafar, O.; Tahar, K. N.

    2017-12-01

    Unmanned Aerial Vehicles (UAV) technology has evolved dramatically in the 21st century. It is used by both military and general public for recreational purposes and mapping work. Operating cost for UAV is much cheaper compared to that of normal aircraft and it does not require a large work space. The UAV systems have similar functions with the LIDAR and satellite images technologies. These systems require a huge cost, labour and time consumption to produce elevation and dimension data. Measurement of difficult objects such as water tank can also be done by using UAV. The purpose of this paper is to show the capability of UAV to compute the volume of water tank based on a different number of images and control points. The results were compared with the actual volume of the tank to validate the measurement. In this study, the image acquisition was done using Phantom 3 Professional, which is a low cost UAV. The analysis in this study is based on different volume computations using two and four control points with variety set of UAV images. The results show that more images will provide a better quality measurement. With 95 images and four GCP, the error percentage to the actual volume is about 5%. Four controls are enough to get good results but more images are needed, estimated about 115 until 220 images. All in all, it can be concluded that the low cost UAV has a potential to be used for volume of water and dimension measurement.

  4. Weed mapping in early-season maize fields using object-based analysis of unmanned aerial vehicle (UAV) images.

    Science.gov (United States)

    Peña, José Manuel; Torres-Sánchez, Jorge; de Castro, Ana Isabel; Kelly, Maggi; López-Granados, Francisca

    2013-01-01

    The use of remote imagery captured by unmanned aerial vehicles (UAV) has tremendous potential for designing detailed site-specific weed control treatments in early post-emergence, which have not possible previously with conventional airborne or satellite images. A robust and entirely automatic object-based image analysis (OBIA) procedure was developed on a series of UAV images using a six-band multispectral camera (visible and near-infrared range) with the ultimate objective of generating a weed map in an experimental maize field in Spain. The OBIA procedure combines several contextual, hierarchical and object-based features and consists of three consecutive phases: 1) classification of crop rows by application of a dynamic and auto-adaptive classification approach, 2) discrimination of crops and weeds on the basis of their relative positions with reference to the crop rows, and 3) generation of a weed infestation map in a grid structure. The estimation of weed coverage from the image analysis yielded satisfactory results. The relationship of estimated versus observed weed densities had a coefficient of determination of r(2)=0.89 and a root mean square error of 0.02. A map of three categories of weed coverage was produced with 86% of overall accuracy. In the experimental field, the area free of weeds was 23%, and the area with low weed coverage (weeds) was 47%, which indicated a high potential for reducing herbicide application or other weed operations. The OBIA procedure computes multiple data and statistics derived from the classification outputs, which permits calculation of herbicide requirements and estimation of the overall cost of weed management operations in advance.

  5. Development of Cloud-Based UAV Monitoring and Management System.

    Science.gov (United States)

    Itkin, Mason; Kim, Mihui; Park, Younghee

    2016-11-15

    Unmanned aerial vehicles (UAVs) are an emerging technology with the potential to revolutionize commercial industries and the public domain outside of the military. UAVs would be able to speed up rescue and recovery operations from natural disasters and can be used for autonomous delivery systems (e.g., Amazon Prime Air). An increase in the number of active UAV systems in dense urban areas is attributed to an influx of UAV hobbyists and commercial multi-UAV systems. As airspace for UAV flight becomes more limited, it is important to monitor and manage many UAV systems using modern collision avoidance techniques. In this paper, we propose a cloud-based web application that provides real-time flight monitoring and management for UAVs. For each connected UAV, detailed UAV sensor readings from the accelerometer, GPS sensor, ultrasonic sensor and visual position cameras are provided along with status reports from the smaller internal components of UAVs (i.e., motor and battery). The dynamic map overlay visualizes active flight paths and current UAV locations, allowing the user to monitor all aircrafts easily. Our system detects and prevents potential collisions by automatically adjusting UAV flight paths and then alerting users to the change. We develop our proposed system and demonstrate its feasibility and performances through simulation.

  6. Development of Cloud-Based UAV Monitoring and Management System

    Directory of Open Access Journals (Sweden)

    Mason Itkin

    2016-11-01

    Full Text Available Unmanned aerial vehicles (UAVs are an emerging technology with the potential to revolutionize commercial industries and the public domain outside of the military. UAVs would be able to speed up rescue and recovery operations from natural disasters and can be used for autonomous delivery systems (e.g., Amazon Prime Air. An increase in the number of active UAV systems in dense urban areas is attributed to an influx of UAV hobbyists and commercial multi-UAV systems. As airspace for UAV flight becomes more limited, it is important to monitor and manage many UAV systems using modern collision avoidance techniques. In this paper, we propose a cloud-based web application that provides real-time flight monitoring and management for UAVs. For each connected UAV, detailed UAV sensor readings from the accelerometer, GPS sensor, ultrasonic sensor and visual position cameras are provided along with status reports from the smaller internal components of UAVs (i.e., motor and battery. The dynamic map overlay visualizes active flight paths and current UAV locations, allowing the user to monitor all aircrafts easily. Our system detects and prevents potential collisions by automatically adjusting UAV flight paths and then alerting users to the change. We develop our proposed system and demonstrate its feasibility and performances through simulation.

  7. Development of Cloud-Based UAV Monitoring and Management System

    Science.gov (United States)

    Itkin, Mason; Kim, Mihui; Park, Younghee

    2016-01-01

    Unmanned aerial vehicles (UAVs) are an emerging technology with the potential to revolutionize commercial industries and the public domain outside of the military. UAVs would be able to speed up rescue and recovery operations from natural disasters and can be used for autonomous delivery systems (e.g., Amazon Prime Air). An increase in the number of active UAV systems in dense urban areas is attributed to an influx of UAV hobbyists and commercial multi-UAV systems. As airspace for UAV flight becomes more limited, it is important to monitor and manage many UAV systems using modern collision avoidance techniques. In this paper, we propose a cloud-based web application that provides real-time flight monitoring and management for UAVs. For each connected UAV, detailed UAV sensor readings from the accelerometer, GPS sensor, ultrasonic sensor and visual position cameras are provided along with status reports from the smaller internal components of UAVs (i.e., motor and battery). The dynamic map overlay visualizes active flight paths and current UAV locations, allowing the user to monitor all aircrafts easily. Our system detects and prevents potential collisions by automatically adjusting UAV flight paths and then alerting users to the change. We develop our proposed system and demonstrate its feasibility and performances through simulation. PMID:27854267

  8. Uav-Based 3d Urban Environment Monitoring

    Science.gov (United States)

    Boonpook, Wuttichai; Tan, Yumin; Liu, Huaqing; Zhao, Binbin; He, Lingfeng

    2018-04-01

    Unmanned Aerial Vehicle (UAV) based remote sensing can be used to make three-dimensions (3D) mapping with great flexibility, besides the ability to provide high resolution images. In this paper we propose a quick-change detection method on UAV images by combining altitude from Digital Surface Model (DSM) and texture analysis from images. Cases of UAV images with and without georeferencing are both considered. Research results show that the accuracy of change detection can be enhanced with georeferencing procedure, and the accuracy and precision of change detection on UAV images which are collected both vertically and obliquely but without georeferencing also have a good performance.

  9. Unmanned aerial vehicle (UAV)-based monitoring of a landslide: Gallenzerkogel landslide (Ybbs-Lower Austria) case study.

    Science.gov (United States)

    Eker, Remzi; Aydın, Abdurrahim; Hübl, Johannes

    2017-12-19

    In the present study, UAV-based monitoring of the Gallenzerkogel landslide (Ybbs, Lower Austria) was carried out by three flight missions. High-resolution digital elevation models (DEMs), orthophotos, and density point clouds were generated from UAV-based aerial photos via structure-from-motion (SfM). According to ground control points (GCPs), an average of 4 cm root mean square error (RMSE) was found for all models. In addition, light detection and ranging (LIDAR) data from 2009, representing the prefailure topography, was utilized as a digital terrain model (DTM) and digital surface model (DSM). First, the DEM of difference (DoD) between the first UAV flight data and the LIDAR-DTM was determined and according to the generated DoD deformation map, an elevation difference of between - 6.6 and 2 m was found. Over the landslide area, a total of 4380.1 m 3 of slope material had been eroded, while 297.4 m 3 of the material had accumulated within the most active part of the slope. In addition, 688.3 m 3 of the total eroded material had belonged to the road destroyed by the landslide. Because of the vegetation surrounding the landslide area, the Multiscale Model-to-Model Cloud Comparison (M3C2) algorithm was then applied to compare the first and second UAV flight data. After eliminating both the distance uncertainty values of higher than 15 cm and the nonsignificant changes, the M3C2 distance obtained was between - 2.5 and 2.5 m. Moreover, the high-resolution orthophoto generated by the third flight allowed visual monitoring of the ongoing control/stabilization work in the area.

  10. Real-time people and vehicle detection from UAV imagery

    Science.gov (United States)

    Gaszczak, Anna; Breckon, Toby P.; Han, Jiwan

    2011-01-01

    A generic and robust approach for the real-time detection of people and vehicles from an Unmanned Aerial Vehicle (UAV) is an important goal within the framework of fully autonomous UAV deployment for aerial reconnaissance and surveillance. Here we present an approach for the automatic detection of vehicles based on using multiple trained cascaded Haar classifiers with secondary confirmation in thermal imagery. Additionally we present a related approach for people detection in thermal imagery based on a similar cascaded classification technique combining additional multivariate Gaussian shape matching. The results presented show the successful detection of vehicle and people under varying conditions in both isolated rural and cluttered urban environments with minimal false positive detection. Performance of the detector is optimized to reduce the overall false positive rate by aiming at the detection of each object of interest (vehicle/person) at least once in the environment (i.e. per search patter flight path) rather than every object in each image frame. Currently the detection rate for people is ~70% and cars ~80% although the overall episodic object detection rate for each flight pattern exceeds 90%.

  11. Unmanned air vehicle (UAV) ultra-persitence research

    Energy Technology Data Exchange (ETDEWEB)

    Dron, S. B.

    2012-03-01

    considered. Fundamental cost driver analysis was also performed. System development plans were drafted in order to determine where the technological and programmatic critical paths lay. As a result of this effort, UAVs were to be able to provide far more surveillance time and intelligence information per mission while reducing the high cost of support activities. This technology was intended to create unmatched global capabilities to observe and preempt terrorist and weapon of mass destruction (WMD) activities. Various DOE laboratory and contractor personnel and facilities could have been used to perform detailed engineering, fabrication, assembly and test operations including follow-on operational support. Unfortunately, none of the results will be used in the near-term or mid-term future. NGIS UMS and SNL felt that the technical goals for the project were accomplished. NGIS UMS was quite pleased with the results of analysis and design although it was disappointing to all that the political realities would not allow use of the results. Technology and system designs evaluated under this CRADA had previously never been applied to unmanned air vehicles (UAVs). Based upon logistic support cost predictions, because the UAVs would not have had to refuel as often, forward basing support costs could have been reduced due to a decrease in the number and extent of support systems and personnel being required to operate UAVs in remote areas. Basic application of the advanced propulsion and power approach is well understood and industry now understands the technical, safety, and political issues surrounding implementation of these strategies. However, the overall economic impact was not investigated. The results will not be applied/implemented. No near-term benefit to industry or the taxpayer will be encountered as a result of these studies.

  12. WETLAND ASSESSMENT USING UNMANNED AERIAL VEHICLE (UAV PHOTOGRAMMETRY

    Directory of Open Access Journals (Sweden)

    M. A. Boon

    2016-06-01

    Full Text Available The use of Unmanned Arial Vehicle (UAV photogrammetry is a valuable tool to enhance our understanding of wetlands. Accurate planning derived from this technological advancement allows for more effective management and conservation of wetland areas. This paper presents results of a study that aimed at investigating the use of UAV photogrammetry as a tool to enhance the assessment of wetland ecosystems. The UAV images were collected during a single flight within 2½ hours over a 100 ha area at the Kameelzynkraal farm, Gauteng Province, South Africa. An AKS Y-6 MKII multi-rotor UAV and a digital camera on a motion compensated gimbal mount were utilised for the survey. Twenty ground control points (GCPs were surveyed using a Trimble GPS to achieve geometrical precision and georeferencing accuracy. Structure-from-Motion (SfM computer vision techniques were used to derive ultra-high resolution point clouds, orthophotos and 3D models from the multi-view photos. The geometric accuracy of the data based on the 20 GCP’s were 0.018 m for the overall, 0.0025 m for the vertical root mean squared error (RMSE and an over all root mean square reprojection error of 0.18 pixel. The UAV products were then edited and subsequently analysed, interpreted and key attributes extracted using a selection of tools/ software applications to enhance the wetland assessment. The results exceeded our expectations and provided a valuable and accurate enhancement to the wetland delineation, classification and health assessment which even with detailed field studies would have been difficult to achieve.

  13. UNMANNED AIRCRAFT VEHICLE (UAV IN THE ROMANIAN AIRSPACE. AN OVERVIEW

    Directory of Open Access Journals (Sweden)

    Vasile PRISACARIU

    2014-04-01

    Full Text Available For the last decade the unmanned aircraft vehicle (UAV field has evolved in terms of the sub-branches established in the aerospace industry. At national level the UAV market is still in its infancy but acknowledges an upward trend in the implementation and use of UAVs in civilian and military missions. The achievements of the past decade confirms that Romanian specialists are able to conceive, design and build UAVs at a technological and operational level comparable to the one achieved by large international producers creating the prerequisites of developing a sub-sector for the national aeronautic industry. The current article aims at providing an overview of all activities related to the conception, manufacturing, testing, improving, operating UAVs as these activities evolved within the national airspace filed with brief references to the missions and legislation in this area.

  14. UAV Robust Strategy Control Based on MAS

    Directory of Open Access Journals (Sweden)

    Jian Han

    2014-01-01

    Full Text Available A novel multiagent system (MAS has been proposed to integrate individual UAV (unmanned aerial vehicle to form a UAV team which can accomplish complex missions with better efficiency and effect. The MAS based UAV team control is more able to conquer dynamic situations and enhance the performance of any single UAV. In this paper, the MAS proposed and established combines the reacting and thinking abilities to be an initiative and autonomous hybrid system which can solve missions involving coordinated flight and cooperative operation. The MAS uses BDI model to support its logical perception and to classify the different missions; then the missions will be allocated by utilizing auction mechanism after analyzing dynamic parameters. Prim potential algorithm, particle swarm algorithm, and reallocation mechanism are proposed to realize the rational decomposing and optimal allocation in order to reach the maximum profit. After simulation, the MAS has been proved to be able to promote the success ratio and raise the robustness, while realizing feasibility of coordinated flight and optimality of cooperative mission.

  15. FEASIBILITY COMPARISON OF AIRBORNE LASER SCANNING DATA AND 3D-POINT CLOUDS FORMED FROM UNMANNED AERIAL VEHICLE (UAV-BASED IMAGERY USED FOR 3D PROJECTING

    Directory of Open Access Journals (Sweden)

    I. I. Rilskiy

    2017-01-01

    Full Text Available New, innovative methods of aerial surveys have changed the approaches to information provision of projecting dramatically for the last 15 years. Nowadays there are at least two methods that claim to be the most efficient way for collecting geospatial data intended for projecting – the airborne laser scanning (LIDAR data and photogrammetrically processed unmanned aerial vehicle (UAV-based aerial imagery, forming 3D point clouds. But these materials are not identical to each other neither in precision, nor in completeness.Airborne laser scanning (LIDAR is normally being performed using manned aircrafts. LIDAR data are very precise, they allow us to achieve data about relief even overgrown with vegetation, or to collect laser reflections from wires, metal constructions and poles. UAV surveys are normally being performed using frame digital cameras (lightweight, full-frame, or mid-size. These cameras form images that are being processed using 3D photogrammetric software in automatic mode that allows one to generate 3D point cloud, which is used for building digital elevation models, surfaces, orthomosaics, etc.All these materials are traditionally being used for making maps and GIS data. LIDAR data have been popular in design work. Also there have been some attempts to use for the same purpose 3D-point clouds, formed by photogrammetric software from images acquired from UAVs.After comparison of the datasets from these two different types of surveying (surveys were made simultaneously on the same territory, it became possible to define some specific, typical for LIDAR or imagery-based 3D data. It can be mentioned that imagery-based 3D data (3D point clouds, formed in automatic mode using photogrammetry, are much worse than LIDAR data – both in terms of precision and completeness.The article highlights these differences and makes attempts at explaining the origin of these differences. 

  16. Estimation of Energy Balance Components over a Drip-Irrigated Olive Orchard Using Thermal and Multispectral Cameras Placed on a Helicopter-Based Unmanned Aerial Vehicle (UAV

    Directory of Open Access Journals (Sweden)

    Samuel Ortega-Farías

    2016-08-01

    Full Text Available A field experiment was carried out to implement a remote sensing energy balance (RSEB algorithm for estimating the incoming solar radiation (Rsi, net radiation (Rn, sensible heat flux (H, soil heat flux (G and latent heat flux (LE over a drip-irrigated olive (cv. Arbequina orchard located in the Pencahue Valley, Maule Region, Chile (35°25′S; 71°44′W; 90 m above sea level. For this study, a helicopter-based unmanned aerial vehicle (UAV was equipped with multispectral and infrared thermal cameras to obtain simultaneously the normalized difference vegetation index (NDVI and surface temperature (Tsurface at very high resolution (6 cm × 6 cm. Meteorological variables and surface energy balance components were measured at the time of the UAV overpass (near solar noon. The performance of the RSEB algorithm was evaluated using measurements of H and LE obtained from an eddy correlation system. In addition, estimated values of Rsi and Rn were compared with ground-truth measurements from a four-way net radiometer while those of G were compared with soil heat flux based on flux plates. Results indicated that RSEB algorithm estimated LE and H with errors of 7% and 5%, respectively. Values of the root mean squared error (RMSE and mean absolute error (MAE for LE were 50 and 43 W m−2 while those for H were 56 and 46 W m−2, respectively. Finally, the RSEB algorithm computed Rsi, Rn and G with error less than 5% and with values of RMSE and MAE less than 38 W m−2. Results demonstrated that multispectral and thermal cameras placed on an UAV could provide an excellent tool to evaluate the intra-orchard spatial variability of Rn, G, H, LE, NDVI and Tsurface over the tree canopy and soil surface between rows.

  17. Vision based systems for UAV applications

    CERN Document Server

    Kuś, Zygmunt

    2013-01-01

    This monograph is motivated by a significant number of vision based algorithms for Unmanned Aerial Vehicles (UAV) that were developed during research and development projects. Vision information is utilized in various applications like visual surveillance, aim systems, recognition systems, collision-avoidance systems and navigation. This book presents practical applications, examples and recent challenges in these mentioned application fields. The aim of the book is to create a valuable source of information for researchers and constructors of solutions utilizing vision from UAV. Scientists, researchers and graduate students involved in computer vision, image processing, data fusion, control algorithms, mechanics, data mining, navigation and IC can find many valuable, useful and practical suggestions and solutions. The latest challenges for vision based systems are also presented.

  18. [Retrieval of crown closure of moso bamboo forest using unmanned aerial vehicle (UAV) remotely sensed imagery based on geometric-optical model].

    Science.gov (United States)

    Wang, Cong; Du, Hua-qiang; Zhou, Guo-mo; Xu, Xiao-jun; Sun, Shao-bo; Gao, Guo-long

    2015-05-01

    This research focused on the application of remotely sensed imagery from unmanned aerial vehicle (UAV) with high spatial resolution for the estimation of crown closure of moso bamboo forest based on the geometric-optical model, and analyzed the influence of unconstrained and fully constrained linear spectral mixture analysis (SMA) on the accuracy of the estimated results. The results demonstrated that the combination of UAV remotely sensed imagery and geometric-optical model could, to some degrees, achieve the estimation of crown closure. However, the different SMA methods led to significant differentiation in the estimation accuracy. Compared with unconstrained SMA, the fully constrained linear SMA method resulted in higher accuracy of the estimated values, with the coefficient of determination (R2) of 0.63 at 0.01 level, against the measured values acquired during the field survey. Root mean square error (RMSE) of approximate 0.04 was low, indicating that the usage of fully constrained linear SMA could bring about better results in crown closure estimation, which was closer to the actual condition in moso bamboo forest.

  19. Unmanned Aerial Vehicle (UAV-based remote sensing to monitor grapevine leaf stripe disease within a vineyard affected by esca complex

    Directory of Open Access Journals (Sweden)

    Salvatore F. DI GENNARO

    2016-07-01

    Full Text Available Foliar symptoms of grapevine leaf stripe disease (GLSD, a disease within the esca complex are linked to drastic alteration of photosynthetic function and activation of defense responses in affected grapevines several days before the appearance of the first visible symptoms on leaves. The present study suggests a methodology to investigate the relationships between high-resolution multispectral images (0.05 m/pixel acquired using an Unmanned Aerial Vehicle (UAV, and GLSD foliar symptoms monitored by ground surveys. This approach showed high correlation between Normalized Differential Vegetation Index (NDVI acquired by the UAV and GLSD symptoms, and discrimination between symptomatic from asymptomatic plants. High-resolution multispectral images were acquired during June and July of 2012 and 2013, in an experimental vineyard heavily affected by GLSD, located in Tuscany (Italy, where vines had been surveyed and mapped since 2003. Each vine was located with a global positioning system, and classified for appearance of foliar symptoms and disease severity at weekly intervals from the beginning of each season. Remote sensing and ground observation data were analyzed to promptly identify the early stages of disease, even before visual detection. This work suggests an innovative methodology for quantitative and qualitative analysis of spatial distribution of symptomatic plants. The system may also be used for exploring the physiological bases of GLSD, and predicting the onset of this disease. 

  20. Rancang Bangun Prototype Unmanned Aerial Vehicle (UAV dengan Tiga Rotor

    Directory of Open Access Journals (Sweden)

    Darmawan Rasyid Hadi Saputra

    2013-03-01

    Full Text Available Unmanned Aerial Vehicle atau yang biasa dikenal dengan istilah UAV  merupakan sebuah sistem penerbangan/ pesawat tanpa pilot yang berada di dalam pesawat tersebut. UAV dapat dikendalikan dengan menggunakan remote dari jarak jauh, diprogram dengan perintah tertentu, atau bahkan dengan sistem pengendalian otomatis yang lebih kompleks. Aplikasi dari teknologi UAV pun beragam mulai dari tugas militer hingga pengamatan udara. Dalam penelitian ini, sebuah UAV akan dikembangkan dengan tiga buah rotor dan satu buah motor servo di bagian belakang UAV. Perancangan model menggunakan software CATIA dengan batasan dimensi (panjang × lebar maksimum 75 × 75 cm dan massa < 2 kg. Analisis struktur rangka dilakukan untuk menguji kekuatan rangka ketika terbang dan membawa beban, dengan menggunakan metode elemen hingga dan kriteria kegagalan Von-Misses. Dalam proses pengerjaan, rancangan dari CATIA dan analisis yang telah dilakukan dalam perancangan tersebut akan digunakan. Hasil yang didapat berupa UAV yang memiliki struktur rangka dengan defleksi maksimum 3,67 mm pada rangka tengah yang berbahan acrylic. Dalam pengujian di lapangan, UAV dapat melakukan gerak roll, pitch, dan yaw yang dikendalikan melalui remote control. Waktu operasi maksimum yang dapat dilakukan adalah selama 7 menit 43 detik.

  1. Effects of Hearing Protection Device Attenuation on Unmanned Aerial Vehicle (UAV) Audio Signatures

    Science.gov (United States)

    2016-03-01

    UAV ) Audio Signatures by Melissa Bezandry, Adrienne Raglin, and John Noble Approved for public release; distribution...Research Laboratory Effects of Hearing Protection Device Attenuation on Unmanned Aerial Vehicle ( UAV ) Audio Signatures by Melissa Bezandry...Aerial Vehicle ( UAV ) Audio Signatures 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Melissa Bezandry

  2. Characteristic analysis on UAV-MIMO channel based on normalized correlation matrix.

    Science.gov (United States)

    Gao, Xi jun; Chen, Zi li; Hu, Yong Jiang

    2014-01-01

    Based on the three-dimensional GBSBCM (geometrically based double bounce cylinder model) channel model of MIMO for unmanned aerial vehicle (UAV), the simple form of UAV space-time-frequency channel correlation function which includes the LOS, SPE, and DIF components is presented. By the methods of channel matrix decomposition and coefficient normalization, the analytic formula of UAV-MIMO normalized correlation matrix is deduced. This formula can be used directly to analyze the condition number of UAV-MIMO channel matrix, the channel capacity, and other characteristic parameters. The simulation results show that this channel correlation matrix can be applied to describe the changes of UAV-MIMO channel characteristics under different parameter settings comprehensively. This analysis method provides a theoretical basis for improving the transmission performance of UAV-MIMO channel. The development of MIMO technology shows practical application value in the field of UAV communication.

  3. An Automated Technique for Generating Georectified Mosaics from Ultra-High Resolution Unmanned Aerial Vehicle (UAV Imagery, Based on Structure from Motion (SfM Point Clouds

    Directory of Open Access Journals (Sweden)

    Christopher Watson

    2012-05-01

    Full Text Available Unmanned Aerial Vehicles (UAVs are an exciting new remote sensing tool capable of acquiring high resolution spatial data. Remote sensing with UAVs has the potential to provide imagery at an unprecedented spatial and temporal resolution. The small footprint of UAV imagery, however, makes it necessary to develop automated techniques to geometrically rectify and mosaic the imagery such that larger areas can be monitored. In this paper, we present a technique for geometric correction and mosaicking of UAV photography using feature matching and Structure from Motion (SfM photogrammetric techniques. Images are processed to create three dimensional point clouds, initially in an arbitrary model space. The point clouds are transformed into a real-world coordinate system using either a direct georeferencing technique that uses estimated camera positions or via a Ground Control Point (GCP technique that uses automatically identified GCPs within the point cloud. The point cloud is then used to generate a Digital Terrain Model (DTM required for rectification of the images. Subsequent georeferenced images are then joined together to form a mosaic of the study area. The absolute spatial accuracy of the direct technique was found to be 65–120 cm whilst the GCP technique achieves an accuracy of approximately 10–15 cm.

  4. Contour Detection for UAV-Based Cadastral Mapping

    Directory of Open Access Journals (Sweden)

    Sophie Crommelinck

    2017-02-01

    Full Text Available Unmanned aerial vehicles (UAVs provide a flexible and low-cost solution for the acquisition of high-resolution data. The potential of high-resolution UAV imagery to create and update cadastral maps is being increasingly investigated. Existing procedures generally involve substantial fieldwork and many manual processes. Arguably, multiple parts of UAV-based cadastral mapping workflows could be automated. Specifically, as many cadastral boundaries coincide with visible boundaries, they could be extracted automatically using image analysis methods. This study investigates the transferability of gPb contour detection, a state-of-the-art computer vision method, to remotely sensed UAV images and UAV-based cadastral mapping. Results show that the approach is transferable to UAV data and automated cadastral mapping: object contours are comprehensively detected at completeness and correctness rates of up to 80%. The detection quality is optimal when the entire scene is covered with one orthoimage, due to the global optimization of gPb contour detection. However, a balance between high completeness and correctness is hard to achieve, so a combination with area-based segmentation and further object knowledge is proposed. The localization quality exhibits the usual dependency on ground resolution. The approach has the potential to accelerate the process of general boundary delineation during the creation and updating of cadastral maps.

  5. UAV Based Imaging for Crop, Weed and Disease Monitoring

    DEFF Research Database (Denmark)

    Garcia Ruiz, Francisco Jose

    Summary Unmanned aerial vehicles (UAV) equipped with cameras have become a powerful technology to collect high resolution remote sensing data from agricultural crops. When equipped with multispectral cameras, light invisible for the human eye may be captured and used to characterize the physiolog......Summary Unmanned aerial vehicles (UAV) equipped with cameras have become a powerful technology to collect high resolution remote sensing data from agricultural crops. When equipped with multispectral cameras, light invisible for the human eye may be captured and used to characterize...... the physiological status of the vegetation. UAV imagery may be divided into three steps (1) spectral characterization of the targets of interest, (2) flight and image acquisition and (3) image processing and interpretation. The overall aims of this study were to improve knowledge in all three steps associated...... with UAV-based remote sensing for practical use in agriculture and to contribute to the incipient research on UAV based remote sensing for agricultural applications. Three case studies were performed to (1) Characterize the spectral signatures of sugar beet (Beta vulgaris L.) and creeping thistle (Cirsium...

  6. Digital Counts of Maize Plants by Unmanned Aerial Vehicles (UAVs

    Directory of Open Access Journals (Sweden)

    Friederike Gnädinger

    2017-05-01

    Full Text Available Precision phenotyping, especially the use of image analysis, allows researchers to gain information on plant properties and plant health. Aerial image detection with unmanned aerial vehicles (UAVs provides new opportunities in precision farming and precision phenotyping. Precision farming has created a critical need for spatial data on plant density. The plant number reflects not only the final field emergence but also allows a more precise assessment of the final yield parameters. The aim of this work is to advance UAV use and image analysis as a possible high-throughput phenotyping technique. In this study, four different maize cultivars were planted in plots with different seeding systems (in rows and equidistantly spaced and different nitrogen fertilization levels (applied at 50, 150 and 250 kg N/ha. The experimental field, encompassing 96 plots, was overflown at a 50-m height with an octocopter equipped with a 10-megapixel camera taking a picture every 5 s. Images were recorded between BBCH 13–15 (it is a scale to identify the phenological development stage of a plant which is here the 3- to 5-leaves development stage when the color of young leaves differs from older leaves. Close correlations up to R2 = 0.89 were found between in situ and image-based counted plants adapting a decorrelation stretch contrast enhancement procedure, which enhanced color differences in the images. On average, the error between visually and digitally counted plants was ≤5%. Ground cover, as determined by analyzing green pixels, ranged between 76% and 83% at these stages. However, the correlation between ground cover and digitally counted plants was very low. The presence of weeds and blurry effects on the images represent possible errors in counting plants. In conclusion, the final field emergence of maize can rapidly be assessed and allows more precise assessment of the final yield parameters. The use of UAVs and image processing has the potential to

  7. Using Unmanned Aerial Vehicles (UAVs) to Modeling Tornado Impacts

    Science.gov (United States)

    Wagner, M.; Doe, R. K.

    2017-12-01

    Using Unmanned Aerial Vehicles (UAVs) to assess storm damage is a useful research tool. Benefits include their ability to access remote or impassable areas post-storm, identify unknown damages and assist with more detailed site investigations and rescue efforts. Technological advancement of UAVs mean that they can capture high resolution images often at an affordable price. These images can be used to create 3D environments to better interpret and delineate damages from large areas that would have been difficult in ground surveys. This research presents the results of a rapid response site investigation of the 29 April 2017 Canton, Texas, USA, tornado using low cost UAVs. This was a multiple, high impact tornado event measuring EF4 at maximum. Rural farmland was chosen as a challenging location to test both equipment and methodology. Such locations provide multiple impacts at a variety of scales including structural and vegetation damage and even animal fatalities. The 3D impact models allow for a more comprehensive study prior to clean-up. The results show previously unseen damages and better quantify damage impacts at the local level. 3D digital track swaths were created allowing for a more accurate track width determination. These results demonstrate how effective the use of low cost UAVs can be for rapid response storm damage assessments, the high quality of data they can achieve, and how they can help us better visualize tornado site investigations.

  8. Unmanned Aerial Vehicles (UAVs): a new tool in counterterrorism operations?

    Science.gov (United States)

    Dörtbudak, Mehmet F.

    2015-05-01

    Terrorism is not a new phenomenon to the world, yet it remains difficult to define and counter. Countering terrorism requires several measures that must be taken simultaneously; however, counterterrorism strategies of many countries mostly depend on military measures. In the aftermath of the 2001 terrorist attack on the Twin Towers of the World Trade Center, the United States (U.S.) has started and led the campaign of Global War on Terrorism. They have invaded Afghanistan and Iraq and have encountered insurgencies run by terrorist organizations, such as al-Qaeda and its affiliates. The U.S. made the utilization of Air and Space Power very intensively during these operations. In order to implement operations; Intelligence, Surveillance, and Reconnaissance (ISR) assets were used to collect the necessary information. Before the successful insertion of a small number of U.S. Special Operation Force (SOF) teams into Afghanistan, the U.S. Air Force attacked al-Qaeda and Taliban's targets such as infrastructure, airfields, ground forces, command-control facilities etc. As soon as the U.S. troops got on the ground and started to marshal to Kabul, the Air Force supported them by attacking jointly determined targets. The Air Force continued to carry out the missions and played a significant role to achieve the objective of operation during all the time. This is not the only example of utilization of Air and Space Power in counterterrorism and counterinsurgency operations. All around the world, many countries have also made the utilization of Air Power in different missions ranging from ISR to attacking. Thinking that terrorism has a psychological dimension and losing a pilot during operations may result in decreasing the population support to operations, Unmanned Aerial Vehicles (UAVs) started to be used by practitioners and took priority over other assets. Although UAVs have been on the theatre for a long time used for ISR mission in conventional conflicts, with the advent

  9. Estimating plant distance in maize using Unmanned Aerial Vehicle (UAV).

    Science.gov (United States)

    Zhang, Jinshui; Basso, Bruno; Price, Richard F; Putman, Gregory; Shuai, Guanyuan

    2018-01-01

    Distance between rows and plants are essential parameters that affect the final grain yield in row crops. This paper presents the results of research intended to develop a novel method to quantify the distance between maize plants at field scale using an Unmanned Aerial Vehicle (UAV). Using this method, we can recognize maize plants as objects and calculate the distance between plants. We initially developed our method by training an algorithm in an indoor facility with plastic corn plants. Then, the method was scaled up and tested in a farmer's field with maize plant spacing that exhibited natural variation. The results of this study demonstrate that it is possible to precisely quantify the distance between maize plants. We found that accuracy of the measurement of the distance between maize plants depended on the height above ground level at which UAV imagery was taken. This study provides an innovative approach to quantify plant-to-plant variability and, thereby final crop yield estimates.

  10. Earthbound Unmanned Autonomous Vehicles (UAVS) As Planetary Science Testbeds

    Science.gov (United States)

    Pieri, D. C.; Bland, G.; Diaz, J. A.; Fladeland, M. M.

    2014-12-01

    Recent advances in the technology of unmanned vehicles have greatly expanded the range of contemplated terrestrial operational environments for their use, including aerial, surface, and submarine. The advances have been most pronounced in the areas of autonomy, miniaturization, durability, standardization, and ease of operation, most notably (especially in the popular press) for airborne vehicles. Of course, for a wide range of planetary venues, autonomy at high cost of both money and risk, has always been a requirement. Most recently, missions to Mars have also featured an unprecedented degree of mobility. Combining the traditional planetary surface deployment operational and science imperatives with emerging, very accessible, and relatively economical small UAV platforms on Earth can provide flexible, rugged, self-directed, test-bed platforms for landed instruments and strategies that will ultimately be directed elsewhere, and, in the process, provide valuable earth science data. While the most direct transfer of technology from terrestrial to planetary venues is perhaps for bodies with atmospheres (and oceans), with appropriate technology and strategy accommodations, single and networked UAVs can be designed to operate on even airless bodies, under a variety of gravities. In this presentation, we present and use results and lessons learned from our recent earth-bound UAV volcano deployments, as well as our future plans for such, to conceptualize a range of planetary and small-body missions. We gratefully acknowledge the assistance of students and colleagues at our home institutions, and the government of Costa Rica, without which our UAV deployments would not have been possible. This work was carried out, in part, at the Jet Propulsion Laboratory of the California Institute of Technology under contract to NASA.

  11. Unmanned Aerial Vehicle (UAV) data analysis for fertilization dose assessment

    Science.gov (United States)

    Kavvadias, Antonis; Psomiadis, Emmanouil; Chanioti, Maroulio; Tsitouras, Alexandros; Toulios, Leonidas; Dercas, Nicholas

    2017-10-01

    The growth rate monitoring of crops throughout their biological cycle is very important as it contributes to the achievement of a uniformly optimum production, a proper harvest planning, and reliable yield estimation. Fertilizer application often dramatically increases crop yields, but it is necessary to find out which is the ideal amount that has to be applied in the field. Remote sensing collects spatially dense information that may contribute to, or provide feedback about, fertilization management decisions. There is a potential goal to accurately predict the amount of fertilizer needed so as to attain an ideal crop yield without excessive use of fertilizers cause financial loss and negative environmental impacts. The comparison of the reflectance values at different wavelengths, utilizing suitable vegetation indices, is commonly used to determine plant vigor and growth. Unmanned Aerial Vehicles (UAVs) have several advantages; because they can be deployed quickly and repeatedly, they are flexible regarding flying height and timing of missions, and they can obtain very high-resolution imagery. In an experimental crop field in Eleftherio Larissa, Greece, different dose of pre-plant and in-season fertilization was applied in 27 plots. A total of 102 aerial photos in two flights were taken using an Unmanned Aerial Vehicle based on the scheduled fertilization. Α correlation of experimental fertilization with the change of vegetation indices values and with the increase of the vegetation cover rate during those days was made. The results of the analysis provide useful information regarding the vigor and crop growth rate performance of various doses of fertilization.

  12. Accuracy and Optimal Altitude for Physical Habitat Assessment (PHA of Stream Environments Using Unmanned Aerial Vehicles (UAV

    Directory of Open Access Journals (Sweden)

    Ângela Maria Klein Hentz

    2018-05-01

    Full Text Available Physical Habitat Assessments (PHA are useful to characterize and monitor stream and river habitat conditions, but can be costly and time-consuming. Alternative methods for data collection are getting attention, such as Unmanned Aerial Vehicles (UAV. The objective of this work was to evaluate the accuracy of UAV-based remote sensing techniques relative to ground-based PHA measurements, and to determine the influence of flight altitude on those accuracies. A UAV quadcopter equipped with an RGB camera was flown at the altitudes of 30.5 m, 61.0 m, 91.5 m and 122.0 m, and the metrics wetted width (Ww, bankfull width (Wbf and distance to water (Dw were compared to field PHA. The UAV-PHA method generated similar values to observed PHA values, but underestimated distance to water, and overestimated wetted width. Bankfull width provided the largest RMSE (25–28%. No systematic error patterns were observed considering the different flight altitudes, and results indicated that all flight altitudes investigated can be reliably used for PHA measurements. However, UAV flight at 61 m provided the most accurate results (CI = 0.05 considering all metrics. All UAV parameters over all altitudes showed significant correlation with observed PHA data, validating the use of UAV-based remote sensing for PHA.

  13. Unmanned aerial vehicles (UAVs) in pest management: Progress in the development of a UAV-deployed mating disruption system for Wisconsin cranberries

    Science.gov (United States)

    Unmanned aerial vehicles (UAVs) represent a powerful new tool for agriculture. Currently, UAVs are used almost exclusively as crop reconnaissance devices (“eyes in the sky”), not as pest control delivery systems. Research in Wisconsin cranberries is taking UAVs in a new direction. The Steffan and Lu...

  14. Photovoltaic electric power applied to Unmanned Aerial Vehicles (UAV)

    Science.gov (United States)

    Geis, Jack; Arnold, Jack H.

    1994-01-01

    Photovoltaic electric-powered flight is receiving a great deal of attention in the context of the United States' Unmanned Aerial Vehicle (UAV) program. This paper addresses some of the enabling technical areas and their potential solutions. Of particular interest are the long-duration, high-altitude class of UAV's whose mission it is to achieve altitudes between 60,000 and 100,000 feet, and to remain at those altitudes for prolonged periods performing various mapping and surveillance activities. Addressed herein are studies which reveal the need for extremely light-weight and efficient solar cells, high-efficiency electric motor-driven propeller modules, and power management and distribution control elements. Since the potential payloads vary dramatically in their power consumption and duty cycles, a typical load profile has been selected to provide commonality for the propulsion power comparisons. Since missions vary widely with respect to ground coverage requirements, from repeated orbiting over a localized target to long-distance routes over irregular terrain, we have also averaged the power requirements for on-board guidance and control power, as well as ground control and communication link utilization. In the context of the national technology reinvestment program, wherever possible we modeled components and materials which have been qualified for space and defense applications, yet are compatible with civilian UAV activities. These include, but are not limited to, solar cell developments, electric storage technology for diurnal operation, local and ground communications, power management and distribution, and control servo design. And finally, the results of tests conducted by Wright Laboratory on ultralight, highly efficient MOCVD GaAs solar cells purchased from EPI Materials Ltd. (EML) of the UK are presented. These cells were also used for modeling the flight characteristics of UAV aircraft.

  15. Photovoltaic electric power applied to Unmanned Aerial Vehicles (UAV)

    Science.gov (United States)

    Geis, Jack; Arnold, Jack H.

    1994-09-01

    Photovoltaic electric-powered flight is receiving a great deal of attention in the context of the United States' Unmanned Aerial Vehicle (UAV) program. This paper addresses some of the enabling technical areas and their potential solutions. Of particular interest are the long-duration, high-altitude class of UAV's whose mission it is to achieve altitudes between 60,000 and 100,000 feet, and to remain at those altitudes for prolonged periods performing various mapping and surveillance activities. Addressed herein are studies which reveal the need for extremely light-weight and efficient solar cells, high-efficiency electric motor-driven propeller modules, and power management and distribution control elements. Since the potential payloads vary dramatically in their power consumption and duty cycles, a typical load profile has been selected to provide commonality for the propulsion power comparisons. Since missions vary widely with respect to ground coverage requirements, from repeated orbiting over a localized target to long-distance routes over irregular terrain, we have also averaged the power requirements for on-board guidance and control power, as well as ground control and communication link utilization. In the context of the national technology reinvestment program, wherever possible we modeled components and materials which have been qualified for space and defense applications, yet are compatible with civilian UAV activities. These include, but are not limited to, solar cell developments, electric storage technology for diurnal operation, local and ground communications, power management and distribution, and control servo design. And finally, the results of tests conducted by Wright Laboratory on ultralight, highly efficient MOCVD GaAs solar cells purchased from EPI Materials Ltd. (EML) of the UK are presented. These cells were also used for modeling the flight characteristics of UAV aircraft.

  16. A fully convolutional network for weed mapping of unmanned aerial vehicle (UAV) imagery.

    Science.gov (United States)

    Huang, Huasheng; Deng, Jizhong; Lan, Yubin; Yang, Aqing; Deng, Xiaoling; Zhang, Lei

    2018-01-01

    Appropriate Site Specific Weed Management (SSWM) is crucial to ensure the crop yields. Within SSWM of large-scale area, remote sensing is a key technology to provide accurate weed distribution information. Compared with satellite and piloted aircraft remote sensing, unmanned aerial vehicle (UAV) is capable of capturing high spatial resolution imagery, which will provide more detailed information for weed mapping. The objective of this paper is to generate an accurate weed cover map based on UAV imagery. The UAV RGB imagery was collected in 2017 October over the rice field located in South China. The Fully Convolutional Network (FCN) method was proposed for weed mapping of the collected imagery. Transfer learning was used to improve generalization capability, and skip architecture was applied to increase the prediction accuracy. After that, the performance of FCN architecture was compared with Patch_based CNN algorithm and Pixel_based CNN method. Experimental results showed that our FCN method outperformed others, both in terms of accuracy and efficiency. The overall accuracy of the FCN approach was up to 0.935 and the accuracy for weed recognition was 0.883, which means that this algorithm is capable of generating accurate weed cover maps for the evaluated UAV imagery.

  17. Unmanned Aerial Vehicle (UAV) photogrammetry produces ...

    African Journals Online (AJOL)

    Structure from Motion (SfM) computer vision techniques were used to reconstruct the camera positions, terrain features and to derive ultra-high resolution point clouds, orthophotos and 3D models from the multi-view photos. The results of the geometric accuracy of the data based on the 20 GCPs were 0.018m for the overall ...

  18. DTM GENERATION WITH UAV BASED PHOTOGRAMMETRIC POINT CLOUD

    Directory of Open Access Journals (Sweden)

    N. Polat

    2017-11-01

    Full Text Available Nowadays Unmanned Aerial Vehicles (UAVs are widely used in many applications for different purposes. Their benefits however are not entirely detected due to the integration capabilities of other equipment such as; digital camera, GPS, or laser scanner. The main scope of this paper is evaluating performance of cameras integrated UAV for geomatic applications by the way of Digital Terrain Model (DTM generation in a small area. In this purpose, 7 ground control points are surveyed with RTK and 420 photographs are captured. Over 30 million georeferenced points were used in DTM generation process. Accuracy of the DTM was evaluated with 5 check points. The root mean square error is calculated as 17.1 cm for an altitude of 100 m. Besides, a LiDAR derived DTM is used as reference in order to calculate correlation. The UAV based DTM has o 94.5 % correlation with reference DTM. Outcomes of the study show that it is possible to use the UAV Photogrammetry data as map producing, surveying, and some other engineering applications with the advantages of low-cost, time conservation, and minimum field work.

  19. DTM Generation with Uav Based Photogrammetric Point Cloud

    Science.gov (United States)

    Polat, N.; Uysal, M.

    2017-11-01

    Nowadays Unmanned Aerial Vehicles (UAVs) are widely used in many applications for different purposes. Their benefits however are not entirely detected due to the integration capabilities of other equipment such as; digital camera, GPS, or laser scanner. The main scope of this paper is evaluating performance of cameras integrated UAV for geomatic applications by the way of Digital Terrain Model (DTM) generation in a small area. In this purpose, 7 ground control points are surveyed with RTK and 420 photographs are captured. Over 30 million georeferenced points were used in DTM generation process. Accuracy of the DTM was evaluated with 5 check points. The root mean square error is calculated as 17.1 cm for an altitude of 100 m. Besides, a LiDAR derived DTM is used as reference in order to calculate correlation. The UAV based DTM has o 94.5 % correlation with reference DTM. Outcomes of the study show that it is possible to use the UAV Photogrammetry data as map producing, surveying, and some other engineering applications with the advantages of low-cost, time conservation, and minimum field work.

  20. Unmanned aerial vehicles: The next big thing? The benefits and detriments of military and commercial UAVs

    OpenAIRE

    Hassan, L.

    2014-01-01

    With law enforcement agencies around the world investing in Unmanned Aerial Vehicles (UAVs, also known as drones) and small commercial drone ventures popping up like weeds, the debate on the morality of drone usage has intensified in the recent months. What are the advantages of UAVs? Are they worth the disadvantages?

  1. Unmanned aerial vehicles : The next big thing? The benefits and detriments of military and commercial UAVs

    NARCIS (Netherlands)

    Hassan, L.

    2014-01-01

    With law enforcement agencies around the world investing in Unmanned Aerial Vehicles (UAVs, also known as drones) and small commercial drone ventures popping up like weeds, the debate on the morality of drone usage has intensified in the recent months. What are the advantages of UAVs? Are they worth

  2. STRUCTURE FROM MOTION (SfM) PROCESSING FOR UNMANNED AERIAL VEHICLE (UAV)

    KAUST Repository

    Smith, Neil G.

    2016-04-07

    A method of imaging an area using an unmanned aerial vehicle (UAV) collects a plurality of images from a sensor mounted to the UAV. The plurality of images are processed to detect regions that require additional imaging and an updated flight plan and sensor gimbal position plan is created to capture portions of the area identified as requiring additional imaging.

  3. STRUCTURE FROM MOTION (SfM) PROCESSING FOR UNMANNED AERIAL VEHICLE (UAV)

    KAUST Repository

    Smith, Neil G.; Shalaby, Mohamed; Passone, Luca

    2016-01-01

    A method of imaging an area using an unmanned aerial vehicle (UAV) collects a plurality of images from a sensor mounted to the UAV. The plurality of images are processed to detect regions that require additional imaging and an updated flight plan and sensor gimbal position plan is created to capture portions of the area identified as requiring additional imaging.

  4. Design of Electric Patrol UAVs Based on a Dual Antenna System

    Directory of Open Access Journals (Sweden)

    Yongjie Zhai

    2018-04-01

    Full Text Available China completed the construction of more than 1.15 million kilometers of transmission lines with conventional voltage levels spanning its vast territory in 2014. This large and complicated power grid structure relies mainly on manual operation and maintenance of lines. Unmanned aerial vehicles (UAVs equipped with high-definition digital video cameras and cameras and GPS positioning systems can conduct autonomous patrols along the grid. However, the presence of electromagnetic fields around high-voltage transmission lines can affect the UAV’s magnetometer, resulting in a wrong heading and thus unsafe flight. In this paper, the traditional method of UAV heading calculation using a magnetometer was analyzed, and a novel method for calculating UAV heading based on dual antennas was proposed. Experimental data showed that the proposed method improves the anti-magnetic interference characteristics of UAVs and increases UAV security and stability for power inspection applications.

  5. High-resolution mapping based on an Unmanned Aerial Vehicle (UAV) to capture paleoseismic offsets along the Altyn-Tagh fault, China.

    Science.gov (United States)

    Gao, Mingxing; Xu, Xiwei; Klinger, Yann; van der Woerd, Jerome; Tapponnier, Paul

    2017-08-15

    The recent dramatic increase in millimeter- to centimeter- resolution topographic datasets obtained via multi-view photogrammetry raises the possibility of mapping detailed offset geomorphology and constraining the spatial characteristics of active faults. Here, for the first time, we applied this new method to acquire high-resolution imagery and generate topographic data along the Altyn Tagh fault, which is located in a remote high elevation area and shows preserved ancient earthquake surface ruptures. A digital elevation model (DEM) with a resolution of 0.065 m and an orthophoto with a resolution of 0.016 m were generated from these images. We identified piercing markers and reconstructed offsets based on both the orthoimage and the topography. The high-resolution UAV data were used to accurately measure the recent seismic offset. We obtained the recent offset of 7 ± 1 m. Combined with the high resolution satellite image, we measured cumulative offsets of 15 ± 2 m, 20 ± 2 m, 30 ± 2 m, which may be due to multiple paleo-earthquakes. Therefore, UAV mapping can provide fine-scale data for the assessment of the seismic hazards.

  6. Analysis of Unmanned Aerial Vehicle (UAV) hyperspectral remote sensing monitoring key technology in coastal wetland

    Science.gov (United States)

    Ma, Yi; Zhang, Jie; Zhang, Jingyu

    2016-01-01

    The coastal wetland, a transitional zone between terrestrial ecosystems and marine ecosystems, is the type of great value to ecosystem services. For the recent 3 decades, area of the coastal wetland is decreasing and the ecological function is gradually degraded with the rapid development of economy, which restricts the sustainable development of economy and society in the coastal areas of China in turn. It is a major demand of the national reality to carry out the monitoring of coastal wetlands, to master the distribution and dynamic change. UAV, namely unmanned aerial vehicle, is a new platform for remote sensing. Compared with the traditional satellite and manned aerial remote sensing, it has the advantage of flexible implementation, no cloud cover, strong initiative and low cost. Image-spectrum merging is one character of high spectral remote sensing. At the same time of imaging, the spectral curve of each pixel is obtained, which is suitable for quantitative remote sensing, fine classification and target detection. Aimed at the frontier and hotspot of remote sensing monitoring technology, and faced the demand of the coastal wetland monitoring, this paper used UAV and the new remote sensor of high spectral imaging instrument to carry out the analysis of the key technologies of monitoring coastal wetlands by UAV on the basis of the current situation in overseas and domestic and the analysis of developing trend. According to the characteristic of airborne hyperspectral data on UAV, that is "three high and one many", the key technology research that should develop are promoted as follows: 1) the atmosphere correction of the UAV hyperspectral in coastal wetlands under the circumstance of complex underlying surface and variable geometry, 2) the best observation scale and scale transformation method of the UAV platform while monitoring the coastal wetland features, 3) the classification and detection method of typical features with high precision from multi scale

  7. UAV Based Agricultural Planning and Landslide Monitoring

    Directory of Open Access Journals (Sweden)

    Servet Yaprak

    2017-12-01

    Full Text Available The use of Unmanned Aerial Vehicle (UAV tools has become widespread in map production, land surveying, landslide, erosion monitoring, monitoring of agricultural activities, aerial crop surveying, forest fire detection and monitoring operations. In this study, GEO 2 UAV manufactured by TEKNOMER equipped with SONY A6000 camera has been used. The flight plan have been performed with 100 m altitude, with 80% longitudinal and 60% side overlapping. Ground Control Points (GCPs have been observed with Topcon and Trimble GNSS geodetic receivers. Recorded GNSS signals have been processed with LGO V.8.4 software to get sensitive location information. 985 photos have been taken for the 344 hectares the agricultural area. 291 photos have been taken for 50 hectares the landslide area. All photos were processed by PIX4D software. For the agricultural area, 25 GCPs and for the landslide area, 8 GCPs have been included in the evaluation. 3D images were produced with pixel matching algorithms. As a result, the RMS evaluation was obtained as ±0.054 m for the agricultural area and as ±0.018 m for the landslide area. UAV images have indisputable contributions to the management of catastrophes such as landslides and earthquakes, and it is impossible to make terrestrial measurements in areas where disaster impact continues.

  8. Preservation potential of subtle glacial landforms based on detailed mapping of recently exposed proglacial areas: application of unmanned aerial vehicle (UAV) and structure-from-motion (SfM)

    Science.gov (United States)

    Ewertowski, Marek; Evans, David; Roberts, David; Tomczyk, Aleksandra; Ewertowski, Wojciech

    2016-04-01

    Ongoing glacier retreat results in the continuous exposure of proglacial areas. Such areas contain invaluable information about glacial process-form relationships manifest in specific landform assemblages. However, preservation potential of freshly exposed glacial landforms is very low, as proglacial terrains are one of the most dynamic parts of the landscape. Therefore, rapid mapping and geomorphological characterisation of such areas is important from a glaciological and geomorphological point of view for proper understanding and reconstruction of glacier-landform dynamics and chronology of glacial events. Annual patterns of recession and relatively small areas exposed every year, mean that the performing of regular aerial or satellite survey is expensive and therefore impractical. Recent advances in technology enables the development of low-cost alternatives for traditional aerial surveys. Small unmanned aerial vehicles (UAV) can be used to acquire high-resolution (several cm) low-altitude photographs. The UAV-based photographs can be subsequently processed through the structure-from-motion process to generate detailed orthophotomaps and digital elevation models. In this study we present case studies from the forelands of various glaciers on Iceland and Svalbard representing different types of proglacial landscapes: Fláajökull (annual push moraines); Hofellsjökul (bedrock bedforms and push moraines); Fjallsjökull (marginal drainage network); Rieperbreen (crevasse squeeze ridges and longitudinal debris stripes); Ayerbreen (transverse debris ridges); Foxfonna (longitudinal debris stripes);Hørbyebreen (geometric ridge network); Nordenskiöldbreen (fluted till surface); Ebbabreen (controlled moraine complex). UAV campaigns were conducted using a low-cost quadcopter platform. Resultant orthophotos and DEMs enabled mapping and assessment of recent glacial landscape development in different types of glacial landsystems. Results of our study indicate that

  9. Cost and effectiveness analysis on unmanned aerial vehicle (UAV) use at border security

    Science.gov (United States)

    Yilmaz, Bahadır.

    2013-06-01

    Drones and Remotely Piloted Vehicles are types of Unmanned Aerial Vehicles. UAVs began to be used with the war of Vietnam, they had a great interest when Israel used them in Bekaa Valley Operations of 1982. UAVs have been used by different countries with different aims with the help of emerging technology and investments. In this article, in the context of areas of UAV usage in national security, benefits and disadvantages of UAVs are put forward. Particularly, it has been evaluated on the basis of cost-effectiveness by focusing the use of UAV in the border security. UAVs have been studied by taking cost analysis, procurement and operational costs into consideration. Analysis of effectiveness has been done with illegal passages of people and drugs from flight times of UAVs. Although the procurement cost of the medium-level UAVs is low, its operational costs are high. For this reason, the idea of less costly alternative systems have been revealed for the border security. As the costs are reduced to acceptable level involving national security and border security in future with high-technology products in their structure, it will continue to be used in an increasing proportion.

  10. Cross Validation on the Equality of Uav-Based and Contour-Based Dems

    Science.gov (United States)

    Ma, R.; Xu, Z.; Wu, L.; Liu, S.

    2018-04-01

    Unmanned Aerial Vehicles (UAV) have been widely used for Digital Elevation Model (DEM) generation in geographic applications. This paper proposes a novel framework of generating DEM from UAV images. It starts with the generation of the point clouds by image matching, where the flight control data are used as reference for searching for the corresponding images, leading to a significant time saving. Besides, a set of ground control points (GCP) obtained from field surveying are used to transform the point clouds to the user's coordinate system. Following that, we use a multi-feature based supervised classification method for discriminating non-ground points from ground ones. In the end, we generate DEM by constructing triangular irregular networks and rasterization. The experiments are conducted in the east of Jilin province in China, which has been suffered from soil erosion for several years. The quality of UAV based DEM (UAV-DEM) is compared with that generated from contour interpolation (Contour-DEM). The comparison shows a higher resolution, as well as higher accuracy of UAV-DEMs, which contains more geographic information. In addition, the RMSE errors of the UAV-DEMs generated from point clouds with and without GCPs are ±0.5 m and ±20 m, respectively.

  11. A Biologically Based Chemo-Sensing UAV for Humanitarian Demining

    Directory of Open Access Journals (Sweden)

    Paul F.M.J. Verschure

    2008-11-01

    Full Text Available Antipersonnel mines, weapons of cheap manufacture but lethal effect, have a high impact on the population even decades after the conflicts have finished. Here we investigate the use of a chemo-sensing Unmanned Aerial Vehicle (cUAV for demining tasks. We developed a blimp based UAV that is equipped with a broadly tuned metal-thin oxide chemo-sensor. A number of chemical mapping strategies were investigated including two biologically based localization strategies derived from the moth chemical search that can optimize the efficiency of the detection and localization of explosives and therefore be used in the demining process. Additionally, we developed a control layer that allows for both fully autonomous and manual controlled flight, as well as for the scheduling of a fleet of cUAVs. Our results confirm the feasibility of this technology for demining in real-world scenarios and give further support to a biologically based approach where the understanding of biological systems is used to solve difficult engineering problems.

  12. A Biologically Based Chemo-Sensing UAV for Humanitarian Demining

    Directory of Open Access Journals (Sweden)

    Sergi Bermúdez i Badia

    2007-06-01

    Full Text Available Antipersonnel mines, weapons of cheap manufacture but lethal effect, have a high impact on the population even decades after the conflicts have finished. Here we investigate the use of a chemo-sensing Unmanned Aerial Vehicle (cUAV for demining tasks. We developed a blimp based UAV that is equipped with a broadly tuned metal-thin oxide chemo-sensor. A number of chemical mapping strategies were investigated including two biologically based localization strategies derived from the moth chemical search that can optimize the efficiency of the detection and localization of explosives and therefore be used in the demining process. Additionally, we developed a control layer that allows for both fully autonomous and manual controlled flight, as well as for the scheduling of a fleet of cUAVs. Our results confirm the feasibility of this technology for demining in real-world scenarios and give further support to a biologically based approach where the understanding of biological systems is used to solve difficult engineering problems.

  13. Pricise Target Geolocation and Tracking Based on Uav Video Imagery

    Science.gov (United States)

    Hosseinpoor, H. R.; Samadzadegan, F.; Dadrasjavan, F.

    2016-06-01

    There is an increasingly large number of applications for Unmanned Aerial Vehicles (UAVs) from monitoring, mapping and target geolocation. However, most of commercial UAVs are equipped with low-cost navigation sensors such as C/A code GPS and a low-cost IMU on board, allowing a positioning accuracy of 5 to 10 meters. This low accuracy cannot be used in applications that require high precision data on cm-level. This paper presents a precise process for geolocation of ground targets based on thermal video imagery acquired by small UAV equipped with RTK GPS. The geolocation data is filtered using an extended Kalman filter, which provides a smoothed estimate of target location and target velocity. The accurate geo-locating of targets during image acquisition is conducted via traditional photogrammetric bundle adjustment equations using accurate exterior parameters achieved by on board IMU and RTK GPS sensors, Kalman filtering and interior orientation parameters of thermal camera from pre-flight laboratory calibration process. The results of this study compared with code-based ordinary GPS, indicate that RTK observation with proposed method shows more than 10 times improvement of accuracy in target geolocation.

  14. The UAV take-off and landing system used for small areas of mobile vehicles

    Science.gov (United States)

    Ren, Tian-Yu; Duanmu, Qing-Duo; Wu, Bo-Qi

    2018-03-01

    In order to realize an UAV formation cluster system based on the current GPS and the fault and insufficiency of Beidou integrated navigation system in strong jamming environment. Due to the impact of the compass on the plane crash, navigation system error caused by the mobile area to help reduce the need for large landing sites and not in the small fast moving area to achieve the reality of the landing. By using Strapdown inertial and all-optical system to form Composite UAV flight control system, the photoelectric composite strapdown inertial coupling is realized, and through the laser and microwave telemetry link compound communication mechanism, using all-optical strapdown inertial and visual navigation system to solve the deviation of take-off and landing caused by electromagnetic interference, all-optical bidirectional data link realizes two-way position correction of landing site and aircraft, thus achieves the accurate recovery of UAV formation cluster in the mobile narrow area which the traditional navigation system can't realize. This system is a set of efficient unmanned aerial vehicle Group Take-off/descending system, which is suitable for many tasks, and not only realizes the reliable continuous navigation under the complex electromagnetic interference environment, moreover, the intelligent flight and Take-off and landing of unmanned aerial vehicles relative to the fast moving and small recovery sites in complex electromagnetic interference environment can not only improve the safe operation rate of unmanned aerial vehicle, but also guarantee the operation safety of the aircraft, and the more has important social value for the application foreground of the aircraft.

  15. Assessing the Accuracy of Georeferenced Point Clouds Produced via Multi-View Stereopsis from Unmanned Aerial Vehicle (UAV Imagery

    Directory of Open Access Journals (Sweden)

    Arko Lucieer

    2012-05-01

    Full Text Available Sensor miniaturisation, improved battery technology and the availability of low-cost yet advanced Unmanned Aerial Vehicles (UAV have provided new opportunities for environmental remote sensing. The UAV provides a platform for close-range aerial photography. Detailed imagery captured from micro-UAV can produce dense point clouds using multi-view stereopsis (MVS techniques combining photogrammetry and computer vision. This study applies MVS techniques to imagery acquired from a multi-rotor micro-UAV of a natural coastal site in southeastern Tasmania, Australia. A very dense point cloud ( < 1–3 cm point spacing is produced in an arbitrary coordinate system using full resolution imagery, whereas other studies usually downsample the original imagery. The point cloud is sparse in areas of complex vegetation and where surfaces have a homogeneous texture. Ground control points collected with Differential Global Positioning System (DGPS are identified and used for georeferencing via a Helmert transformation. This study compared georeferenced point clouds to a Total Station survey in order to assess and quantify their geometric accuracy. The results indicate that a georeferenced point cloud accurate to 25–40 mm can be obtained from imagery acquired from 50 m. UAV-based image capture provides the spatial and temporal resolution required to map and monitor natural landscapes. This paper assesses the accuracy of the generated point clouds based on field survey points. Based on our key findings we conclude that sub-decimetre terrain change (in this case coastal erosion can be monitored.

  16. Wavelength-Adaptive Dehazing Using Histogram Merging-Based Classification for UAV Images

    Directory of Open Access Journals (Sweden)

    Inhye Yoon

    2015-03-01

    Full Text Available Since incoming light to an unmanned aerial vehicle (UAV platform can be scattered by haze and dust in the atmosphere, the acquired image loses the original color and brightness of the subject. Enhancement of hazy images is an important task in improving the visibility of various UAV images. This paper presents a spatially-adaptive dehazing algorithm that merges color histograms with consideration of the wavelength-dependent atmospheric turbidity. Based on the wavelength-adaptive hazy image acquisition model, the proposed dehazing algorithm consists of three steps: (i image segmentation based on geometric classes; (ii generation of the context-adaptive transmission map; and (iii intensity transformation for enhancing a hazy UAV image. The major contribution of the research is a novel hazy UAV image degradation model by considering the wavelength of light sources. In addition, the proposed transmission map provides a theoretical basis to differentiate visually important regions from others based on the turbidity and merged classification results.

  17. Wavelength-adaptive dehazing using histogram merging-based classification for UAV images.

    Science.gov (United States)

    Yoon, Inhye; Jeong, Seokhwa; Jeong, Jaeheon; Seo, Doochun; Paik, Joonki

    2015-03-19

    Since incoming light to an unmanned aerial vehicle (UAV) platform can be scattered by haze and dust in the atmosphere, the acquired image loses the original color and brightness of the subject. Enhancement of hazy images is an important task in improving the visibility of various UAV images. This paper presents a spatially-adaptive dehazing algorithm that merges color histograms with consideration of the wavelength-dependent atmospheric turbidity. Based on the wavelength-adaptive hazy image acquisition model, the proposed dehazing algorithm consists of three steps: (i) image segmentation based on geometric classes; (ii) generation of the context-adaptive transmission map; and (iii) intensity transformation for enhancing a hazy UAV image. The major contribution of the research is a novel hazy UAV image degradation model by considering the wavelength of light sources. In addition, the proposed transmission map provides a theoretical basis to differentiate visually important regions from others based on the turbidity and merged classification results.

  18. Uav Positioning and Collision Avoidance Based on RSS Measurements

    Science.gov (United States)

    Masiero, A.; Fissore, F.; Guarnieri, A.; Pirotti, F.; Vettore, A.

    2015-08-01

    In recent years, Unmanned Aerial Vehicles (UAVs) are attracting more and more attention in both the research and industrial communities: indeed, the possibility to use them in a wide range of remote sensing applications makes them a very flexible and attractive solution in both civil and commercial cases (e.g. precision agriculture, security and control, monitoring of sites, exploration of areas difficult to reach). Most of the existing UAV positioning systems rely on the use of the GPS signal. Despite this can be a satisfactory solution in open environments where the GPS signal is available, there are several operating conditions of interest where it is unavailable or unreliable (e.g. close to high buildings, or mountains, in indoor environments). Consequently, a different approach has to be adopted in these cases. This paper considers the use ofWiFi measurements in order to obtain position estimations of the device of interest. More specifically, to limit the costs for the devices involved in the positioning operations, an approach based on radio signal strengths (RSS) measurements is considered. Thanks to the use of a Kalman filter, the proposed approach takes advantage of the temporal dynamic of the device of interest in order to improve the positioning results initially provided by means of maximum likelihood estimations. The considered UAVs are assumed to be provided with communication devices, which can allow them to communicate with each other in order to improve their cooperation abilities. In particular, the collision avoidance problem is examined in this work.

  19. Autonomous target tracking of UAVs based on low-power neural network hardware

    Science.gov (United States)

    Yang, Wei; Jin, Zhanpeng; Thiem, Clare; Wysocki, Bryant; Shen, Dan; Chen, Genshe

    2014-05-01

    Detecting and identifying targets in unmanned aerial vehicle (UAV) images and videos have been challenging problems due to various types of image distortion. Moreover, the significantly high processing overhead of existing image/video processing techniques and the limited computing resources available on UAVs force most of the processing tasks to be performed by the ground control station (GCS) in an off-line manner. In order to achieve fast and autonomous target identification on UAVs, it is thus imperative to investigate novel processing paradigms that can fulfill the real-time processing requirements, while fitting the size, weight, and power (SWaP) constrained environment. In this paper, we present a new autonomous target identification approach on UAVs, leveraging the emerging neuromorphic hardware which is capable of massively parallel pattern recognition processing and demands only a limited level of power consumption. A proof-of-concept prototype was developed based on a micro-UAV platform (Parrot AR Drone) and the CogniMemTMneural network chip, for processing the video data acquired from a UAV camera on the y. The aim of this study was to demonstrate the feasibility and potential of incorporating emerging neuromorphic hardware into next-generation UAVs and their superior performance and power advantages towards the real-time, autonomous target tracking.

  20. Multi-Unmanned Aerial Vehicle (UAV) Cooperative Fault Detection Employing Differential Global Positioning (DGPS), Inertial and Vision Sensors.

    Science.gov (United States)

    Heredia, Guillermo; Caballero, Fernando; Maza, Iván; Merino, Luis; Viguria, Antidio; Ollero, Aníbal

    2009-01-01

    This paper presents a method to increase the reliability of Unmanned Aerial Vehicle (UAV) sensor Fault Detection and Identification (FDI) in a multi-UAV context. Differential Global Positioning System (DGPS) and inertial sensors are used for sensor FDI in each UAV. The method uses additional position estimations that augment individual UAV FDI system. These additional estimations are obtained using images from the same planar scene taken from two different UAVs. Since accuracy and noise level of the estimation depends on several factors, dynamic replanning of the multi-UAV team can be used to obtain a better estimation in case of faults caused by slow growing errors of absolute position estimation that cannot be detected by using local FDI in the UAVs. Experimental results with data from two real UAVs are also presented.

  1. Exploring Naval Tactics with UAVs in an Island Complex Using Agent-Based Simulation

    National Research Council Canada - National Science Library

    Lalis, Vasileios

    2007-01-01

    The benefits of Unmanned Aerial Vehicles (UAV) at sea are undisputed. The amount and speed of the incoming information from a UAV, combined with its maneuverability and time-on-task capability, are assets to any navy...

  2. A meta-analysis of human-system interfaces in unmanned aerial vehicle (UAV) swarm management.

    Science.gov (United States)

    Hocraffer, Amy; Nam, Chang S

    2017-01-01

    A meta-analysis was conducted to systematically evaluate the current state of research on human-system interfaces for users controlling semi-autonomous swarms composed of groups of drones or unmanned aerial vehicles (UAVs). UAV swarms pose several human factors challenges, such as high cognitive demands, non-intuitive behavior, and serious consequences for errors. This article presents findings from a meta-analysis of 27 UAV swarm management papers focused on the human-system interface and human factors concerns, providing an overview of the advantages, challenges, and limitations of current UAV management interfaces, as well as information on how these interfaces are currently evaluated. In general allowing user and mission-specific customization to user interfaces and raising the swarm's level of autonomy to reduce operator cognitive workload are beneficial and improve situation awareness (SA). It is clear more research is needed in this rapidly evolving field. Copyright © 2016 Elsevier Ltd. All rights reserved.

  3. VISION BASED OBSTACLE DETECTION IN UAV IMAGING

    Directory of Open Access Journals (Sweden)

    S. Badrloo

    2017-08-01

    Full Text Available Detecting and preventing incidence with obstacles is crucial in UAV navigation and control. Most of the common obstacle detection techniques are currently sensor-based. Small UAVs are not able to carry obstacle detection sensors such as radar; therefore, vision-based methods are considered, which can be divided into stereo-based and mono-based techniques. Mono-based methods are classified into two groups: Foreground-background separation, and brain-inspired methods. Brain-inspired methods are highly efficient in obstacle detection; hence, this research aims to detect obstacles using brain-inspired techniques, which try to enlarge the obstacle by approaching it. A recent research in this field, has concentrated on matching the SIFT points along with, SIFT size-ratio factor and area-ratio of convex hulls in two consecutive frames to detect obstacles. This method is not able to distinguish between near and far obstacles or the obstacles in complex environment, and is sensitive to wrong matched points. In order to solve the above mentioned problems, this research calculates the dist-ratio of matched points. Then, each and every point is investigated for Distinguishing between far and close obstacles. The results demonstrated the high efficiency of the proposed method in complex environments.

  4. Design and Implementation of a Fully Autonomous UAV's Navigator Based on Omni-directional Vision System

    Directory of Open Access Journals (Sweden)

    Seyed Mohammadreza Kasaei

    2011-12-01

    Full Text Available Unmanned Aerial Vehicles (UAVs are the subject of an increasing interest in many applications . UAVs are seeing more widespread use in military, scenic, and civilian sectors in recent years. Autonomy is one of the major advantages of these vehicles. It is then necessary to develop particular sensor in order to provide efficient navigation functions. The helicopter has been stabilized with visual information through the control loop. Omni directional vision can be a useful sensor for this propose. It can be used as the only sensor or as complementary sensor. In this paper , we propose a novel method for path planning on an UAV based on electrical potential .We are using an omni directional vision system for navigating and path planning.

  5. Survey on the novel hybrid aquatic-aerial amphibious aircraft: Aquatic unmanned aerial vehicle (AquaUAV)

    Science.gov (United States)

    Yang, Xingbang; Wang, Tianmiao; Liang, Jianhong; Yao, Guocai; Liu, Miao

    2015-04-01

    The aquatic unmanned aerial vehicle (AquaUAV), a kind of vehicle that can operate both in the air and the water, has been regarded as a new breakthrough to broaden the application scenario of UAV. Wide application prospects in military and civil field are more than bright, therefore many institutions have focused on the development of such a vehicle. However, due to the significant difference of the physical properties between the air and the water, it is rather difficult to design a fully-featured AquaUAV. Until now, majority of partially-featured AquaUAVs have been developed and used to verify the feasibility of an aquatic-aerial vehicle. In the present work, we classify the current partially-featured AquaUAV into three categories from the scope of the whole UAV field, i.e., the seaplane UAV, the submarine-launched UAV, and the submersible UAV. Then the recent advancements and common characteristics of the three kinds of AquaUAVs are reviewed in detail respectively. Then the applications of bionics in the design of AquaUAV, the transition mode between the air and the water, the morphing wing structure for air-water adaptation, and the power source and the propulsion type are summarized and discussed. The tradeoff analyses for different transition methods between the air and the water are presented. Furthermore, it indicates that applying the bionics into the design and development of the AquaUAV will be essential and significant. Finally, the significant technical challenges for the AquaUAV to change from a conception to a practical prototype are indicated.

  6. Doppler Effect-Based Automatic Landing Procedure for UAV in Difficult Access Environments

    Directory of Open Access Journals (Sweden)

    Jan M. Kelner

    2017-01-01

    Full Text Available Currently, almost unrestricted access to low-lying areas of airspace creates an opportunity to use unmanned aerial vehicles (UAVs, especially those capable of vertical take-off and landing (VTOL, in transport services. UAVs become increasingly popular for transporting postal items over small, medium, and large distances. It is forecasted that, in the near future, VTOL UAVs with a high take-off weight will also deliver goods to very distant and hard-to-reach locations. Therefore, UAV navigation plays a very important role in the process of carrying out transport services. At present, during the flight phase, drones make use of the integrated global navigation satellite system (GNSS and the inertial navigation system (INS. However, the inaccuracy of GNSS + INS makes it unsuitable for landing and take-off, necessitating the guidance of a human UAV operator during those phases. Available navigation systems do not provide sufficiently high positioning accuracy for an UAV. For this reason, full automation of the landing approach is not possible. This paper puts forward a proposal to solve this problem. The authors show the structure of an autonomous system and a Doppler-based navigation procedure that allows for automatic landing approaches. An accuracy evaluation of the developed solution for VTOL is made on the basis of simulation studies.

  7. POTENTIAL OF UAV-BASED LASER SCANNER AND MULTISPECTRAL CAMERA DATA IN BUILDING INSPECTION

    Directory of Open Access Journals (Sweden)

    D. Mader

    2016-06-01

    Full Text Available Conventional building inspection of bridges, dams or large constructions in general is rather time consuming and often cost expensive due to traffic closures and the need of special heavy vehicles such as under-bridge inspection units or other large lifting platforms. In consideration that, an unmanned aerial vehicle (UAV will be more reliable and efficient as well as less expensive and simpler to operate. The utilisation of UAVs as an assisting tool in building inspections is obviously. Furthermore, light-weight special sensors such as infrared and thermal cameras as well as laser scanner are available and predestined for usage on unmanned aircraft systems. Such a flexible low-cost system is realized in the ADFEX project with the goal of time-efficient object exploration, monitoring and damage detection. For this purpose, a fleet of UAVs, equipped with several sensors for navigation, obstacle avoidance and 3D object-data acquisition, has been developed and constructed. This contribution deals with the potential of UAV-based data in building inspection. Therefore, an overview of the ADFEX project, sensor specifications and requirements of building inspections in general are given. On the basis of results achieved in practical studies, the applicability and potential of the UAV system in building inspection will be presented and discussed.

  8. Measurement of greenhouse gases in UAE by using Unmanned Aerial Vehicle (UAV)

    Science.gov (United States)

    Abou-Elnour, Ali; Odeh, Mohamed; Abdelrhman, Mohammed; Balkis, Ahmed; Amira, Abdelraouf

    2017-04-01

    In the present work, a reliable and low cost system has been designed and implemented to measure greenhouse gases (GHG) in United Arab Emirates (UAE) by using unmanned aerial vehicle (UAV). A set of accurate gas, temperature, pressure, humidity sensors are integrated together with a wireless communication system on a microcontroller based platform to continuously measure the required data. The system instantaneously sends the measured data to a center monitoring unit via the wireless communication system. In addition, the proposed system has the features that all measurements are recorded directly in a storage device to allow effective monitoring in regions with weak or no wireless coverage. The obtained data will be used in all further sophisticated calculations for environmental research and monitoring purposes.

  9. Weed map generation from UAV image mosaics based on crop row detection

    DEFF Research Database (Denmark)

    Midtiby, Henrik Skov

    To control weed in a field effectively with a minimum of herbicides, knowledge about the weed patches is required. Based on images acquired by Unmanned Aerial Vehicles (UAVs), a vegetation map of the entire field can be generated. Manual analysis, which is often required, to detect weed patches...... is used as input for the method. Issues related to perspective distortion are reduced by using an orthomosaic, which is a high resolution image of the entire field, built from hundreds of images taken by a UAV. A vegetation map is generated from the orthomosaic by calculating the excess green color index...

  10. PERFORMANCE CHARACTERISTIC MEMS-BASED IMUs FOR UAVs NAVIGATION

    Directory of Open Access Journals (Sweden)

    H. A. Mohamed

    2015-08-01

    Full Text Available Accurate 3D reconstruction has become essential for non-traditional mapping applications such as urban planning, mining industry, environmental monitoring, navigation, surveillance, pipeline inspection, infrastructure monitoring, landslide hazard analysis, indoor localization, and military simulation. The needs of these applications cannot be satisfied by traditional mapping, which is based on dedicated data acquisition systems designed for mapping purposes. Recent advances in hardware and software development have made it possible to conduct accurate 3D mapping without using costly and high-end data acquisition systems. Low-cost digital cameras, laser scanners, and navigation systems can provide accurate mapping if they are properly integrated at the hardware and software levels. Unmanned Aerial Vehicles (UAVs are emerging as a mobile mapping platform that can provide additional economical and practical advantages. However, such economical and practical requirements need navigation systems that can provide uninterrupted navigation solution. Hence, testing the performance characteristics of Micro-Electro-Mechanical Systems (MEMS or low cost navigation sensors for various UAV applications is important research. This work focuses on studying the performance characteristics under different manoeuvres using inertial measurements integrated with single point positioning, Real-Time-Kinematic (RTK, and additional navigational aiding sensors. Furthermore, the performance of the inertial sensors is tested during Global Positioning System (GPS signal outage.

  11. Performance Characteristic Mems-Based IMUs for UAVs Navigation

    Science.gov (United States)

    Mohamed, H. A.; Hansen, J. M.; Elhabiby, M. M.; El-Sheimy, N.; Sesay, A. B.

    2015-08-01

    Accurate 3D reconstruction has become essential for non-traditional mapping applications such as urban planning, mining industry, environmental monitoring, navigation, surveillance, pipeline inspection, infrastructure monitoring, landslide hazard analysis, indoor localization, and military simulation. The needs of these applications cannot be satisfied by traditional mapping, which is based on dedicated data acquisition systems designed for mapping purposes. Recent advances in hardware and software development have made it possible to conduct accurate 3D mapping without using costly and high-end data acquisition systems. Low-cost digital cameras, laser scanners, and navigation systems can provide accurate mapping if they are properly integrated at the hardware and software levels. Unmanned Aerial Vehicles (UAVs) are emerging as a mobile mapping platform that can provide additional economical and practical advantages. However, such economical and practical requirements need navigation systems that can provide uninterrupted navigation solution. Hence, testing the performance characteristics of Micro-Electro-Mechanical Systems (MEMS) or low cost navigation sensors for various UAV applications is important research. This work focuses on studying the performance characteristics under different manoeuvres using inertial measurements integrated with single point positioning, Real-Time-Kinematic (RTK), and additional navigational aiding sensors. Furthermore, the performance of the inertial sensors is tested during Global Positioning System (GPS) signal outage.

  12. PROCESSING OF UAV BASED RANGE IMAGING DATA TO GENERATE DETAILED ELEVATION MODELS OF COMPLEX NATURAL STRUCTURES

    Directory of Open Access Journals (Sweden)

    T. K. Kohoutek

    2012-07-01

    Full Text Available Unmanned Aerial Vehicles (UAVs are more and more used in civil areas like geomatics. Autonomous navigated platforms have a great flexibility in flying and manoeuvring in complex environments to collect remote sensing data. In contrast to standard technologies such as aerial manned platforms (airplanes and helicopters UAVs are able to fly closer to the object and in small-scale areas of high-risk situations such as landslides, volcano and earthquake areas and floodplains. Thus, UAVs are sometimes the only practical alternative in areas where access is difficult and where no manned aircraft is available or even no flight permission is given. Furthermore, compared to terrestrial platforms, UAVs are not limited to specific view directions and could overcome occlusions from trees, houses and terrain structures. Equipped with image sensors and/or laser scanners they are able to provide elevation models, rectified images, textured 3D-models and maps. In this paper we will describe a UAV platform, which can carry a range imaging (RIM camera including power supply and data storage for the detailed mapping and monitoring of complex structures, such as alpine riverbed areas. The UAV platform NEO from Swiss UAV was equipped with the RIM camera CamCube 2.0 by PMD Technologies GmbH to capture the surface structures. Its navigation system includes an autopilot. To validate the UAV-trajectory a 360° prism was installed and tracked by a total station. Within the paper a workflow for the processing of UAV-RIM data is proposed, which is based on the processing of differential GNSS data in combination with the acquired range images. Subsequently, the obtained results for the trajectory are compared and verified with a track of a UAV (Falcon 8, Ascending Technologies carried out with a total station simultaneously to the GNSS data acquisition. The results showed that the UAV's position using differential GNSS could be determined in the centimetre to the decimetre

  13. Pigeon interaction mode switch-based UAV distributed flocking control under obstacle environments.

    Science.gov (United States)

    Qiu, Huaxin; Duan, Haibin

    2017-11-01

    Unmanned aerial vehicle (UAV) flocking control is a serious and challenging problem due to local interactions and changing environments. In this paper, a pigeon flocking model and a pigeon coordinated obstacle-avoiding model are proposed based on a behavior that pigeon flocks will switch between hierarchical and egalitarian interaction mode at different flight phases. Owning to the similarity between bird flocks and UAV swarms in essence, a distributed flocking control algorithm based on the proposed pigeon flocking and coordinated obstacle-avoiding models is designed to coordinate a heterogeneous UAV swarm to fly though obstacle environments with few informed individuals. The comparative simulation results are elaborated to show the feasibility, validity and superiority of our proposed algorithm. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  14. Uav Visual Autolocalizaton Based on Automatic Landmark Recognition

    Science.gov (United States)

    Silva Filho, P.; Shiguemori, E. H.; Saotome, O.

    2017-08-01

    Deploying an autonomous unmanned aerial vehicle in GPS-denied areas is a highly discussed problem in the scientific community. There are several approaches being developed, but the main strategies yet considered are computer vision based navigation systems. This work presents a new real-time computer-vision position estimator for UAV navigation. The estimator uses images captured during flight to recognize specific, well-known, landmarks in order to estimate the latitude and longitude of the aircraft. The method was tested in a simulated environment, using a dataset of real aerial images obtained in previous flights, with synchronized images, GPS and IMU data. The estimated position in each landmark recognition was compatible with the GPS data, stating that the developed method can be used as an alternative navigation system.

  15. UAV VISUAL AUTOLOCALIZATON BASED ON AUTOMATIC LANDMARK RECOGNITION

    Directory of Open Access Journals (Sweden)

    P. Silva Filho

    2017-08-01

    Full Text Available Deploying an autonomous unmanned aerial vehicle in GPS-denied areas is a highly discussed problem in the scientific community. There are several approaches being developed, but the main strategies yet considered are computer vision based navigation systems. This work presents a new real-time computer-vision position estimator for UAV navigation. The estimator uses images captured during flight to recognize specific, well-known, landmarks in order to estimate the latitude and longitude of the aircraft. The method was tested in a simulated environment, using a dataset of real aerial images obtained in previous flights, with synchronized images, GPS and IMU data. The estimated position in each landmark recognition was compatible with the GPS data, stating that the developed method can be used as an alternative navigation system.

  16. Moments of Inertia: Uninhabited Aerial Vehicle (UAV) Dryden Remotely Operated Integrated Drone (DROID)

    Science.gov (United States)

    Haro, Helida C.

    2010-01-01

    The objective of this research effort is to determine the most appropriate, cost efficient, and effective method to utilize for finding moments of inertia for the Uninhabited Aerial Vehicle (UAV) Dryden Remotely Operated Integrated Drone (DROID). A moment is a measure of the body's tendency to turn about its center of gravity (CG) and inertia is the resistance of a body to changes in its momentum. Therefore, the moment of inertia (MOI) is a body's resistance to change in rotation about its CG. The inertial characteristics of an UAV have direct consequences on aerodynamics, propulsion, structures, and control. Therefore, it is imperative to determine the precise inertial characteristics of the DROID.

  17. Moments of Inertia - Uninhabited Aerial Vehicle (UAV) Dryden Remotely Operated Integrated Drone (DROID)

    Science.gov (United States)

    Haro, Helida C.

    2010-01-01

    The objective of this research effort is to determine the most appropriate, cost efficient, and effective method to utilize for finding moments of inertia for the Uninhabited Aerial Vehicle (UAV) Dryden Remotely Operated Integrated Drone (DROID). A moment is a measure of the body's tendency to turn about its center of gravity (CG) and inertia is the resistance of a body to changes in its momentum. Therefore, the moment of inertia (MOI) is a body's resistance to change in rotation about its CG. The inertial characteristics of an UAV have direct consequences on aerodynamics, propulsion, structures, and control. Therefore, it is imperative to determine the precise inertial characteristics of the DROID.

  18. Using Unmanned Aerial Vehicles (UAV for High-Resolution Reconstruction of Topography: The Structure from Motion Approach on Coastal Environments

    Directory of Open Access Journals (Sweden)

    Francesco Mancini

    2013-12-01

    Full Text Available The availability of high-resolution Digital Surface Models of coastal environments is of increasing interest for scientists involved in the study of the coastal system processes. Among the range of terrestrial and aerial methods available to produce such a dataset, this study tests the utility of the Structure from Motion (SfM approach to low-altitude aerial imageries collected by Unmanned Aerial Vehicle (UAV. The SfM image-based approach was selected whilst searching for a rapid, inexpensive, and highly automated method, able to produce 3D information from unstructured aerial images. In particular, it was used to generate a dense point cloud and successively a high-resolution Digital Surface Models (DSM of a beach dune system in Marina di Ravenna (Italy. The quality of the elevation dataset produced by the UAV-SfM was initially evaluated by comparison with point cloud generated by a Terrestrial Laser Scanning (TLS surveys. Such a comparison served to highlight an average difference in the vertical values of 0.05 m (RMS = 0.19 m. However, although the points cloud comparison is the best approach to investigate the absolute or relative correspondence between UAV and TLS methods, the assessment of geomorphic features is usually based on multi-temporal surfaces analysis, where an interpolation process is required. DSMs were therefore generated from UAV and TLS points clouds and vertical absolute accuracies assessed by comparison with a Global Navigation Satellite System (GNSS survey. The vertical comparison of UAV and TLS DSMs with respect to GNSS measurements pointed out an average distance at cm-level (RMS = 0.011 m. The successive point by point direct comparison between UAV and TLS elevations show a very small average distance, 0.015 m, with RMS = 0.220 m. Larger values are encountered in areas where sudden changes in topography are present. The UAV-based approach was demonstrated to be a straightforward one and accuracy of the vertical dataset

  19. Neural network-based optimal adaptive output feedback control of a helicopter UAV.

    Science.gov (United States)

    Nodland, David; Zargarzadeh, Hassan; Jagannathan, Sarangapani

    2013-07-01

    Helicopter unmanned aerial vehicles (UAVs) are widely used for both military and civilian operations. Because the helicopter UAVs are underactuated nonlinear mechanical systems, high-performance controller design for them presents a challenge. This paper introduces an optimal controller design via an output feedback for trajectory tracking of a helicopter UAV, using a neural network (NN). The output-feedback control system utilizes the backstepping methodology, employing kinematic and dynamic controllers and an NN observer. The online approximator-based dynamic controller learns the infinite-horizon Hamilton-Jacobi-Bellman equation in continuous time and calculates the corresponding optimal control input by minimizing a cost function, forward-in-time, without using the value and policy iterations. Optimal tracking is accomplished by using a single NN utilized for the cost function approximation. The overall closed-loop system stability is demonstrated using Lyapunov analysis. Finally, simulation results are provided to demonstrate the effectiveness of the proposed control design for trajectory tracking.

  20. Fleet Protection Using a Small UAV Based IR Sensor

    National Research Council Canada - National Science Library

    Buss, James R; Ax, Jr, George R

    2005-01-01

    A study was performed to define candidate electro-optical and infrared (EO/IR) sensor configurations and assess their potential utility as small UAV-based sensors surveilling a perimeter around surface fleet assets...

  1. Data Acquisition (DAQ) system dedicated for remote sensing applications on Unmanned Aerial Vehicles (UAV)

    Science.gov (United States)

    Keleshis, C.; Ioannou, S.; Vrekoussis, M.; Levin, Z.; Lange, M. A.

    2014-08-01

    Continuous advances in unmanned aerial vehicles (UAV) and the increased complexity of their applications raise the demand for improved data acquisition systems (DAQ). These improvements may comprise low power consumption, low volume and weight, robustness, modularity and capability to interface with various sensors and peripherals while maintaining the high sampling rates and processing speeds. Such a system has been designed and developed and is currently integrated on the Autonomous Flying Platforms for Atmospheric and Earth Surface Observations (APAESO/NEA-YΠOΔOMH/NEKΠ/0308/09) however, it can be easily adapted to any UAV or any other mobile vehicle. The system consists of a single-board computer with a dual-core processor, rugged surface-mount memory and storage device, analog and digital input-output ports and many other peripherals that enhance its connectivity with various sensors, imagers and on-board devices. The system is powered by a high efficiency power supply board. Additional boards such as frame-grabbers, differential global positioning system (DGPS) satellite receivers, general packet radio service (3G-4G-GPRS) modems for communication redundancy have been interfaced to the core system and are used whenever there is a mission need. The onboard DAQ system can be preprogrammed for automatic data acquisition or it can be remotely operated during the flight from the ground control station (GCS) using a graphical user interface (GUI) which has been developed and will also be presented in this paper. The unique design of the GUI and the DAQ system enables the synchronized acquisition of a variety of scientific and UAV flight data in a single core location. The new DAQ system and the GUI have been successfully utilized in several scientific UAV missions. In conclusion, the novel DAQ system provides the UAV and the remote-sensing community with a new tool capable of reliably acquiring, processing, storing and transmitting data from any sensor integrated

  2. Using Unmanned Aerial Vehicles (UAV to Quantify Spatial Gap Patterns in Forests

    Directory of Open Access Journals (Sweden)

    Stephan Getzin

    2014-07-01

    Full Text Available Gap distributions in forests reflect the spatial impact of man-made tree harvesting or naturally-induced patterns of tree death being caused by windthrow, inter-tree competition, disease or senescence. Gap sizes can vary from large (>100 m2 to small (<10 m2, and they may have contrasting spatial patterns, such as being aggregated or regularly distributed. However, very small gaps cannot easily be recorded with conventional aerial or satellite images, which calls for new and cost-effective methodologies of forest monitoring. Here, we used an unmanned aerial vehicle (UAV and very high-resolution images to record the gaps in 10 temperate managed and unmanaged forests in two regions of Germany. All gaps were extracted for 1-ha study plots and subsequently analyzed with spatially-explicit statistics, such as the conventional pair correlation function (PCF, the polygon-based PCF and the mark correlation function. Gap-size frequency was dominated by small gaps of an area <5 m2, which were particularly frequent in unmanaged forests. We found that gap distances showed a variety of patterns. However, the polygon-based PCF was a better descriptor of patterns than the conventional PCF, because it showed randomness or aggregation for cases when the conventional PCF showed small-scale regularity; albeit, the latter was only a mathematical artifact. The mark correlation function revealed that gap areas were in half of the cases negatively correlated and in the other half independent. Negative size correlations may likely be the result of single-tree harvesting or of repeated gap formation, which both lead to nearby small gaps. Here, we emphasize the usefulness of UAV to record forest gaps of a very small size. These small gaps may originate from repeated gap-creating disturbances, and their spatial patterns should be monitored with spatially-explicit statistics at recurring intervals in order to further insights into forest dynamics.

  3. Unmanned aerial vehicles (UAVs for surveying marine fauna: a dugong case study.

    Directory of Open Access Journals (Sweden)

    Amanda Hodgson

    Full Text Available Aerial surveys of marine mammals are routinely conducted to assess and monitor species' habitat use and population status. In Australia, dugongs (Dugong dugon are regularly surveyed and long-term datasets have formed the basis for defining habitat of high conservation value and risk assessments of human impacts. Unmanned aerial vehicles (UAVs may facilitate more accurate, human-risk free, and cheaper aerial surveys. We undertook the first Australian UAV survey trial in Shark Bay, western Australia. We conducted seven flights of the ScanEagle UAV, mounted with a digital SLR camera payload. During each flight, ten transects covering a 1.3 km(2 area frequently used by dugongs, were flown at 500, 750 and 1000 ft. Image (photograph capture was controlled via the Ground Control Station and the capture rate was scheduled to achieve a prescribed 10% overlap between images along transect lines. Images were manually reviewed post hoc for animals and scored according to sun glitter, Beaufort Sea state and turbidity. We captured 6243 images, 627 containing dugongs. We also identified whales, dolphins, turtles and a range of other fauna. Of all possible dugong sightings, 95% (CI = 90%, 98% were subjectively classed as 'certain' (unmistakably dugongs. Neither our dugong sighting rate, nor our ability to identify dugongs with certainty, were affected by UAV altitude. Turbidity was the only environmental variable significantly affecting the dugong sighting rate. Our results suggest that UAV systems may not be limited by sea state conditions in the same manner as sightings from manned surveys. The overlap between images proved valuable for detecting animals that were masked by sun glitter in the corners of images, and identifying animals initially captured at awkward body angles. This initial trial of a basic camera system has successfully demonstrated that the ScanEagle UAV has great potential as a tool for marine mammal aerial surveys.

  4. Unmanned aerial vehicles (UAVs) for surveying marine fauna: a dugong case study.

    Science.gov (United States)

    Hodgson, Amanda; Kelly, Natalie; Peel, David

    2013-01-01

    Aerial surveys of marine mammals are routinely conducted to assess and monitor species' habitat use and population status. In Australia, dugongs (Dugong dugon) are regularly surveyed and long-term datasets have formed the basis for defining habitat of high conservation value and risk assessments of human impacts. Unmanned aerial vehicles (UAVs) may facilitate more accurate, human-risk free, and cheaper aerial surveys. We undertook the first Australian UAV survey trial in Shark Bay, western Australia. We conducted seven flights of the ScanEagle UAV, mounted with a digital SLR camera payload. During each flight, ten transects covering a 1.3 km(2) area frequently used by dugongs, were flown at 500, 750 and 1000 ft. Image (photograph) capture was controlled via the Ground Control Station and the capture rate was scheduled to achieve a prescribed 10% overlap between images along transect lines. Images were manually reviewed post hoc for animals and scored according to sun glitter, Beaufort Sea state and turbidity. We captured 6243 images, 627 containing dugongs. We also identified whales, dolphins, turtles and a range of other fauna. Of all possible dugong sightings, 95% (CI = 90%, 98%) were subjectively classed as 'certain' (unmistakably dugongs). Neither our dugong sighting rate, nor our ability to identify dugongs with certainty, were affected by UAV altitude. Turbidity was the only environmental variable significantly affecting the dugong sighting rate. Our results suggest that UAV systems may not be limited by sea state conditions in the same manner as sightings from manned surveys. The overlap between images proved valuable for detecting animals that were masked by sun glitter in the corners of images, and identifying animals initially captured at awkward body angles. This initial trial of a basic camera system has successfully demonstrated that the ScanEagle UAV has great potential as a tool for marine mammal aerial surveys.

  5. Configuration and specifications of an Unmanned Aerial Vehicle (UAV) for early site specific weed management.

    Science.gov (United States)

    Torres-Sánchez, Jorge; López-Granados, Francisca; De Castro, Ana Isabel; Peña-Barragán, José Manuel

    2013-01-01

    A new aerial platform has risen recently for image acquisition, the Unmanned Aerial Vehicle (UAV). This article describes the technical specifications and configuration of a UAV used to capture remote images for early season site- specific weed management (ESSWM). Image spatial and spectral properties required for weed seedling discrimination were also evaluated. Two different sensors, a still visible camera and a six-band multispectral camera, and three flight altitudes (30, 60 and 100 m) were tested over a naturally infested sunflower field. The main phases of the UAV workflow were the following: 1) mission planning, 2) UAV flight and image acquisition, and 3) image pre-processing. Three different aspects were needed to plan the route: flight area, camera specifications and UAV tasks. The pre-processing phase included the correct alignment of the six bands of the multispectral imagery and the orthorectification and mosaicking of the individual images captured in each flight. The image pixel size, area covered by each image and flight timing were very sensitive to flight altitude. At a lower altitude, the UAV captured images of finer spatial resolution, although the number of images needed to cover the whole field may be a limiting factor due to the energy required for a greater flight length and computational requirements for the further mosaicking process. Spectral differences between weeds, crop and bare soil were significant in the vegetation indices studied (Excess Green Index, Normalised Green-Red Difference Index and Normalised Difference Vegetation Index), mainly at a 30 m altitude. However, greater spectral separability was obtained between vegetation and bare soil with the index NDVI. These results suggest that an agreement among spectral and spatial resolutions is needed to optimise the flight mission according to every agronomical objective as affected by the size of the smaller object to be discriminated (weed plants or weed patches).

  6. Configuration and specifications of an Unmanned Aerial Vehicle (UAV for early site specific weed management.

    Directory of Open Access Journals (Sweden)

    Jorge Torres-Sánchez

    Full Text Available A new aerial platform has risen recently for image acquisition, the Unmanned Aerial Vehicle (UAV. This article describes the technical specifications and configuration of a UAV used to capture remote images for early season site- specific weed management (ESSWM. Image spatial and spectral properties required for weed seedling discrimination were also evaluated. Two different sensors, a still visible camera and a six-band multispectral camera, and three flight altitudes (30, 60 and 100 m were tested over a naturally infested sunflower field. The main phases of the UAV workflow were the following: 1 mission planning, 2 UAV flight and image acquisition, and 3 image pre-processing. Three different aspects were needed to plan the route: flight area, camera specifications and UAV tasks. The pre-processing phase included the correct alignment of the six bands of the multispectral imagery and the orthorectification and mosaicking of the individual images captured in each flight. The image pixel size, area covered by each image and flight timing were very sensitive to flight altitude. At a lower altitude, the UAV captured images of finer spatial resolution, although the number of images needed to cover the whole field may be a limiting factor due to the energy required for a greater flight length and computational requirements for the further mosaicking process. Spectral differences between weeds, crop and bare soil were significant in the vegetation indices studied (Excess Green Index, Normalised Green-Red Difference Index and Normalised Difference Vegetation Index, mainly at a 30 m altitude. However, greater spectral separability was obtained between vegetation and bare soil with the index NDVI. These results suggest that an agreement among spectral and spatial resolutions is needed to optimise the flight mission according to every agronomical objective as affected by the size of the smaller object to be discriminated (weed plants or weed patches.

  7. Comparison of Uncalibrated Rgbvi with Spectrometer-Based Ndvi Derived from Uav Sensing Systems on Field Scale

    Science.gov (United States)

    Bareth, G.; Bolten, A.; Gnyp, M. L.; Reusch, S.; Jasper, J.

    2016-06-01

    The development of UAV-based sensing systems for agronomic applications serves the improvement of crop management. The latter is in the focus of precision agriculture which intends to optimize yield, fertilizer input, and crop protection. Besides, in some cropping systems vehicle-based sensing devices are less suitable because fields cannot be entered from certain growing stages onwards. This is true for rice, maize, sorghum, and many more crops. Consequently, UAV-based sensing approaches fill a niche of very high resolution data acquisition on the field scale in space and time. While mounting RGB digital compact cameras to low-weight UAVs (modified version of the Yara N-Sensor. The latter is a well-established tractor-based hyperspectral sensor for crop management and is available on the market since a decade. It was modified for this study to fit the requirements of UAV-based data acquisition. Consequently, we focus on three objectives in this contribution: (1) to evaluate the potential of the uncalibrated RGBVI for monitoring nitrogen status in winter wheat, (2) investigate the UAV-based performance of the modified Yara N-Sensor, and (3) compare the results of the two different UAV-based sensing approaches for winter wheat.

  8. New generation of human machine interfaces for controlling UAV through depth-based gesture recognition

    Science.gov (United States)

    Mantecón, Tomás.; del Blanco, Carlos Roberto; Jaureguizar, Fernando; García, Narciso

    2014-06-01

    New forms of natural interactions between human operators and UAVs (Unmanned Aerial Vehicle) are demanded by the military industry to achieve a better balance of the UAV control and the burden of the human operator. In this work, a human machine interface (HMI) based on a novel gesture recognition system using depth imagery is proposed for the control of UAVs. Hand gesture recognition based on depth imagery is a promising approach for HMIs because it is more intuitive, natural, and non-intrusive than other alternatives using complex controllers. The proposed system is based on a Support Vector Machine (SVM) classifier that uses spatio-temporal depth descriptors as input features. The designed descriptor is based on a variation of the Local Binary Pattern (LBP) technique to efficiently work with depth video sequences. Other major consideration is the especial hand sign language used for the UAV control. A tradeoff between the use of natural hand signs and the minimization of the inter-sign interference has been established. Promising results have been achieved in a depth based database of hand gestures especially developed for the validation of the proposed system.

  9. An Efficient Energy Constraint Based UAV Path Planning for Search and Coverage

    OpenAIRE

    Gramajo, German; Shankar, Praveen

    2017-01-01

    A path planning strategy for a search and coverage mission for a small UAV that maximizes the area covered based on stored energy and maneuverability constraints is presented. The proposed formulation has a high level of autonomy, without requiring an exact choice of optimization parameters, and is appropriate for real-time implementation. The computed trajectory maximizes spatial coverage while closely satisfying terminal constraints on the position of the vehicle and minimizing the time of ...

  10. The System Design of a Global Communications System for Military and Commercial use Utilizing High Altitude Unmanned Aerial Vehicles (UAVs) and Terrestrial Local Multipoint Distribution Service (LMDS) Sites

    OpenAIRE

    Banks, Bradley

    2000-01-01

    This thesis proposes the design of the UAV-LMDS communication system for military and commercial use. The UAV-LMDS system is a digital, wireless communication system that provides service using unmanned aerial vehicles (UAVs) flying at 60,000 ft. acting as communication hubs. This thesis provides background information on UAV-LMDS system elements, a financial analysis, theory, link budgets, system component design and implementation issues. To begin the design, we develop link budgets t...

  11. Cooperative Monocular-Based SLAM for Multi-UAV Systems in GPS-Denied Environments.

    Science.gov (United States)

    Trujillo, Juan-Carlos; Munguia, Rodrigo; Guerra, Edmundo; Grau, Antoni

    2018-04-26

    This work presents a cooperative monocular-based SLAM approach for multi-UAV systems that can operate in GPS-denied environments. The main contribution of the work is to show that, using visual information obtained from monocular cameras mounted onboard aerial vehicles flying in formation, the observability properties of the whole system are improved. This fact is especially notorious when compared with other related visual SLAM configurations. In order to improve the observability properties, some measurements of the relative distance between the UAVs are included in the system. These relative distances are also obtained from visual information. The proposed approach is theoretically validated by means of a nonlinear observability analysis. Furthermore, an extensive set of computer simulations is presented in order to validate the proposed approach. The numerical simulation results show that the proposed system is able to provide a good position and orientation estimation of the aerial vehicles flying in formation.

  12. Perception-based Co-evolutionary Reinforcement Learning for UAV Sensor Allocation

    National Research Council Canada - National Science Library

    Berenji, Hamid

    2003-01-01

    .... A Perception-based reasoning approach based on co-evolutionary reinforcement learning was developed for jointly addressing sensor allocation on each individual UAV and allocation of a team of UAVs...

  13. Small Whiskbroom Imager for atmospheric compositioN monitorinG (SWING) from an Unmanned Aerial Vehicle (UAV): Results from the 2014 AROMAT campaign

    Science.gov (United States)

    Merlaud, Alexis; Tack, Frederik; Constantin, Daniel; Fayt, Caroline; Maes, Jeroen; Mingireanu, Florin; Mocanu, Ionut; Georgescu, Lucian; Van Roozendael, Michel

    2015-04-01

    The Small Whiskbroom Imager for atmospheric compositioN monitorinG (SWING) is an instrument dedicated to atmospheric trace gas retrieval from an Unmanned Aerial Vehicle (UAV). The payload is based on a compact visible spectrometer and a scanning mirror to collect scattered sunlight. Its weight, size, and power consumption are respectively 920 g, 27x12x12 cm3, and 6 W. The custom-built 2.5 m flying wing UAV is electrically powered, has a typical airspeed of 100 km/h, and can operate at a maximum altitude of 3 km. Both the payload and the UAV were developed in the framework of a collaboration between the Belgian Institute for Space Aeronomy (BIRA-IASB) and the Dunarea de Jos University of Galati, Romania. We present here SWING-UAV test flights dedicated to NO2 measurements and performed in Romania on 10 and 11 September 2014, during the Airborne ROmanian Measurements of Aerosols and Trace gases (AROMAT) campaign. The UAV performed 5 flights in the vicinity of the large thermal power station of Turceni (44.67° N, 23.4° E). The UAV was operated in visual range during the campaign, up to 900 m AGL , downwind of the plant and crossing its exhaust plume. The spectra recorded on flight are analyzed with the Differential Optical Absorption Spectroscopy (DOAS) method. The retrieved NO2 Differential Slant Column Densities (DSCDs) are up to 1.5e17 molec/cm2 and reveal the horizontal gradients around the plant. The DSCDs are converted to vertical columns and compared with coincident car-based DOAS measurements. We also present the near-future perspective of the SWING-UAV observation system, which includes flights in 2015 above the Black Sea to quantify ship emissions, the addition of SO2 as a target species, and autopilot flights at higher altitudes to cover a typical satellite pixel extent (10x10 km2).

  14. UAV based hydromorphological mapping of a river reach to improve hydrodynamic numerical models

    Science.gov (United States)

    Lükő, Gabriella; Baranya, Sándor; Rüther, Nils

    2017-04-01

    Unmanned Aerial Vehicles (UAVs) are increasingly used in the field of engineering surveys. In river engineering, or in general, water resources engineering, UAV based measurements have a huge potential. For instance, indirect measurements of the flow discharge using e.g. large-scale particle image velocimetry (LSPIV), particle tracking velocimetry (PTV), space-time image velocimetry (STIV) or radars became a real alternative for direct flow measurements. Besides flow detection, topographic surveys are also essential for river flow studies as the channel and floodplain geometry is the primary steering feature of the flow. UAVs can play an important role in this field, too. The widely used laser based topographic survey method (LIDAR) can be deployed on UAVs, moreover, the application of the Structure from Motion (SfM) method, which is based on images taken by UAVs, might be an even more cost-efficient alternative to reveal the geometry of distinct objects in the river or on the floodplain. The goal of this study is to demonstrate the utilization of photogrammetry and videogrammetry from airborne footage to provide geometry and flow data for a hydrodynamic numerical simulation of a 2 km long river reach in Albania. First, the geometry of the river is revealed from photogrammetry using the SfM method. Second, a more detailed view of the channel bed at low water level is taken. Using the fine resolution images, a Matlab based code, BASEGrain, developed by the ETH in Zürich, will be applied to determine the grain size characteristics of the river bed. This information will be essential to define the hydraulic roughness in the numerical model. Third, flow mapping is performed using UAV measurements and LSPIV method to quantitatively asses the flow field at the free surface and to estimate the discharge in the river. All data collection and analysis will be carried out using a simple, low-cost UAV, moreover, for all the data processing, open source, freely available

  15. Two-UAV Intersection Localization System Based on the Airborne Optoelectronic Platform.

    Science.gov (United States)

    Bai, Guanbing; Liu, Jinghong; Song, Yueming; Zuo, Yujia

    2017-01-06

    To address the limitation of the existing UAV (unmanned aerial vehicles) photoelectric localization method used for moving objects, this paper proposes an improved two-UAV intersection localization system based on airborne optoelectronic platforms by using the crossed-angle localization method of photoelectric theodolites for reference. This paper introduces the makeup and operating principle of intersection localization system, creates auxiliary coordinate systems, transforms the LOS (line of sight, from the UAV to the target) vectors into homogeneous coordinates, and establishes a two-UAV intersection localization model. In this paper, the influence of the positional relationship between UAVs and the target on localization accuracy has been studied in detail to obtain an ideal measuring position and the optimal localization position where the optimal intersection angle is 72.6318°. The result shows that, given the optimal position, the localization root mean square error (RMS) will be 25.0235 m when the target is 5 km away from UAV baselines. Finally, the influence of modified adaptive Kalman filtering on localization results is analyzed, and an appropriate filtering model is established to reduce the localization RMS error to 15.7983 m. Finally, An outfield experiment was carried out and obtained the optimal results: σ B = 1.63 × 10 - 4 ( ° ) , σ L = 1.35 × 10 - 4 ( ° ) , σ H = 15.8 ( m ) , σ s u m = 27.6 ( m ) , where σ B represents the longitude error, σ L represents the latitude error, σ H represents the altitude error, and σ s u m represents the error radius.

  16. Development of Open source-based automatic shooting and processing UAV imagery for Orthoimage Using Smart Camera UAV

    Science.gov (United States)

    Park, J. W.; Jeong, H. H.; Kim, J. S.; Choi, C. U.

    2016-06-01

    Recently, aerial photography with unmanned aerial vehicle (UAV) system uses UAV and remote controls through connections of ground control system using bandwidth of about 430 MHz radio Frequency (RF) modem. However, as mentioned earlier, existing method of using RF modem has limitations in long distance communication. The Smart Camera equipments's LTE (long-term evolution), Bluetooth, and Wi-Fi to implement UAV that uses developed UAV communication module system carried out the close aerial photogrammetry with the automatic shooting. Automatic shooting system is an image capturing device for the drones in the area's that needs image capturing and software for loading a smart camera and managing it. This system is composed of automatic shooting using the sensor of smart camera and shooting catalog management which manages filmed images and information. Processing UAV imagery module used Open Drone Map. This study examined the feasibility of using the Smart Camera as the payload for a photogrammetric UAV system. The open soure tools used for generating Android, OpenCV (Open Computer Vision), RTKLIB, Open Drone Map.

  17. Development of Open source-based automatic shooting and processing UAV imagery for Orthoimage Using Smart Camera UAV

    Directory of Open Access Journals (Sweden)

    J. W. Park

    2016-06-01

    Full Text Available Recently, aerial photography with unmanned aerial vehicle (UAV system uses UAV and remote controls through connections of ground control system using bandwidth of about 430 MHz radio Frequency (RF modem. However, as mentioned earlier, existing method of using RF modem has limitations in long distance communication. The Smart Camera equipments’s LTE (long-term evolution, Bluetooth, and Wi-Fi to implement UAV that uses developed UAV communication module system carried out the close aerial photogrammetry with the automatic shooting. Automatic shooting system is an image capturing device for the drones in the area’s that needs image capturing and software for loading a smart camera and managing it. This system is composed of automatic shooting using the sensor of smart camera and shooting catalog management which manages filmed images and information. Processing UAV imagery module used Open Drone Map. This study examined the feasibility of using the Smart Camera as the payload for a photogrammetric UAV system. The open soure tools used for generating Android, OpenCV (Open Computer Vision, RTKLIB, Open Drone Map.

  18. Unmanned Aerial Vehicles (UAVs and Artificial Intelligence Revolutionizing Wildlife Monitoring and Conservation

    Directory of Open Access Journals (Sweden)

    Luis F. Gonzalez

    2016-01-01

    Full Text Available Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as camera traps and surveys performed on foot, are known to be resource intensive, potentially inaccurate and imprecise, and difficult to validate. Recent developments in unmanned aerial vehicles (UAV, artificial intelligence and miniaturized thermal imaging systems represent a new opportunity for wildlife experts to inexpensively survey relatively large areas. The system presented in this paper includes thermal image acquisition as well as a video processing pipeline to perform object detection, classification and tracking of wildlife in forest or open areas. The system is tested on thermal video data from ground based and test flight footage, and is found to be able to detect all the target wildlife located in the surveyed area. The system is flexible in that the user can readily define the types of objects to classify and the object characteristics that should be considered during classification.

  19. Unmanned Aerial Vehicles (UAVs) and Artificial Intelligence Revolutionizing Wildlife Monitoring and Conservation.

    Science.gov (United States)

    Gonzalez, Luis F; Montes, Glen A; Puig, Eduard; Johnson, Sandra; Mengersen, Kerrie; Gaston, Kevin J

    2016-01-14

    Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as camera traps and surveys performed on foot, are known to be resource intensive, potentially inaccurate and imprecise, and difficult to validate. Recent developments in unmanned aerial vehicles (UAV), artificial intelligence and miniaturized thermal imaging systems represent a new opportunity for wildlife experts to inexpensively survey relatively large areas. The system presented in this paper includes thermal image acquisition as well as a video processing pipeline to perform object detection, classification and tracking of wildlife in forest or open areas. The system is tested on thermal video data from ground based and test flight footage, and is found to be able to detect all the target wildlife located in the surveyed area. The system is flexible in that the user can readily define the types of objects to classify and the object characteristics that should be considered during classification.

  20. Distortion correction algorithm for UAV remote sensing image based on CUDA

    International Nuclear Information System (INIS)

    Wenhao, Zhang; Yingcheng, Li; Delong, Li; Changsheng, Teng; Jin, Liu

    2014-01-01

    In China, natural disasters are characterized by wide distribution, severe destruction and high impact range, and they cause significant property damage and casualties every year. Following a disaster, timely and accurate acquisition of geospatial information can provide an important basis for disaster assessment, emergency relief, and reconstruction. In recent years, Unmanned Aerial Vehicle (UAV) remote sensing systems have played an important role in major natural disasters, with UAVs becoming an important technique of obtaining disaster information. UAV is equipped with a non-metric digital camera with lens distortion, resulting in larger geometric deformation for acquired images, and affecting the accuracy of subsequent processing. The slow speed of the traditional CPU-based distortion correction algorithm cannot meet the requirements of disaster emergencies. Therefore, we propose a Compute Unified Device Architecture (CUDA)-based image distortion correction algorithm for UAV remote sensing, which takes advantage of the powerful parallel processing capability of the GPU, greatly improving the efficiency of distortion correction. Our experiments show that, compared with traditional CPU algorithms and regardless of image loading and saving times, the maximum acceleration ratio using our proposed algorithm reaches 58 times that using the traditional algorithm. Thus, data processing time can be reduced by one to two hours, thereby considerably improving disaster emergency response capability

  1. Target Tracking in 3-D Using Estimation Based Nonlinear Control Laws for UAVs

    Directory of Open Access Journals (Sweden)

    Mousumi Ahmed

    2016-02-01

    Full Text Available This paper presents an estimation based backstepping like control law design for an Unmanned Aerial Vehicle (UAV to track a moving target in 3-D space. A ground-based sensor or an onboard seeker antenna provides range, azimuth angle, and elevation angle measurements to a chaser UAV that implements an extended Kalman filter (EKF to estimate the full state of the target. A nonlinear controller then utilizes this estimated target state and the chaser’s state to provide speed, flight path, and course/heading angle commands to the chaser UAV. Tracking performance with respect to measurement uncertainty is evaluated for three cases: (1 stationary white noise; (2 stationary colored noise and (3 non-stationary (range correlated white noise. Furthermore, in an effort to improve tracking performance, the measurement model is made more realistic by taking into consideration range-dependent uncertainties in the measurements, i.e., as the chaser closes in on the target, measurement uncertainties are reduced in the EKF, thus providing the UAV with more accurate control commands. Simulation results for these cases are shown to illustrate target state estimation and trajectory tracking performance.

  2. UAV Delivery Monitoring System

    Directory of Open Access Journals (Sweden)

    San Khin Thida

    2018-01-01

    Full Text Available UAV-based delivery systems are increasingly being used in the logistics field, particularly to achieve faster last-mile delivery. This study develops a UAV delivery system that manages delivery order assignments, autonomous flight operation, real time control for UAV flights, and delivery status tracking. To manage the delivery item assignments, we apply the concurrent scheduler approach with a genetic algorithm. The present paper describes real time flight data based on a micro air vehicle communication protocol (MAVLink. It also presents the detailed hardware components used for the field tests. Finally, we provide UAV component analysis to choose the suitable components for delivery in terms of battery capacity, flight time, payload weight and motor thrust ratio.

  3. Research on detection method of UAV obstruction based on binocular vision

    Science.gov (United States)

    Zhu, Xiongwei; Lei, Xusheng; Sui, Zhehao

    2018-04-01

    For the autonomous obstacle positioning and ranging in the process of UAV (unmanned aerial vehicle) flight, a system based on binocular vision is constructed. A three-stage image preprocessing method is proposed to solve the problem of the noise and brightness difference in the actual captured image. The distance of the nearest obstacle is calculated by using the disparity map that generated by binocular vision. Then the contour of the obstacle is extracted by post-processing of the disparity map, and a color-based adaptive parameter adjustment algorithm is designed to extract contours of obstacle automatically. Finally, the safety distance measurement and obstacle positioning during the UAV flight process are achieved. Based on a series of tests, the error of distance measurement can keep within 2.24% of the measuring range from 5 m to 20 m.

  4. Colour-based Object Detection and Tracking for Autonomous Quadrotor UAV

    International Nuclear Information System (INIS)

    Kadouf, Hani Hunud A; Mustafah, Yasir Mohd

    2013-01-01

    With robotics becoming a fundamental aspect of modern society, further research and consequent application is ever increasing. Aerial robotics, in particular, covers applications such as surveillance in hostile military zones or search and rescue operations in disaster stricken areas, where ground navigation is impossible. The increased visual capacity of UAV's (Unmanned Air Vehicles) is also applicable in the support of ground vehicles to provide supplies for emergency assistance, for scouting purposes or to extend communication beyond insurmountable land or water barriers. The Quadrotor, which is a small UAV has its lift generated by four rotors and can be controlled by altering the speeds of its motors relative to each other. The four rotors allow for a higher payload than single or dual rotor UAVs, which makes it safer and more suitable to carry camera and transmitter equipment. An onboard camera is used to capture and transmit images of the Quadrotor's First Person View (FPV) while in flight, in real time, wirelessly to a base station. The aim of this research is to develop an autonomous quadrotor platform capable of transmitting real time video signals to a base station for processing. The result from the image analysis will be used as a feedback in the quadrotor positioning control. To validate the system, the algorithm should have the capacity to make the quadrotor identify, track or hover above stationary or moving objects

  5. UAV-Based Hyperspectral Remote Sensing for Precision Agriculture: Challenges and Opportunities

    Science.gov (United States)

    Angel, Y.; Parkes, S. D.; Turner, D.; Houborg, R.; Lucieer, A.; McCabe, M.

    2017-12-01

    Modern agricultural production relies on monitoring crop status by observing and measuring variables such as soil condition, plant health, fertilizer and pesticide effect, irrigation and crop yield. Managing all of these factors is a considerable challenge for crop producers. As such, providing integrated technological solutions that enable improved diagnostics of field condition to maximize profits, while minimizing environmental impacts, would be of much interest. Such challenges can be addressed by implementing remote sensing systems such as hyperspectral imaging to produce precise biophysical indicator maps across the various cycles of crop development. Recent progress in unmanned aerial vehicles (UAVs) have advanced traditional satellite-based capabilities, providing a capacity for high-spatial, spectral and temporal response. However, while some hyperspectral sensors have been developed for use onboard UAVs, significant investment is required to develop a system and data processing workflow that retrieves accurately georeferenced mosaics. Here we explore the use of a pushbroom hyperspectral camera that is integrated on-board a multi-rotor UAV system to measure the surface reflectance in 272 distinct spectral bands across a wavelengths range spanning 400-1000 nm, and outline the requirement for sensor calibration, integration onto a stable UAV platform enabling accurate positional data, flight planning, and development of data post-processing workflows for georeferenced mosaics. The provision of high-quality and geo-corrected imagery facilitates the development of metrics of vegetation health that can be used to identify potential problems such as production inefficiencies, diseases and nutrient deficiencies and other data-streams to enable improved crop management. Immense opportunities remain to be exploited in the implementation of UAV-based hyperspectral sensing (and its combination with other imaging systems) to provide a transferable and scalable

  6. Embedded, real-time UAV control for improved, image-based 3D scene reconstruction

    Science.gov (United States)

    Jean Liénard; Andre Vogs; Demetrios Gatziolis; Nikolay Strigul

    2016-01-01

    Unmanned Aerial Vehicles (UAVs) are already broadly employed for 3D modeling of large objects such as trees and monuments via photogrammetry. The usual workflow includes two distinct steps: image acquisition with UAV and computationally demanding postflight image processing. Insufficient feature overlaps across images is a common shortcoming in post-flight image...

  7. COMPARISON OF UNCALIBRATED RGBVI WITH SPECTROMETER-BASED NDVI DERIVED FROM UAV SENSING SYSTEMS ON FIELD SCALE

    Directory of Open Access Journals (Sweden)

    G. Bareth

    2016-06-01

    Full Text Available The development of UAV-based sensing systems for agronomic applications serves the improvement of crop management. The latter is in the focus of precision agriculture which intends to optimize yield, fertilizer input, and crop protection. Besides, in some cropping systems vehicle-based sensing devices are less suitable because fields cannot be entered from certain growing stages onwards. This is true for rice, maize, sorghum, and many more crops. Consequently, UAV-based sensing approaches fill a niche of very high resolution data acquisition on the field scale in space and time. While mounting RGB digital compact cameras to low-weight UAVs (< 5 kg is well established, the miniaturization of sensors in the last years also enables hyperspectral data acquisition from those platforms. From both, RGB and hyperspectral data, vegetation indices (VIs are computed to estimate crop growth parameters. In this contribution, we compare two different sensing approaches from a low-weight UAV platform (< 5 kg for monitoring a nitrogen field experiment of winter wheat and a corresponding farmers’ field in Western Germany. (i A standard digital compact camera was flown to acquire RGB images which are used to compute the RGBVI and (ii NDVI is computed from a newly modified version of the Yara N-Sensor. The latter is a well-established tractor-based hyperspectral sensor for crop management and is available on the market since a decade. It was modified for this study to fit the requirements of UAV-based data acquisition. Consequently, we focus on three objectives in this contribution: (1 to evaluate the potential of the uncalibrated RGBVI for monitoring nitrogen status in winter wheat, (2 investigate the UAV-based performance of the modified Yara N-Sensor, and (3 compare the results of the two different UAV-based sensing approaches for winter wheat.

  8. The Practical Application of Uav-Based Photogrammetry Under Economic Aspects

    Science.gov (United States)

    Sauerbier, M.; Siegrist, E.; Eisenbeiss, H.; Demir, N.

    2011-09-01

    Nowadays, small size UAVs (Unmanned Aerial Vehicles) have reached a level of practical reliability and functionality that enables this technology to enter the geomatics market as an additional platform for spatial data acquisition. Though one could imagine a wide variety of interesting sensors to be mounted on such a device, here we will focus on photogrammetric applications using digital cameras. In praxis, UAV-based photogrammetry will only be accepted if it a) provides the required accuracy and an additional value and b) if it is competitive in terms of economic application compared to other measurement technologies. While a) was already proven by the scientific community and results were published comprehensively during the last decade, b) still has to be verified under real conditions. For this purpose, a test data set representing a realistic scenario provided by ETH Zurich was used to investigate cost effectiveness and to identify weak points in the processing chain that require further development. Our investigations are limited to UAVs carrying digital consumer cameras, for larger UAVs equipped with medium format cameras the situation has to be considered as significantly different. Image data was acquired during flights using a microdrones MD4-1000 quadrocopter equipped with an Olympus PE-1 digital compact camera. From these images, a subset of 5 images was selected for processing in order to register the effort of time required for the whole production chain of photogrammetric products. We see the potential of mini UAV-based photogrammetry mainly in smaller areas, up to a size of ca. 100 hectares. Larger areas can be efficiently covered by small airplanes with few images, reducing processing effort drastically. In case of smaller areas of a few hectares only, it depends more on the products required. UAVs can be an enhancement or alternative to GNSS measurements, terrestrial laser scanning and ground based photogrammetry. We selected the above mentioned

  9. Automatic detection and counting of cattle in UAV imagery based on machine vision technology (Conference Presentation)

    Science.gov (United States)

    Rahnemoonfar, Maryam; Foster, Jamie; Starek, Michael J.

    2017-05-01

    Beef production is the main agricultural industry in Texas, and livestock are managed in pasture and rangeland which are usually huge in size, and are not easily accessible by vehicles. The current research method for livestock location identification and counting is visual observation which is very time consuming and costly. For animals on large tracts of land, manned aircraft may be necessary to count animals which is noisy and disturbs the animals, and may introduce a source of error in counts. Such manual approaches are expensive, slow and labor intensive. In this paper we study the combination of small unmanned aerial vehicle (sUAV) and machine vision technology as a valuable solution to manual animal surveying. A fixed-wing UAV fitted with GPS and digital RGB camera for photogrammetry was flown at the Welder Wildlife Foundation in Sinton, TX. Over 600 acres were flown with four UAS flights and individual photographs used to develop orthomosaic imagery. To detect animals in UAV imagery, a fully automatic technique was developed based on spatial and spectral characteristics of objects. This automatic technique can even detect small animals that are partially occluded by bushes. Experimental results in comparison to ground-truth show the effectiveness of our algorithm.

  10. Coastal Ecosystem Assessment, Development and Creation of a Policy Tool using Unmanned Aerial Vehicles (UAVs) for: A Case Study of Western Puerto Rico Coastal Region

    Science.gov (United States)

    Munoz Barreto, J.; Pillich, J.; Aponte Bermúdez, L. D.; Torres Pagan, G.

    2017-12-01

    This project utilizes low-cost Unmanned Aerial Vehicles (UAVs) based systems for different applications, such as low-altitude (high resolution) aerial photogrammetry for aerial analysis of vegetation, reconstruction of beach topography and mapping coastal erosion to understand, and estimated ecosystem values. As part of this work, five testbeds coastal sites, designated as the Caribbean Littoral Aerial Surveillance System (CLASS), were established. The sites are distributed along western Puerto Rico coastline where population and industry (tourism) are very much clustered and dense along the coast. Over the past year, rapid post-storm deployment of UAV surveying has been successfully integrated into the CLASS sites, specifically at Rincon (Puerto Rico), where coastal erosion has raised the public and government concern over the past decades. A case study is presented here where we collected aerial photos before and after the swells caused by Hurricane Mathew (October 2016). We merged the point cloud obtained from the UAV photogrammetric assessment with topo-bathymetric data, to get a complete beach topography. Using the rectified and georeferenced UAV orthophotos, we identified the maximum wave runup for the pre-swell and post-swell events. Also, we used numerical modeling (X-Beach) to simulate the rate-of-change dynamics of the coastal zones and compare the model results to observed values (including multiple historic shoreline positions). In summary, our project has accomplished the first milestone which is the Development and Implementation of an Effective Shoreline Monitoring Program using UAVs. The activities of the monitoring program have enabled the collection of crucial data for coastal mapping along Puerto Rico's shorelines with emphasis on coastal erosion hot spots zones and ecosystem values. Our results highlight the potential of the synergy between UAVs, photogrammetry, and Geographic Information Systems to provide faster and low-cost reliable

  11. Direct Georeferencing of Uav Data Based on Simple Building Structures

    Science.gov (United States)

    Tampubolon, W.; Reinhardt, W.

    2016-06-01

    Unmanned Aerial Vehicle (UAV) data acquisition is more flexible compared with the more complex traditional airborne data acquisition. This advantage puts UAV platforms in a position as an alternative acquisition method in many applications including Large Scale Topographical Mapping (LSTM). LSTM, i.e. larger or equal than 1:10.000 map scale, is one of a number of prominent priority tasks to be solved in an accelerated way especially in third world developing countries such as Indonesia. As one component of fundamental geospatial data sets, large scale topographical maps are mandatory in order to enable detailed spatial planning. However, the accuracy of the products derived from the UAV data are normally not sufficient for LSTM as it needs robust georeferencing, which requires additional costly efforts such as the incorporation of sophisticated GPS Inertial Navigation System (INS) or Inertial Measurement Unit (IMU) on the platform and/or Ground Control Point (GCP) data on the ground. To reduce the costs and the weight on the UAV alternative solutions have to be found. This paper outlines a direct georeferencing method of UAV data by providing image orientation parameters derived from simple building structures and presents results of an investigation on the achievable results in a LSTM application. In this case, the image orientation determination has been performed through sequential images without any input from INS/IMU equipment. The simple building structures play a significant role in such a way that geometrical characteristics have been considered. Some instances are the orthogonality of the building's wall/rooftop and the local knowledge of the building orientation in the field. In addition, we want to include the Structure from Motion (SfM) approach in order to reduce the number of required GCPs especially for the absolute orientation purpose. The SfM technique applied to the UAV data and simple building structures additionally presents an effective tool

  12. DIRECT GEOREFERENCING OF UAV DATA BASED ON SIMPLE BUILDING STRUCTURES

    Directory of Open Access Journals (Sweden)

    W. Tampubolon

    2016-06-01

    Full Text Available Unmanned Aerial Vehicle (UAV data acquisition is more flexible compared with the more complex traditional airborne data acquisition. This advantage puts UAV platforms in a position as an alternative acquisition method in many applications including Large Scale Topographical Mapping (LSTM. LSTM, i.e. larger or equal than 1:10.000 map scale, is one of a number of prominent priority tasks to be solved in an accelerated way especially in third world developing countries such as Indonesia. As one component of fundamental geospatial data sets, large scale topographical maps are mandatory in order to enable detailed spatial planning. However, the accuracy of the products derived from the UAV data are normally not sufficient for LSTM as it needs robust georeferencing, which requires additional costly efforts such as the incorporation of sophisticated GPS Inertial Navigation System (INS or Inertial Measurement Unit (IMU on the platform and/or Ground Control Point (GCP data on the ground. To reduce the costs and the weight on the UAV alternative solutions have to be found. This paper outlines a direct georeferencing method of UAV data by providing image orientation parameters derived from simple building structures and presents results of an investigation on the achievable results in a LSTM application. In this case, the image orientation determination has been performed through sequential images without any input from INS/IMU equipment. The simple building structures play a significant role in such a way that geometrical characteristics have been considered. Some instances are the orthogonality of the building’s wall/rooftop and the local knowledge of the building orientation in the field. In addition, we want to include the Structure from Motion (SfM approach in order to reduce the number of required GCPs especially for the absolute orientation purpose. The SfM technique applied to the UAV data and simple building structures additionally presents an

  13. Information Fusion-Based Optimal Attitude Control for an Alterable Thrust Direction Unmanned Aerial Vehicle

    Directory of Open Access Journals (Sweden)

    Ziyang Zhen

    2013-01-01

    Full Text Available Attitude control is the inner-loop and the most important part of the automatic flight control system of an unmanned aerial vehicle (UAV. The information fusion-based optimal control method is applied in a UAV flight control system in this work. Firstly, a nonlinear model of alterable thrust direction UAV (ATD-UAV is established and linearized for controller design. The longitudinal controller and lateral controller are respectively designed based on information fusion-based optimal control, and then the information fusion flight control system is built up. Finally, the simulation of a nonlinear model described as ATD-UAV is carried out, the results of which show the superiority of the information fusion-based control strategy when compared to the single-loop design method. We also show that the ATD technique improves the anti-disturbance capacity of the UAV.

  14. High-Throughput 3-D Monitoring of Agricultural-Tree Plantations with Unmanned Aerial Vehicle (UAV) Technology

    Science.gov (United States)

    Torres-Sánchez, Jorge; López-Granados, Francisca; Serrano, Nicolás; Arquero, Octavio; Peña, José M.

    2015-01-01

    The geometric features of agricultural trees such as canopy area, tree height and crown volume provide useful information about plantation status and crop production. However, these variables are mostly estimated after a time-consuming and hard field work and applying equations that treat the trees as geometric solids, which produce inconsistent results. As an alternative, this work presents an innovative procedure for computing the 3-dimensional geometric features of individual trees and tree-rows by applying two consecutive phases: 1) generation of Digital Surface Models with Unmanned Aerial Vehicle (UAV) technology and 2) use of object-based image analysis techniques. Our UAV-based procedure produced successful results both in single-tree and in tree-row plantations, reporting up to 97% accuracy on area quantification and minimal deviations compared to in-field estimations of tree heights and crown volumes. The maps generated could be used to understand the linkages between tree grown and field-related factors or to optimize crop management operations in the context of precision agriculture with relevant agro-environmental implications. PMID:26107174

  15. High-Throughput 3-D Monitoring of Agricultural-Tree Plantations with Unmanned Aerial Vehicle (UAV) Technology.

    Science.gov (United States)

    Torres-Sánchez, Jorge; López-Granados, Francisca; Serrano, Nicolás; Arquero, Octavio; Peña, José M

    2015-01-01

    The geometric features of agricultural trees such as canopy area, tree height and crown volume provide useful information about plantation status and crop production. However, these variables are mostly estimated after a time-consuming and hard field work and applying equations that treat the trees as geometric solids, which produce inconsistent results. As an alternative, this work presents an innovative procedure for computing the 3-dimensional geometric features of individual trees and tree-rows by applying two consecutive phases: 1) generation of Digital Surface Models with Unmanned Aerial Vehicle (UAV) technology and 2) use of object-based image analysis techniques. Our UAV-based procedure produced successful results both in single-tree and in tree-row plantations, reporting up to 97% accuracy on area quantification and minimal deviations compared to in-field estimations of tree heights and crown volumes. The maps generated could be used to understand the linkages between tree grown and field-related factors or to optimize crop management operations in the context of precision agriculture with relevant agro-environmental implications.

  16. High-Throughput 3-D Monitoring of Agricultural-Tree Plantations with Unmanned Aerial Vehicle (UAV Technology.

    Directory of Open Access Journals (Sweden)

    Jorge Torres-Sánchez

    Full Text Available The geometric features of agricultural trees such as canopy area, tree height and crown volume provide useful information about plantation status and crop production. However, these variables are mostly estimated after a time-consuming and hard field work and applying equations that treat the trees as geometric solids, which produce inconsistent results. As an alternative, this work presents an innovative procedure for computing the 3-dimensional geometric features of individual trees and tree-rows by applying two consecutive phases: 1 generation of Digital Surface Models with Unmanned Aerial Vehicle (UAV technology and 2 use of object-based image analysis techniques. Our UAV-based procedure produced successful results both in single-tree and in tree-row plantations, reporting up to 97% accuracy on area quantification and minimal deviations compared to in-field estimations of tree heights and crown volumes. The maps generated could be used to understand the linkages between tree grown and field-related factors or to optimize crop management operations in the context of precision agriculture with relevant agro-environmental implications.

  17. A Novel Methodology for Improving Plant Pest Surveillance in Vineyards and Crops Using UAV-Based Hyperspectral and Spatial Data.

    Science.gov (United States)

    Vanegas, Fernando; Bratanov, Dmitry; Powell, Kevin; Weiss, John; Gonzalez, Felipe

    2018-01-17

    Recent advances in remote sensed imagery and geospatial image processing using unmanned aerial vehicles (UAVs) have enabled the rapid and ongoing development of monitoring tools for crop management and the detection/surveillance of insect pests. This paper describes a (UAV) remote sensing-based methodology to increase the efficiency of existing surveillance practices (human inspectors and insect traps) for detecting pest infestations (e.g., grape phylloxera in vineyards). The methodology uses a UAV integrated with advanced digital hyperspectral, multispectral, and RGB sensors. We implemented the methodology for the development of a predictive model for phylloxera detection. In this method, we explore the combination of airborne RGB, multispectral, and hyperspectral imagery with ground-based data at two separate time periods and under different levels of phylloxera infestation. We describe the technology used-the sensors, the UAV, and the flight operations-the processing workflow of the datasets from each imagery type, and the methods for combining multiple airborne with ground-based datasets. Finally, we present relevant results of correlation between the different processed datasets. The objective of this research is to develop a novel methodology for collecting, processing, analising and integrating multispectral, hyperspectral, ground and spatial data to remote sense different variables in different applications, such as, in this case, plant pest surveillance. The development of such methodology would provide researchers, agronomists, and UAV practitioners reliable data collection protocols and methods to achieve faster processing techniques and integrate multiple sources of data in diverse remote sensing applications.

  18. A Novel Methodology for Improving Plant Pest Surveillance in Vineyards and Crops Using UAV-Based Hyperspectral and Spatial Data

    Science.gov (United States)

    Vanegas, Fernando; Weiss, John; Gonzalez, Felipe

    2018-01-01

    Recent advances in remote sensed imagery and geospatial image processing using unmanned aerial vehicles (UAVs) have enabled the rapid and ongoing development of monitoring tools for crop management and the detection/surveillance of insect pests. This paper describes a (UAV) remote sensing-based methodology to increase the efficiency of existing surveillance practices (human inspectors and insect traps) for detecting pest infestations (e.g., grape phylloxera in vineyards). The methodology uses a UAV integrated with advanced digital hyperspectral, multispectral, and RGB sensors. We implemented the methodology for the development of a predictive model for phylloxera detection. In this method, we explore the combination of airborne RGB, multispectral, and hyperspectral imagery with ground-based data at two separate time periods and under different levels of phylloxera infestation. We describe the technology used—the sensors, the UAV, and the flight operations—the processing workflow of the datasets from each imagery type, and the methods for combining multiple airborne with ground-based datasets. Finally, we present relevant results of correlation between the different processed datasets. The objective of this research is to develop a novel methodology for collecting, processing, analysing and integrating multispectral, hyperspectral, ground and spatial data to remote sense different variables in different applications, such as, in this case, plant pest surveillance. The development of such methodology would provide researchers, agronomists, and UAV practitioners reliable data collection protocols and methods to achieve faster processing techniques and integrate multiple sources of data in diverse remote sensing applications. PMID:29342101

  19. PERANCANGAN SISTEM TRANSFER DAYA NIRKABEL UNTUK UNMANNED AERIAL VEHICLE (UAV MICRO JENIS QUADCOPTER

    Directory of Open Access Journals (Sweden)

    Setyawan Wahyu Pratomo

    2016-11-01

    Full Text Available Dalam Unmanned Aerial Vehicle ( UAV jenis Quadcopter, sumber catu daya berupa baterai yang hanya mampu bekerja 10-15 menit di udara merupakan permasalahan tersendiri bagi performa Quadcopter. Sedangkan perfomansi dari Quadcopter pada ketinggian yang susah dijangkau, diharapkan peran operator yang selama ini harus mengkoneksikan secara manual kabel charging ke baterai bisa digantikan oleh sistem secara otomatis ketika baterai akan habis. Untuk itu dalam paper ini membahas suatu perancangan sistem transfer daya nirkabel untuk Quadcopter mengisi ulang baterai tanpa bantuan operator dan tidak harus dilakukan pendaratan di atas tanah. Proses isi ulang ( charging baterai bisa dilakukan di atas gedung maupun di landasan yang telah terpasang transfer daya nirkabel. Tujuannya adalah meningkatkan performansi kerja Quadcopter di udara sesuai dengan kegunaanya. Dari perancangan sistem transfer daya nirkabel untuk Unmanned Aerial Vehicle ( UAV jenis Quadcopter mengisi ulang ( charging baterai, diperoleh hasil efisiensi transfer daya terbaik sebesar 62,24% dengan jarak efektif 10 cm. Frekuensi sistem transfer daya nirkabel diperoleh dari rangkaian Colpitss Oscillator sebesar 333,1 KHz dengan menerapkan prinsip induksi elektromagnetik.

  20. UAV-based Radar Sounding of Antarctic Ice

    Science.gov (United States)

    Leuschen, Carl; Yan, Jie-Bang; Mahmood, Ali; Rodriguez-Morales, Fernando; Hale, Rick; Camps-Raga, Bruno; Metz, Lynsey; Wang, Zongbo; Paden, John; Bowman, Alec; Keshmiri, Shahriar; Gogineni, Sivaprasad

    2014-05-01

    We developed a compact radar for use on a small UAV to conduct measurements over the ice sheets in Greenland and Antarctica. It operates at center frequencies of 14 and 35 MHz with bandwidths of 1 MHz and 4 MHz, respectively. The radar weighs about 2 kgs and is housed in a box with dimensions of 20.3 cm x 15.2 cm x 13.2 cm. It transmits a signal power of 100 W at a pulse repletion frequency of 10 kHz and requires average power of about 20 W. The antennas for operating the radar are integrated into the wings and airframe of a small UAV with a wingspan of 5.3 m. We selected the frequencies of 14 and 35 MHz based on previous successful soundings of temperate ice in Alaska with a 12.5 MHz impulse radar [Arcone, 2002] and temperate glaciers in Patagonia with a 30 MHz monocycle radar [Blindow et al., 2012]. We developed the radar-equipped UAV to perform surveys over a 2-D grid, which allows us to synthesize a large two-dimensional aperture and obtain fine resolution in both the along- and cross-track directions. Low-frequency, high-sensitivity radars with 2-D aperture synthesis capability are needed to overcome the surface and volume scatter that masks weak echoes from the ice-bed interface of fast-flowing glaciers. We collected data with the radar-equipped UAV on sub-glacial ice near Lake Whillans at both 14 and 35 MHz. We acquired data to evaluate the concept of 2-D aperture synthesis and successfully demonstrated the first successful sounding of ice with a radar on an UAV. We are planning to build multiple radar-equipped UAVs for collecting fine-resolution data near the grounding lines of fast-flowing glaciers. In this presentation we will provide a brief overview of the radar and UAV, as well as present results obtained at both 14 and 35 MHz. Arcone, S. 2002. Airborne-radar stratigraphy and electrical structure of temperate firn: Bagley Ice Field, Alaska, U.S.A. Journal of Glaciology, 48, 317-334. Blindow, N., C. Salat, and G. Casassa. 2012. Airborne GPR sounding of

  1. Technical Note: Advances in flash flood monitoring using unmanned aerial vehicles (UAVs

    Directory of Open Access Journals (Sweden)

    M. T. Perks

    2016-10-01

    Full Text Available Unmanned aerial vehicles (UAVs have the potential to capture information about the earth's surface in dangerous and previously inaccessible locations. Through image acquisition of flash flood events and subsequent object-based analysis, highly dynamic and oft-immeasurable hydraulic phenomena may be quantified at previously unattainable spatial and temporal resolutions. The potential for this approach to provide valuable information about the hydraulic conditions present during dynamic, high-energy flash floods has until now not been explored. In this paper we adopt a novel approach, utilizing the Kande–Lucas–Tomasi (KLT algorithm to track features present on the water surface which are related to the free-surface velocity. Following the successful tracking of features, a method analogous to the vector correction method has enabled accurate geometric rectification of velocity vectors. Uncertainties associated with the rectification process induced by unsteady camera movements are subsequently explored. Geo-registration errors are relatively stable and occur as a result of persistent residual distortion effects following image correction. The apparent ground movement of immobile control points between measurement intervals ranges from 0.05 to 0.13 m. The application of this approach to assess the hydraulic conditions present in the Alyth Burn, Scotland, during a 1 : 200 year flash flood resulted in the generation of an average 4.2 at a rate of 508 measurements s−1. Analysis of these vectors provides a rare insight into the complexity of channel–overbank interactions during flash floods. The uncertainty attached to the calculated velocities is relatively low, with a spatial average across the area of ±0.15 m s−1. Little difference is observed in the uncertainty attached to out-of-bank velocities (±0.15 m s−1, and within-channel velocities (±0.16 m s−1, illustrating the consistency of the approach.

  2. A Robust Vision-based Runway Detection and Tracking Algorithm for Automatic UAV Landing

    KAUST Repository

    Abu Jbara, Khaled F.

    2015-05-01

    This work presents a novel real-time algorithm for runway detection and tracking applied to the automatic takeoff and landing of Unmanned Aerial Vehicles (UAVs). The algorithm is based on a combination of segmentation based region competition and the minimization of a specific energy function to detect and identify the runway edges from streaming video data. The resulting video-based runway position estimates are updated using a Kalman Filter, which can integrate other sensory information such as position and attitude angle estimates to allow a more robust tracking of the runway under turbulence. We illustrate the performance of the proposed lane detection and tracking scheme on various experimental UAV flights conducted by the Saudi Aerospace Research Center. Results show an accurate tracking of the runway edges during the landing phase under various lighting conditions. Also, it suggests that such positional estimates would greatly improve the positional accuracy of the UAV during takeoff and landing phases. The robustness of the proposed algorithm is further validated using Hardware in the Loop simulations with diverse takeoff and landing videos generated using a commercial flight simulator.

  3. UAV-based urban structural damage assessment using object-based image analysis and semantic reasoning

    Science.gov (United States)

    Fernandez Galarreta, J.; Kerle, N.; Gerke, M.

    2015-06-01

    Structural damage assessment is critical after disasters but remains a challenge. Many studies have explored the potential of remote sensing data, but limitations of vertical data persist. Oblique imagery has been identified as more useful, though the multi-angle imagery also adds a new dimension of complexity. This paper addresses damage assessment based on multi-perspective, overlapping, very high resolution oblique images obtained with unmanned aerial vehicles (UAVs). 3-D point-cloud assessment for the entire building is combined with detailed object-based image analysis (OBIA) of façades and roofs. This research focuses not on automatic damage assessment, but on creating a methodology that supports the often ambiguous classification of intermediate damage levels, aiming at producing comprehensive per-building damage scores. We identify completely damaged structures in the 3-D point cloud, and for all other cases provide the OBIA-based damage indicators to be used as auxiliary information by damage analysts. The results demonstrate the usability of the 3-D point-cloud data to identify major damage features. Also the UAV-derived and OBIA-processed oblique images are shown to be a suitable basis for the identification of detailed damage features on façades and roofs. Finally, we also demonstrate the possibility of aggregating the multi-perspective damage information at building level.

  4. Development of a Data Acquisition System for Unmanned Aerial Vehicle (UAV) System Identification

    Science.gov (United States)

    Lear, Donald Joseph

    Aircraft system identification techniques are developed for fixed wing Unmanned Aerial Vehicles (UAV). The use of a designed flight experiment with measured system inputs/outputs can be used to derive aircraft stability derivatives. This project set out to develop a methodology to support an experiment to model pitch damping in the longitudinal short-period mode of a UAV. A Central Composite Response Surface Design was formed using angle of attack and power levels as factors to test for the pitching moment coefficient response induced by a multistep pitching maneuver. Selecting a high-quality data acquisition platform was critical to the success of the project. This system was designed to support fixed wing research through the addition of a custom air data vane capable of measuring angle of attack and sideslip, as well as an airspeed sensor. A Pixhawk autopilot system serves as the core and modification of the device firmware allowed for the integration of custom sensors and custom RC channels dedicated to performing system identification maneuvers. Tests were performed on all existing Pixhawk sensors to validate stated uncertainty values. The air data system was calibrated in a low speed wind tunnel and dynamic performance was verified. The assembled system was then installed in a commercially available UAV known as an Air Titan FPV in order to test the Pixhawk's automated flight maneuvers and determine the final performance of each sensor. Flight testing showed all the critical sensors produced acceptable data for further research. The Air Titan FPV airframe was found to be very flexible and did not lend itself well to accurate measurement of inertial properties. This realization prohibited the construction of the required math models for longitudinal dynamics. It is recommended that future projects using the developed methods choose an aircraft with a more rigid airframe.

  5. Some technical notes on using UAV-based remote sensing for post disaster assessment

    Science.gov (United States)

    Rokhmana, Catur Aries; Andaru, Ruli

    2017-07-01

    Indonesia is located in an area prone to disasters, which are various kinds of natural disasters happen. In disaster management, the geoinformation data are needed to be able to evaluate the impact area. The UAV (Unmanned Aerial Vehicle)-Based remote sensing technology is a good choice to produce a high spatial resolution of less than 15 cm, while the current resolution of the satellite imagery is still greater than 50 cm. This paper shows some technical notes that should be considered when using UAV-Based remote sensing system in post disaster for rapid assessment. Some cases are Aceh Earthquake in years 2013 for seeing infrastructure damages, Banjarnegara landslide in year 2014 for seeing the impact; and Kelud volcano eruption in year 2014 for seeing the impact and volumetric material calculation. The UAV-Based remote sensing system should be able to produce the Orthophoto image that can provide capabilities for visual interpretation the individual damage objects, and the changes situation. Meanwhile the DEM (digital Elevation model) product can derive terrain topography, and volumetric calculation with accuracy 3-5 pixel or sub-meter also. The UAV platform should be able for working remotely and autonomously in dangerous area and limited infrastructures. In mountainous or volcano area, an unconventional flight plan should implemented. Unfortunately, not all impact can be seen from above such as wall crack, some parcel boundaries, and many objects that covered by others higher object. The previous existing geoinformation data are also needed to be able to evaluate the change detection automatically.

  6. Optimized UAV Communication Protocol Based on Prior Locations

    OpenAIRE

    Sboui, Lokman; Rabah, Abdullatif

    2015-01-01

    In this paper, we adopt a new communication protocol between the UAV and fixed on-ground nodes. This protocol tends to reduce communication power consumption by stopping communication if the channel is not good to communicate (i.e. far nodes, obstacles, etc.) The communication is performed using the XBee 868M standard and Libelium wapsmotes. Our designed protocol is based on a new communication model that we propose in this paper. The protocole decides wether to communicate or not after compu...

  7. Using infrared HOG-based pedestrian detection for outdoor autonomous searching UAV with embedded system

    Science.gov (United States)

    Shao, Yanhua; Mei, Yanying; Chu, Hongyu; Chang, Zhiyuan; He, Yuxuan; Zhan, Huayi

    2018-04-01

    Pedestrian detection (PD) is an important application domain in computer vision and pattern recognition. Unmanned Aerial Vehicles (UAVs) have become a major field of research in recent years. In this paper, an algorithm for a robust pedestrian detection method based on the combination of the infrared HOG (IR-HOG) feature and SVM is proposed for highly complex outdoor scenarios on the basis of airborne IR image sequences from UAV. The basic flow of our application operation is as follows. Firstly, the thermal infrared imager (TAU2-336), which was installed on our Outdoor Autonomous Searching (OAS) UAV, is used for taking pictures of the designated outdoor area. Secondly, image sequences collecting and processing were accomplished by using high-performance embedded system with Samsung ODROID-XU4 and Ubuntu as the core and operating system respectively, and IR-HOG features were extracted. Finally, the SVM is used to train the pedestrian classifier. Experiment show that, our method shows promising results under complex conditions including strong noise corruption, partial occlusion etc.

  8. Vision-Based Target Finding and Inspection of a Ground Target Using a Multirotor UAV System.

    Science.gov (United States)

    Hinas, Ajmal; Roberts, Jonathan M; Gonzalez, Felipe

    2017-12-17

    In this paper, a system that uses an algorithm for target detection and navigation and a multirotor Unmanned Aerial Vehicle (UAV) for finding a ground target and inspecting it closely is presented. The system can also be used for accurate and safe delivery of payloads or spot spraying applications in site-specific crop management. A downward-looking camera attached to a multirotor is used to find the target on the ground. The UAV descends to the target and hovers above the target for a few seconds to inspect the target. A high-level decision algorithm based on an OODA (observe, orient, decide, and act) loop was developed as a solution to address the problem. Navigation of the UAV was achieved by continuously sending local position messages to the autopilot via Mavros. The proposed system performed hovering above the target in three different stages: locate, descend, and hover. The system was tested in multiple trials, in simulations and outdoor tests, from heights of 10 m to 40 m. Results show that the system is highly reliable and robust to sensor errors, drift, and external disturbance.

  9. Multi-UAV joint target recognizing based on binocular vision theory

    Directory of Open Access Journals (Sweden)

    Yuan Zhang

    2017-01-01

    Full Text Available Target recognizing of unmanned aerial vehicle (UAV based on image processing take the advantage of 2D information containing in the image for identifying the target. Compare to single UAV with electrical optical tracking system (EOTS, multi-UAV with EOTS is able to take a group of image focused on the suspected target from multiple view point. Benefit from matching each couple of image in this group, points set constituted by matched feature points implicates the depth of each point. Coordinate of target feature points could be computing from depth of feature points. This depth information makes up a cloud of points and reconstructed an exclusive 3D model to recognizing system. Considering the target recognizing do not require precise target model, the cloud of feature points was regrouped into n subsets and reconstructed to a semi-3D model. Casting these subsets in a Cartesian coordinate and applying these projections in convolutional neural networks (CNN respectively, the integrated output of networks is the improved result of recognizing.

  10. Quasi-ADS-B Based UAV Conflict Detection and Resolution to Manned Aircraft

    Directory of Open Access Journals (Sweden)

    Chin E. Lin

    2015-01-01

    Full Text Available A Conflict Detection and Resolution (CD&R system for manned/unmanned aerial vehicle (UAV based on Automatic Dependent Surveillance-Broadcast (ADS-B concept is designed and verified in this paper. The 900 MHz XBee-Pro is selected as data transponder to broadcast flight information among participating aircraft in omnirange. Standard Compact Position Report (CPR format packet data are automatically broadcasted by ID sequencing under Quasi-ADS-B mechanism. Time Division Multiple Access (TDMA monitoring checks the designated time slot and reallocates the conflict ID. This mechanism allows the transponder to effectively share data with multiple aircraft in near airspace. The STM32f103 microprocessor is designed to handle RF, GPS, and flight data with Windows application on manned aircraft and ground control station simultaneously. Different conflict detection and collision avoidance algorithms can be implemented into the system to ensure flight safety. The proposed UAV/CD&R using Quasi-ADS-B transceiver is tested using ultralight aircraft flying at 100–120 km/hr speed in small airspace for mission simulation. The proposed hardware is also useful to additional applications to mountain hikers for emergency search and rescue. The fundamental function by the proposed UAV/CD&R using Quasi-ADS-B is verified with effective signal broadcasting for surveillance and efficient collision alert and avoidance performance to low altitude flights.

  11. Angular Dependency of Hyperspectral Measurements over Wheat Characterized by a Novel UAV Based Goniometer

    Directory of Open Access Journals (Sweden)

    Andreas Burkart

    2015-01-01

    Full Text Available In this study we present a hyperspectral flying goniometer system, based on a rotary-wing unmanned aerial vehicle (UAV equipped with a spectrometer mounted on an active gimbal. We show that this approach may be used to collect multiangular hyperspectral data over vegetated environments. The pointing and positioning accuracy are assessed using structure from motion and vary from σ = 1° to 8° in pointing and σ = 0.7 to 0.8 m in positioning. We use a wheat dataset to investigate the influence of angular effects on the NDVI, TCARI and REIP vegetation indices. Angular effects caused significant variations on the indices: NDVI = 0.83–0.95; TCARI = 0.04–0.116; REIP = 729–735 nm. Our analysis highlights the necessity to consider angular effects in optical sensors when observing vegetation. We compare the measurements of the UAV goniometer to the angular modules of the SCOPE radiative transfer model. Model and measurements are in high accordance (r2 = 0.88 in the infrared region at angles close to nadir; in contrast the comparison show discrepancies at low tilt angles (r2 = 0.25. This study demonstrates that the UAV goniometer is a promising approach for the fast and flexible assessment of angular effects.

  12. Image-based tracking and sensor resource management for UAVs in an urban environment

    Science.gov (United States)

    Samant, Ashwin; Chang, K. C.

    2010-04-01

    Coordination and deployment of multiple unmanned air vehicles (UAVs) requires a lot of human resources in order to carry out a successful mission. The complexity of such a surveillance mission is significantly increased in the case of an urban environment where targets can easily escape from the UAV's field of view (FOV) due to intervening building and line-of-sight obstruction. In the proposed methodology, we focus on the control and coordination of multiple UAVs having gimbaled video sensor onboard for tracking multiple targets in an urban environment. We developed optimal path planning algorithms with emphasis on dynamic target prioritizations and persistent target updates. The command center is responsible for target prioritization and autonomous control of multiple UAVs, enabling a single operator to monitor and control a team of UAVs from a remote location. The results are obtained using extensive 3D simulations in Google Earth using Tangent plus Lyapunov vector field guidance for target tracking.

  13. An analysis of the development and application of plant protection UAV based on advanced materials

    Science.gov (United States)

    Huang, Yuan-hui; Wei, Neng; Quan, Zhi-cheng; Huang, Yu-rong

    2018-06-01

    The development and application of a number of advanced materials plant protection unmanned aerial vehicle (UAV) is an important part of the comprehensive production of agricultural modernization. The paper is taken as an example of Guangxi No. 1 agricultural service aviation science and Technology Co., Ltd. This paper introduces the internal and external environment of the research and development of the plant protection UAV for the advanced materials of the company. The external environment focuses on the role of the plant protection UAV on the development of the agricultural mechanization; the internal environment focuses on the advantages of the UAV in technology research, market promotion and application, which is imperative. Finally, according to the background of the whole industry, we put forward some suggestions for the developing opportunities and challenges faced by plant protection UAV, hoping to proving some ideas for operators, experts and scholars engaged in agricultural industry.

  14. BENCHMARKING THE OPTICAL RESOLVING POWER OF UAV BASED CAMERA SYSTEMS

    Directory of Open Access Journals (Sweden)

    H. Meißner

    2017-08-01

    Full Text Available UAV based imaging and 3D object point generation is an established technology. Some of the UAV users try to address (very highaccuracy applications, i.e. inspection or monitoring scenarios. In order to guarantee such level of detail and accuracy high resolving imaging systems are mandatory. Furthermore, image quality considerably impacts photogrammetric processing, as the tie point transfer, mandatory for forming the block geometry, fully relies on the radiometric quality of images. Thus, empirical testing of radiometric camera performance is an important issue, in addition to standard (geometric calibration, which normally is covered primarily. Within this paper the resolving power of ten different camera/lens installations has been investigated. Selected systems represent different camera classes, like DSLRs, system cameras, larger format cameras and proprietary systems. As the systems have been tested in wellcontrolled laboratory conditions and objective quality measures have been derived, individual performance can be compared directly, thus representing a first benchmark on radiometric performance of UAV cameras. The results have shown, that not only the selection of appropriate lens and camera body has an impact, in addition the image pre-processing, i.e. the use of a specific debayering method, significantly influences the final resolving power.

  15. Perancangan dan Implementasi Kontroler PID untuk Pengaturan Heading dan Pengaturan Arah pada Fixed-Wing Unmanned Aerial Vehicle (UAV

    Directory of Open Access Journals (Sweden)

    Hery setyo widodo

    2012-09-01

    Full Text Available UAV (Unmanned Aerial Vehicle merupakan kendaraan udara tanpa awak yang dikendalikan dari jarak jauh oleh atau tanpa seorang pilot (Autopilot. Kontrol pesawat UAV ada dua variasi utama, variasi pertama yaitu dikontrol melalui pengendali jarak jauh dan variasi kedua adalah pesawat yang terbang secara mandiri berdasarkan program yang dimasukan. Sebuah fixed-winng UAV harus mampu mempertahankan posisinya pada lintasan yang sudah ditentukan selama melakukan tracking lintasan. Keakuratan dalam tracking arah dan heading pesawat sangat berpengaruh terhadap keberhasilan misi penerbangan pesawat UAV dalam memperthankan lintasannya untuk mencapai target. Oleh karena itu pada Tugas Akhir ini dirancang sistem pengaturan dengan menggunakan metode kontrol PID untuk mengatasi kesalahan dalam menjaga lintasan pesawat. Pengaturan arah dan heading pesawat UAV dilakukan dengan memanfaatkan dinamika gerak lateral yang meliputi gerak roll dan yaw dan input dari GPS (Global Positioning System. Dari simulasi diperoleh proses tracking dapat mengikuti rancangan gerak yang diinginkan Pergeseran lintasan pesawat pada saat implementasi kontroler PID disebabkan akurasi GPS yang masih rendah yaitu 3 meter.

  16. Detection of Catchment-Scale Gully-Affected Areas Using Unmanned Aerial Vehicle (UAV on the Chinese Loess Plateau

    Directory of Open Access Journals (Sweden)

    Kai Liu

    2016-12-01

    Full Text Available The Chinese Loess Plateau suffers from serious gully erosion induced by natural and human causes. Gully-affected areas detection is the basic work in this region for gully erosion assessment and monitoring. For the first time, an unmanned aerial vehicle (UAV was applied to extract gully features in this region. Two typical catchments in Changwu and Ansai were selected to represent loess tableland and loess hilly regions, respectively. A high-powered quadrocopter (md4-1000 equipped with a non-metric camera was used for image acquisition. InPho and MapMatrix were applied for semi-automatic workflow including aerial triangulation and model generation. Based on the stereo-imaging and the ground control points, the highly detailed digital elevation models (DEMs and ortho-mosaics were generated. Subsequently, an object-based approach combined with the random forest classifier was designed to detect gully-affected areas. Two experiments were conducted to investigate the influences of segmentation strategy and feature selection. Results showed that vertical and horizontal root-mean-square errors were below 0.5 and 0.2 m, respectively, which were ideal for the Loess Plateau region. The overall extraction accuracy in Changwu and Ansai achieved was 84.62% and 86.46%, respectively, which indicated the potential of the proposed workflow for extracting gully features. This study demonstrated that UAV can bridge the gap between field measurement and satellite-based remote sensing, obtaining a balance in resolution and efficiency for catchment-scale gully erosion research.

  17. Research on UAV Intelligent Obstacle Avoidance Technology During Inspection of Transmission Line

    Science.gov (United States)

    Wei, Chuanhu; Zhang, Fei; Yin, Chaoyuan; Liu, Yue; Liu, Liang; Li, Zongyu; Wang, Wanguo

    Autonomous obstacle avoidance of unmanned aerial vehicle (hereinafter referred to as UAV) in electric power line inspection process has important significance for operation safety and economy for UAV intelligent inspection system of transmission line as main content of UAV intelligent inspection system on transmission line. In the paper, principles of UAV inspection obstacle avoidance technology of transmission line are introduced. UAV inspection obstacle avoidance technology based on particle swarm global optimization algorithm is proposed after common obstacle avoidance technologies are studied. Stimulation comparison is implemented with traditional UAV inspection obstacle avoidance technology which adopts artificial potential field method. Results show that UAV inspection strategy of particle swarm optimization algorithm, adopted in the paper, is prominently better than UAV inspection strategy of artificial potential field method in the aspects of obstacle avoidance effect and the ability of returning to preset inspection track after passing through the obstacle. An effective method is provided for UAV inspection obstacle avoidance of transmission line.

  18. Application of Unmanned Air Vehicles (UAV) in monitoring of terrestrial habitats

    DEFF Research Database (Denmark)

    Sørensen, Peter Borgen; Strandberg, Beate; Bak, Jesper Leth

    2015-01-01

    I the last years there have been high focus on UAVs (drones) for many civil purposes and UAVs are also increasingly used for ecological data gathering. This presentation will first make an appetizer to show the new possibilities of using UAVs. The traditional concept of separating “data......” that are “real” from “models” that are “simulations” has to be refined in the area of field investigations, in order to utilize UAVs to make a revolution in data and understanding about the terrestrial habitats. However, this is not straightforward, and the presentation will line up the obstacles for using UAVs...

  19. EMERGENCY RADIATION SURVEY DEVICE ONBOARD THE UAV

    Directory of Open Access Journals (Sweden)

    S. Bogatov

    2013-08-01

    Full Text Available Radiation survey device (RSD on the base of unmanned aerial vehicle (UAV was developed as an equipment of rescue forces for radiation situation reconnaissance in case of emergency. RSD is multi range radiometer with spectrometer functions capable to work within gamma ray fields of dose rate 10–7 – 10–1 Sievert per hour. UAV md4-1000 (Microdrones GmbH, Germany was selected as the RSD carrier as a reliable vehicle with appropriate properties. Short description of RSD, UAV and developed software features as well as sensitivity assessments for different radiation sources are presented.

  20. An Efficient Energy Constraint Based UAV Path Planning for Search and Coverage

    Directory of Open Access Journals (Sweden)

    German Gramajo

    2017-01-01

    Full Text Available A path planning strategy for a search and coverage mission for a small UAV that maximizes the area covered based on stored energy and maneuverability constraints is presented. The proposed formulation has a high level of autonomy, without requiring an exact choice of optimization parameters, and is appropriate for real-time implementation. The computed trajectory maximizes spatial coverage while closely satisfying terminal constraints on the position of the vehicle and minimizing the time of flight. Comparisons of this formulation to a path planning algorithm based on those with time constraint show equivalent coverage performance but improvement in prediction of overall mission duration and accuracy of the terminal position of the vehicle.

  1. Diverse Planning for UAV Control and Remote Sensing

    Directory of Open Access Journals (Sweden)

    Jan Tožička

    2016-12-01

    Full Text Available Unmanned aerial vehicles (UAVs are suited to various remote sensing missions, such as measuring air quality. The conventional method of UAV control is by human operators. Such an approach is limited by the ability of cooperation among the operators controlling larger fleets of UAVs in a shared area. The remedy for this is to increase autonomy of the UAVs in planning their trajectories by considering other UAVs and their plans. To provide such improvement in autonomy, we need better algorithms for generating alternative trajectory variants that the UAV coordination algorithms can utilize. In this article, we define a novel family of multi-UAV sensing problems, solving task allocation of huge number of tasks (tens of thousands to a group of configurable UAVs with non-zero weight of equipped sensors (comprising the air quality measurement as well together with two base-line solvers. To solve the problem efficiently, we use an algorithm for diverse trajectory generation and integrate it with a solver for the multi-UAV coordination problem. Finally, we experimentally evaluate the multi-UAV sensing problem solver. The evaluation is done on synthetic and real-world-inspired benchmarks in a multi-UAV simulator. Results show that diverse planning is a valuable method for remote sensing applications containing multiple UAVs.

  2. Ground Control Point - Wireless System Network for UAV-based environmental monitoring applications

    Science.gov (United States)

    Mejia-Aguilar, Abraham

    2016-04-01

    In recent years, Unmanned Aerial Vehicles (UAV) have seen widespread civil applications including usage for survey and monitoring services in areas such as agriculture, construction and civil engineering, private surveillance and reconnaissance services and cultural heritage management. Most aerial monitoring services require the integration of information acquired during the flight (such as imagery) with ground-based information (such as GPS information or others) for improved ground truth validation. For example, to obtain an accurate 3D and Digital Elevation Model based on aerial imagery, it is necessary to include ground-based information of coordinate points, which are normally acquired with surveying methods based on Global Position Systems (GPS). However, GPS surveys are very time consuming and especially for longer time series of monitoring data repeated GPS surveys are necessary. In order to improve speed of data collection and integration, this work presents an autonomous system based on Waspmote technologies build on single nodes interlinked in a Wireless Sensor Network (WSN) star-topology for ground based information collection and later integration with surveying data obtained by UAV. Nodes are designed to be visible from the air, to resist extreme weather conditions with low-power consumption. Besides, nodes are equipped with GPS as well as Inertial Measurement Unit (IMU), accelerometer, temperature and soil moisture sensors and thus provide significant advantages in a broad range of applications for environmental monitoring. For our purpose, the WSN transmits the environmental data with 3G/GPRS to a database on a regular time basis. This project provides a detailed case study and implementation of a Ground Control Point System Network for UAV-based vegetation monitoring of dry mountain grassland in the Matsch valley, Italy.

  3. Automated geographic registration and radiometric correction for UAV-based mosaics

    Science.gov (United States)

    Texas A&M University has been operating a large-scale, UAV-based, agricultural remote-sensing research project since 2015. To use UAV-based images in agricultural production, many high-resolution images must be mosaicked together to create an image of an agricultural field. Two key difficulties to s...

  4. An Efficient Seam Elimination Method for UAV Images Based on Wallis Dodging and Gaussian Distance Weight Enhancement.

    Science.gov (United States)

    Tian, Jinyan; Li, Xiaojuan; Duan, Fuzhou; Wang, Junqian; Ou, Yang

    2016-05-10

    The rapid development of Unmanned Aerial Vehicle (UAV) remote sensing conforms to the increasing demand for the low-altitude very high resolution (VHR) image data. However, high processing speed of massive UAV data has become an indispensable prerequisite for its applications in various industry sectors. In this paper, we developed an effective and efficient seam elimination approach for UAV images based on Wallis dodging and Gaussian distance weight enhancement (WD-GDWE). The method encompasses two major steps: first, Wallis dodging was introduced to adjust the difference of brightness between the two matched images, and the parameters in the algorithm were derived in this study. Second, a Gaussian distance weight distribution method was proposed to fuse the two matched images in the overlap region based on the theory of the First Law of Geography, which can share the partial dislocation in the seam to the whole overlap region with an effect of smooth transition. This method was validated at a study site located in Hanwang (Sichuan, China) which was a seriously damaged area in the 12 May 2008 enchuan Earthquake. Then, a performance comparison between WD-GDWE and the other five classical seam elimination algorithms in the aspect of efficiency and effectiveness was conducted. Results showed that WD-GDWE is not only efficient, but also has a satisfactory effectiveness. This method is promising in advancing the applications in UAV industry especially in emergency situations.

  5. The Small Whiskbroom Imager for atmospheric compositioN monitorinG (SWING) and its operations from an unmanned aerial vehicle (UAV) during the AROMAT campaign

    Science.gov (United States)

    Merlaud, Alexis; Tack, Frederik; Constantin, Daniel; Georgescu, Lucian; Maes, Jeroen; Fayt, Caroline; Mingireanu, Florin; Schuettemeyer, Dirk; Meier, Andreas Carlos; Schönardt, Anja; Ruhtz, Thomas; Bellegante, Livio; Nicolae, Doina; Den Hoed, Mirjam; Allaart, Marc; Van Roozendael, Michel

    2018-01-01

    The Small Whiskbroom Imager for atmospheric compositioN monitorinG (SWING) is a compact remote sensing instrument dedicated to mapping trace gases from an unmanned aerial vehicle (UAV). SWING is based on a compact visible spectrometer and a scanning mirror to collect scattered sunlight. Its weight, size, and power consumption are respectively 920 g, 27 cm × 12 cm × 8 cm, and 6 W. SWING was developed in parallel with a 2.5 m flying-wing UAV. This unmanned aircraft is electrically powered, has a typical airspeed of 100 km h-1, and can operate at a maximum altitude of 3 km. We present SWING-UAV experiments performed in Romania on 11 September 2014 during the Airborne ROmanian Measurements of Aerosols and Trace gases (AROMAT) campaign, which was dedicated to test newly developed instruments in the context of air quality satellite validation. The UAV was operated up to 700 m above ground, in the vicinity of the large power plant of Turceni (44.67° N, 23.41° E; 116 m a. s. l. ). These SWING-UAV flights were coincident with another airborne experiment using the Airborne imaging differential optical absorption spectroscopy (DOAS) instrument for Measurements of Atmospheric Pollution (AirMAP), and with ground-based DOAS, lidar, and balloon-borne in situ observations. The spectra recorded during the SWING-UAV flights are analysed with the DOAS technique. This analysis reveals NO2 differential slant column densities (DSCDs) up to 13±0.6×1016 molec cm-2. These NO2 DSCDs are converted to vertical column densities (VCDs) by estimating air mass factors. The resulting NO2 VCDs are up to 4.7±0.4×1016 molec cm-2. The water vapour DSCD measurements, up to 8±0.15×1022 molec cm-2, are used to estimate a volume mixing ratio of water vapour in the boundary layer of 0.013±0.002 mol mol-1. These geophysical quantities are validated with the coincident measurements.

  6. The Small Whiskbroom Imager for atmospheric compositioN monitorinG (SWING and its operations from an unmanned aerial vehicle (UAV during the AROMAT campaign

    Directory of Open Access Journals (Sweden)

    A. Merlaud

    2018-01-01

    Full Text Available The Small Whiskbroom Imager for atmospheric compositioN monitorinG (SWING is a compact remote sensing instrument dedicated to mapping trace gases from an unmanned aerial vehicle (UAV. SWING is based on a compact visible spectrometer and a scanning mirror to collect scattered sunlight. Its weight, size, and power consumption are respectively 920 g, 27 cm  ×  12 cm  ×  8 cm, and 6 W. SWING was developed in parallel with a 2.5 m flying-wing UAV. This unmanned aircraft is electrically powered, has a typical airspeed of 100 km h−1, and can operate at a maximum altitude of 3 km. We present SWING-UAV experiments performed in Romania on 11 September 2014 during the Airborne ROmanian Measurements of Aerosols and Trace gases (AROMAT campaign, which was dedicated to test newly developed instruments in the context of air quality satellite validation. The UAV was operated up to 700 m above ground, in the vicinity of the large power plant of Turceni (44.67° N, 23.41° E; 116 m a. s. l. . These SWING-UAV flights were coincident with another airborne experiment using the Airborne imaging differential optical absorption spectroscopy (DOAS instrument for Measurements of Atmospheric Pollution (AirMAP, and with ground-based DOAS, lidar, and balloon-borne in situ observations. The spectra recorded during the SWING-UAV flights are analysed with the DOAS technique. This analysis reveals NO2 differential slant column densities (DSCDs up to 13±0.6×1016 molec cm−2. These NO2 DSCDs are converted to vertical column densities (VCDs by estimating air mass factors. The resulting NO2 VCDs are up to 4.7±0.4×1016 molec cm−2. The water vapour DSCD measurements, up to 8±0.15×1022 molec cm−2, are used to estimate a volume mixing ratio of water vapour in the boundary layer of 0.013±0.002 mol mol−1. These geophysical quantities are validated with the coincident measurements.

  7. A Robust Transform Estimator Based on Residual Analysis and Its Application on UAV Aerial Images

    Directory of Open Access Journals (Sweden)

    Guorong Cai

    2018-02-01

    Full Text Available Estimating the transformation between two images from the same scene is a fundamental step for image registration, image stitching and 3D reconstruction. State-of-the-art methods are mainly based on sorted residual for generating hypotheses. This scheme has acquired encouraging results in many remote sensing applications. Unfortunately, mainstream residual based methods may fail in estimating the transform between Unmanned Aerial Vehicle (UAV low altitude remote sensing images, due to the fact that UAV images always have repetitive patterns and severe viewpoint changes, which produce lower inlier rate and higher pseudo outlier rate than other tasks. We performed extensive experiments and found the main reason is that these methods compute feature pair similarity within a fixed window, making them sensitive to the size of residual window. To solve this problem, three schemes that based on the distribution of residuals are proposed, which are called Relational Window (RW, Sliding Window (SW, Reverse Residual Order (RRO, respectively. Specially, RW employs a relaxation residual window size to evaluate the highest similarity within a relaxation model length. SW fixes the number of overlap models while varying the length of window size. RRO takes the permutation of residual values into consideration to measure similarity, not only including the number of overlap structures, but also giving penalty to reverse number within the overlap structures. Experimental results conducted on our own built UAV high resolution remote sensing images show that the proposed three strategies all outperform traditional methods in the presence of severe perspective distortion due to viewpoint change.

  8. UAV Flight Control Based on RTX System Simulation Platform

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    Xiaojun Duan

    2014-03-01

    Full Text Available This paper proposes RTX and Matlab UAV flight control system simulation platform based on the advantages and disadvantages of Windows and real-time system RTX. In the simulation platform, we set the RTW toolbox configuration and modify grt_main.c in order to make simulation platform endowed with online parameter adjustment, fault injection. Meanwhile, we develop the interface of the system simulation platform by CVI, thus it makes effective and has good prospects in application. In order to improve the real-time performance of simulation system, the current computer of real-time simulation mostly use real-time operating system to solve simulation model, as well as dual- framework containing in Host and target machine. The system is complex, high cost, and generally used for the control and half of practical system simulation. For the control system designers, they expect to design control law at a computer with Windows-based environment and conduct real-time simulation. This paper proposes simulation platform for UAV flight control system based on RTX and Matlab for this demand.

  9. Accuracy Investigation of Creating Orthophotomaps Based on Images Obtained by Applying Trimble-UX5 UAV

    Science.gov (United States)

    Hlotov, Volodymyr; Hunina, Alla; Siejka, Zbigniew

    2017-06-01

    The main purpose of this work is to confirm the possibility of making largescale orthophotomaps applying unmanned aerial vehicle (UAV) Trimble- UX5. A planned altitude reference of the studying territory was carried out before to the aerial surveying. The studying territory has been marked with distinctive checkpoints in the form of triangles (0.5 × 0.5 × 0.2 m). The checkpoints used to precise the accuracy of orthophotomap have been marked with similar triangles. To determine marked reference point coordinates and check-points method of GNSS in real-time kinematics (RTK) measuring has been applied. Projecting of aerial surveying has been done with the help of installed Trimble Access Aerial Imaging, having been used to run out the UX5. Aerial survey out of the Trimble UX5 UAV has been done with the help of the digital camera SONY NEX-5R from 200m and 300 m altitude. These aerial surveying data have been calculated applying special photogrammetric software Pix 4D. The orthophotomap of the surveying objects has been made with its help. To determine the precise accuracy of the got results of aerial surveying the checkpoint coordinates according to the orthophotomap have been set. The average square error has been calculated according to the set coordinates applying GNSS measurements. A-priori accuracy estimation of spatial coordinates of the studying territory using the aerial surveying data have been calculated: mx=0.11 m, my=0.15 m, mz=0.23 m in the village of Remeniv and mx=0.26 m, my=0.38 m, mz=0.43 m in the town of Vynnyky. The accuracy of determining checkpoint coordinates has been investigated using images obtained out of UAV and the average square error of the reference points. Based on comparative analysis of the got results of the accuracy estimation of the made orthophotomap it can be concluded that the value the average square error does not exceed a-priori accuracy estimation. The possibility of applying Trimble UX5 UAV for making large

  10. POTENTIAL OF UAV BASED CONVERGENT PHOTOGRAMMETRY IN MONITORING REGENERATION STANDARDS

    Directory of Open Access Journals (Sweden)

    U. Vepakomma

    2015-08-01

    Full Text Available Several thousand hectares of forest blocks are regenerating after harvest in Canada. Monitoring their performance over different stages of growth is critical in ensuring future productivity and ecological balance. Tools for rapid evaluation can support timely and reliable planning of interventions. Conventional ground surveys or visual image assessments are either time intensive or inaccurate, while alternate operational remote sensing tools are unavailable. In this study, we test the feasibility and strength of UAV-based photogrammetry with an EO camera on a UAV platform in assessing regeneration performance. Specifically we evaluated stocking, spatial density and height distribution of naturally growing (irregularly spaced stems or planted (regularly spaced stems conifer regeneration in different phases of growth. Standard photogrammetric workflow was applied on the 785 acquired images for 3D reconstruction of the study sites. The required parameters were derived based on automated single stem detection algorithm developed in-house. Comparing with field survey data, preliminary results hold promise. Future studies are planned to expand the scope to larger areas and different stand conditions.

  11. UAV-Based Optical Granulometry as Tool for Detecting Changes in Structure of Flood Depositions

    Directory of Open Access Journals (Sweden)

    Jakub Langhammer

    2017-03-01

    Full Text Available This paper presents a new non-invasive technique of granulometric analysis based on the fusion of two imaging techniques, Unmanned Aerial Vehicles (UAV-based photogrammetry and optical digital granulometry. This newly proposed technique produces seamless coverage of a study site in order to analyze the granulometric properties of alluvium and observe its spatiotemporal changes. This proposed technique is tested by observing changes along the point bar of a mid-latitude mountain stream. UAV photogrammetry acquired at a low-level flight altitude (at a height of 8 m is used to acquire ultra-high resolution orthoimages to build high-precision digital terrain models (DTMs. These orthoimages are covered by a regular virtual grid, and the granulometric properties of the grid fields are analyzed using the digital optical granulometric tool BaseGrain. This tested framework demonstrates the applicability of the proposed method for granulometric analysis, which yields accuracy comparable to that of traditional field optical granulometry. The seamless nature of this method further enables researchers to study the spatial distribution of granulometric properties across multiple study sites, as well as to analyze multitemporal changes using repeated imaging.

  12. Multi-UAV Doppler Information Fusion for Target Tracking Based on Distributed High Degrees Information Filters

    Directory of Open Access Journals (Sweden)

    Hamza Benzerrouk

    2018-03-01

    Full Text Available Multi-Unmanned Aerial Vehicle (UAV Doppler-based target tracking has not been widely investigated, specifically when using modern nonlinear information filters. A high-degree Gauss–Hermite information filter, as well as a seventh-degree cubature information filter (CIF, is developed to improve the fifth-degree and third-degree CIFs proposed in the most recent related literature. These algorithms are applied to maneuvering target tracking based on Radar Doppler range/range rate signals. To achieve this purpose, different measurement models such as range-only, range rate, and bearing-only tracking are used in the simulations. In this paper, the mobile sensor target tracking problem is addressed and solved by a higher-degree class of quadrature information filters (HQIFs. A centralized fusion architecture based on distributed information filtering is proposed, and yielded excellent results. Three high dynamic UAVs are simulated with synchronized Doppler measurement broadcasted in parallel channels to the control center for global information fusion. Interesting results are obtained, with the superiority of certain classes of higher-degree quadrature information filters.

  13. Research study concerning the 3D printing adittion (FDM-fused deposition modeling) to design UAV (UAV-unconventional aerial vehicle) structures

    Science.gov (United States)

    Pascu, Nicoleta Elisabeta; CǎruÅ£aşu, Nicoleta LuminiÅ£a.; Geambaşu, Gabriel George; Adîr, Victor Gabriel; Arion, Aurel Florin; Ivaşcu, Laura

    2018-02-01

    Aerial vehicles have become indispensable. There are in this field UAV (Unconventional Aerial vehicle) and transportation airplanes and other aerospace vehicles for spatial tourism. Today, the research and development activity in aerospace industry is focused to obtain a good and efficient design for airplanes, to solve the problem of high pollution and to reduce the noise. For these goals are necessary to realize light and resistant components. The aerospace industry products are, generally, very complex concerning geometric shapes and the costs are high, usually. Due to the progress in this field (products obtained using FDM) was possible to reduce the number of used tools, welding belts, and, of course, to eliminate a lot of machine tools. In addition, the complex shapes are easier product using this high technology, the cost is more attractive and the time is lower. This paper allows to present a few aspects about FDM technology and the obtained structures using it, as follows: computer geometric modeling (different designing softs) to design and redesign complex structures using 3D printing, for this kind of vehicles; finite element analysis to identify what is the influence of design for different structures; testing the structures.

  14. Persistent Aerial Tracking system for UAVs

    KAUST Repository

    Mueller, Matthias

    2016-12-19

    In this paper, we propose a persistent, robust and autonomous object tracking system for unmanned aerial vehicles (UAVs) called Persistent Aerial Tracking (PAT). A computer vision and control strategy is applied to a diverse set of moving objects (e.g. humans, animals, cars, boats, etc.) integrating multiple UAVs with a stabilized RGB camera. A novel strategy is employed to successfully track objects over a long period, by ‘handing over the camera’ from one UAV to another. We evaluate several state-of-the-art trackers on the VIVID aerial video dataset and additional sequences that are specifically tailored to low altitude UAV target tracking. Based on the evaluation, we select the leading tracker and improve upon it by optimizing for both speed and performance, integrate the complete system into an off-the-shelf UAV, and obtain promising results showing the robustness of our solution in real-world aerial scenarios.

  15. Persistent Aerial Tracking system for UAVs

    KAUST Repository

    Mueller, Matthias; Sharma, Gopal; Smith, Neil; Ghanem, Bernard

    2016-01-01

    In this paper, we propose a persistent, robust and autonomous object tracking system for unmanned aerial vehicles (UAVs) called Persistent Aerial Tracking (PAT). A computer vision and control strategy is applied to a diverse set of moving objects (e.g. humans, animals, cars, boats, etc.) integrating multiple UAVs with a stabilized RGB camera. A novel strategy is employed to successfully track objects over a long period, by ‘handing over the camera’ from one UAV to another. We evaluate several state-of-the-art trackers on the VIVID aerial video dataset and additional sequences that are specifically tailored to low altitude UAV target tracking. Based on the evaluation, we select the leading tracker and improve upon it by optimizing for both speed and performance, integrate the complete system into an off-the-shelf UAV, and obtain promising results showing the robustness of our solution in real-world aerial scenarios.

  16. Next Generation UAV Based Spectral Systems for Environmental Monitoring

    Data.gov (United States)

    National Aeronautics and Space Administration — At present, UAVs used in environmental monitoring mostly collect low spectral resolution imagery, capable of retrieving canopy greenness or properties related water...

  17. AN IMAGE-BASED TECHNIQUE FOR 3D BUILDING RECONSTRUCTION USING MULTI-VIEW UAV IMAGES

    Directory of Open Access Journals (Sweden)

    F. Alidoost

    2015-12-01

    Full Text Available Nowadays, with the development of the urban areas, the automatic reconstruction of the buildings, as an important objects of the city complex structures, became a challenging topic in computer vision and photogrammetric researches. In this paper, the capability of multi-view Unmanned Aerial Vehicles (UAVs images is examined to provide a 3D model of complex building façades using an efficient image-based modelling workflow. The main steps of this work include: pose estimation, point cloud generation, and 3D modelling. After improving the initial values of interior and exterior parameters at first step, an efficient image matching technique such as Semi Global Matching (SGM is applied on UAV images and a dense point cloud is generated. Then, a mesh model of points is calculated using Delaunay 2.5D triangulation and refined to obtain an accurate model of building. Finally, a texture is assigned to mesh in order to create a realistic 3D model. The resulting model has provided enough details of building based on visual assessment.

  18. Corn and sorghum phenotyping using a fixed-wing UAV-based remote sensing system

    Science.gov (United States)

    Shi, Yeyin; Murray, Seth C.; Rooney, William L.; Valasek, John; Olsenholler, Jeff; Pugh, N. Ace; Henrickson, James; Bowden, Ezekiel; Zhang, Dongyan; Thomasson, J. Alex

    2016-05-01

    Recent development of unmanned aerial systems has created opportunities in automation of field-based high-throughput phenotyping by lowering flight operational cost and complexity and allowing flexible re-visit time and higher image resolution than satellite or manned airborne remote sensing. In this study, flights were conducted over corn and sorghum breeding trials in College Station, Texas, with a fixed-wing unmanned aerial vehicle (UAV) carrying two multispectral cameras and a high-resolution digital camera. The objectives were to establish the workflow and investigate the ability of UAV-based remote sensing for automating data collection of plant traits to develop genetic and physiological models. Most important among these traits were plant height and number of plants which are currently manually collected with high labor costs. Vegetation indices were calculated for each breeding cultivar from mosaicked and radiometrically calibrated multi-band imagery in order to be correlated with ground-measured plant heights, populations and yield across high genetic-diversity breeding cultivars. Growth curves were profiled with the aerial measured time-series height and vegetation index data. The next step of this study will be to investigate the correlations between aerial measurements and ground truth measured manually in field and from lab tests.

  19. Remote Marker-Based Tracking for UAV Landing Using Visible-Light Camera Sensor.

    Science.gov (United States)

    Nguyen, Phong Ha; Kim, Ki Wan; Lee, Young Won; Park, Kang Ryoung

    2017-08-30

    Unmanned aerial vehicles (UAVs), which are commonly known as drones, have proved to be useful not only on the battlefields where manned flight is considered too risky or difficult, but also in everyday life purposes such as surveillance, monitoring, rescue, unmanned cargo, aerial video, and photography. More advanced drones make use of global positioning system (GPS) receivers during the navigation and control loop which allows for smart GPS features of drone navigation. However, there are problems if the drones operate in heterogeneous areas with no GPS signal, so it is important to perform research into the development of UAVs with autonomous navigation and landing guidance using computer vision. In this research, we determined how to safely land a drone in the absence of GPS signals using our remote maker-based tracking algorithm based on the visible light camera sensor. The proposed method uses a unique marker designed as a tracking target during landing procedures. Experimental results show that our method significantly outperforms state-of-the-art object trackers in terms of both accuracy and processing time, and we perform test on an embedded system in various environments.

  20. Unmanned aerial vehicle (UAV) application to the structural health assessment of large civil engineering structures

    Science.gov (United States)

    Castiglioni, Carlo A.; Rabuffetti, Angelo S.; Chiarelli, Gian P.; Brambilla, Giovanni; Georgi, Julia

    2017-09-01

    This paper summarizes the experience gained in the structural assessment of an existing Thermal Power Plant (TPP) located near Pristina, focusing on the cooling tower and the flue gas stack, which are the main structures of the TPP. Scope of the work was the evaluation of the actual conditions of the structures and to identify the eventual repair measures in order to guarantee a safe and reliable operation of the TPP in view of the extension of its operational lifetime for the next 30 years. With this aim, a sequence of different activities was performed, like: a topographic survey to compare the actual geometrical configuration with the design one, an investigation of the material properties, an in depth visual inspection in order to detect any visible existing damage. Due to the very high elevations of the constructions and to the lack of appropriate structures aimed to their inspections and maintenance, this activity could not be performed without using Unmanned Aerial Vehicle (UAV). This resulted the safest, most economical and less time-consuming solution identified to map the surface damage in the reinforced concrete elements of these large structures including zones that could not be inspected because out of reach by other means.

  1. Topographic data acquisition in tsunami-prone coastal area using Unmanned Aerial Vehicle (UAV)

    Science.gov (United States)

    Marfai, M. A.; Sunarto; Khakim, N.; Cahyadi, A.; Rosaji, F. S. C.; Fatchurohman, H.; Wibowo, Y. A.

    2018-04-01

    The southern coastal area of Java Island is one of the nine seismic gaps prone to tsunamis. The entire coastline in one of the regencies, Gunungkidul, is exposed to the subduction zone in the Indian Ocean. Also, the growing tourism industries in the regency increase its vulnerability, which places most of its areas at high risk of tsunamis. The same case applies to Kukup, i.e., one of the most well-known beaches in Gunungkidul. Structurally shaped cliffs that surround it experience intensive wave erosion process, but it has very minimum access for evacuation routes. Since tsunami modeling is a very advanced analysis, it requires an accurate topographic data. Therefore, the research aimed to generate the topographic data of Kukup Beach as the baseline in tsunami risk reduction analysis and disaster management. It used aerial photograph data, which was acquired using Unmanned Aerial Vehicle (UAV). The results showed that the aerial photographs captured by drone had accurate elevation and spatial resolution. Therefore, they are applicable for tsunami modeling and disaster management.

  2. Small unmanned aerial vehicles (micro-UAVs, drones) in plant ecology.

    Science.gov (United States)

    Cruzan, Mitchell B; Weinstein, Ben G; Grasty, Monica R; Kohrn, Brendan F; Hendrickson, Elizabeth C; Arredondo, Tina M; Thompson, Pamela G

    2016-09-01

    Low-elevation surveys with small aerial drones (micro-unmanned aerial vehicles [UAVs]) may be used for a wide variety of applications in plant ecology, including mapping vegetation over small- to medium-sized regions. We provide an overview of methods and procedures for conducting surveys and illustrate some of these applications. Aerial images were obtained by flying a small drone along transects over the area of interest. Images were used to create a composite image (orthomosaic) and a digital surface model (DSM). Vegetation classification was conducted manually and using an automated routine. Coverage of an individual species was estimated from aerial images. We created a vegetation map for the entire region from the orthomosaic and DSM, and mapped the density of one species. Comparison of our manual and automated habitat classification confirmed that our mapping methods were accurate. A species with high contrast to the background matrix allowed adequate estimate of its coverage. The example surveys demonstrate that small aerial drones are capable of gathering large amounts of information on the distribution of vegetation and individual species with minimal impact to sensitive habitats. Low-elevation aerial surveys have potential for a wide range of applications in plant ecology.

  3. Small unmanned aerial vehicles (micro-UAVs, drones) in plant ecology1

    Science.gov (United States)

    Cruzan, Mitchell B.; Weinstein, Ben G.; Grasty, Monica R.; Kohrn, Brendan F.; Hendrickson, Elizabeth C.; Arredondo, Tina M.; Thompson, Pamela G.

    2016-01-01

    Premise of the study: Low-elevation surveys with small aerial drones (micro–unmanned aerial vehicles [UAVs]) may be used for a wide variety of applications in plant ecology, including mapping vegetation over small- to medium-sized regions. We provide an overview of methods and procedures for conducting surveys and illustrate some of these applications. Methods: Aerial images were obtained by flying a small drone along transects over the area of interest. Images were used to create a composite image (orthomosaic) and a digital surface model (DSM). Vegetation classification was conducted manually and using an automated routine. Coverage of an individual species was estimated from aerial images. Results: We created a vegetation map for the entire region from the orthomosaic and DSM, and mapped the density of one species. Comparison of our manual and automated habitat classification confirmed that our mapping methods were accurate. A species with high contrast to the background matrix allowed adequate estimate of its coverage. Discussion: The example surveys demonstrate that small aerial drones are capable of gathering large amounts of information on the distribution of vegetation and individual species with minimal impact to sensitive habitats. Low-elevation aerial surveys have potential for a wide range of applications in plant ecology. PMID:27672518

  4. UNMANNED AERIAL VEHICLE (UAV) HYPERSPECTRAL REMOTE SENSING FOR DRYLAND VEGETATION MONITORING

    Energy Technology Data Exchange (ETDEWEB)

    Nancy F. Glenn; Jessica J. Mitchell; Matthew O. Anderson; Ryan C. Hruska

    2012-06-01

    UAV-based hyperspectral remote sensing capabilities developed by the Idaho National Lab and Idaho State University, Boise Center Aerospace Lab, were recently tested via demonstration flights that explored the influence of altitude on geometric error, image mosaicking, and dryland vegetation classification. The test flights successfully acquired usable flightline data capable of supporting classifiable composite images. Unsupervised classification results support vegetation management objectives that rely on mapping shrub cover and distribution patterns. Overall, supervised classifications performed poorly despite spectral separability in the image-derived endmember pixels. Future mapping efforts that leverage ground reference data, ultra-high spatial resolution photos and time series analysis should be able to effectively distinguish native grasses such as Sandberg bluegrass (Poa secunda), from invasives such as burr buttercup (Ranunculus testiculatus) and cheatgrass (Bromus tectorum).

  5. UAV remote sensing atmospheric degradation image restoration based on multiple scattering APSF estimation

    Science.gov (United States)

    Qiu, Xiang; Dai, Ming; Yin, Chuan-li

    2017-09-01

    Unmanned aerial vehicle (UAV) remote imaging is affected by the bad weather, and the obtained images have the disadvantages of low contrast, complex texture and blurring. In this paper, we propose a blind deconvolution model based on multiple scattering atmosphere point spread function (APSF) estimation to recovery the remote sensing image. According to Narasimhan analytical theory, a new multiple scattering restoration model is established based on the improved dichromatic model. Then using the L0 norm sparse priors of gradient and dark channel to estimate APSF blur kernel, the fast Fourier transform is used to recover the original clear image by Wiener filtering. By comparing with other state-of-the-art methods, the proposed method can correctly estimate blur kernel, effectively remove the atmospheric degradation phenomena, preserve image detail information and increase the quality evaluation indexes.

  6. A UAV based system for real time flash flood monitoring in desert environments using Lagrangian microsensors

    KAUST Repository

    Abdelkader, Mohamed

    2013-05-01

    Floods are the most common natural disasters, causing thousands of casualties every year in the world. In particular, flash flood events are particularly deadly because of the short timescales on which they occur. Most casualties could be avoided with advance warning, for which real time monitoring is critical. While satellite-based high resolution weather forecasts can help predict floods to a certain extent, they are not reliable enough, as flood models depend on a large number of parameters that cannot be estimated beforehand. In this article, we present a novel flood sensing architecture to monitor large scale desert hydrological basins surrounding metropolitan areas, based on unmanned air vehicles. The system relies on Lagrangian (mobile) microsensors, that are released by a swarm of UAVs. A preliminary testbed implementing this technology is briefly described, and future research directions and problems are discussed. © 2013 IEEE.

  7. Development Situation, Trend and Countermeasure of Consumer-level UAV Market in China

    Directory of Open Access Journals (Sweden)

    Kang Yu-Lei

    2017-01-01

    Full Text Available This paper is based on the status of Chinese consumer-level UAV(Unmanned Aerial Vehicle market. According to the main problems in Chinese consumer-level UAV market, the author analyses the trends of Chinese consumer-level UAV market. Then, the author put forward some suggestions to develop Chinese consumer-level UAV market. In 21st century, the research and development expenditure presents the explosive growth in Chinese consumer-level UAV market. From the year of 2012, DJI released their first consumer-level UAV product. Amazon, Facebook, Google and other companies have announced their entry into the UAV market. In 2016, Huawei also announced that it will enter the UAV market.

  8. UAV formation control design with obstacle avoidance in dynamic three-dimensional environment.

    Science.gov (United States)

    Chang, Kai; Xia, Yuanqing; Huang, Kaoli

    2016-01-01

    This paper considers the artificial potential field method combined with rotational vectors for a general problem of multi-unmanned aerial vehicle (UAV) systems tracking a moving target in dynamic three-dimensional environment. An attractive potential field is generated between the leader and the target. It drives the leader to track the target based on the relative position of them. The other UAVs in the formation are controlled to follow the leader by the attractive control force. The repulsive force affects among the UAVs to avoid collisions and distribute the UAVs evenly on the spherical surface whose center is the leader-UAV. Specific orders or positions of the UAVs are not required. The trajectories of avoidance obstacle can be obtained through two kinds of potential field with rotation vectors. Every UAV can choose the optimal trajectory to avoid the obstacle and reconfigure the formation after passing the obstacle. Simulations study on UAV are presented to demonstrate the effectiveness of proposed method.

  9. Fuzzy-Based Hybrid Control Algorithm for the Stabilization of a Tri-Rotor UAV.

    Science.gov (United States)

    Ali, Zain Anwar; Wang, Daobo; Aamir, Muhammad

    2016-05-09

    In this paper, a new and novel mathematical fuzzy hybrid scheme is proposed for the stabilization of a tri-rotor unmanned aerial vehicle (UAV). The fuzzy hybrid scheme consists of a fuzzy logic controller, regulation pole-placement tracking (RST) controller with model reference adaptive control (MRAC), in which adaptive gains of the RST controller are being fine-tuned by a fuzzy logic controller. Brushless direct current (BLDC) motors are installed in the triangular frame of the tri-rotor UAV, which helps maintain control on its motion and different altitude and attitude changes, similar to rotorcrafts. MRAC-based MIT rule is proposed for system stability. Moreover, the proposed hybrid controller with nonlinear flight dynamics is shown in the presence of translational and rotational velocity components. The performance of the proposed algorithm is demonstrated via MATLAB simulations, in which the proposed fuzzy hybrid controller is compared with the existing adaptive RST controller. It shows that our proposed algorithm has better transient performance with zero steady-state error, and fast convergence towards stability.

  10. Vision Based Displacement Detection for Stabilized UAV Control on Cloud Server

    Directory of Open Access Journals (Sweden)

    Hyeok-June Jeong

    2016-01-01

    Full Text Available Nowadays, image processing solution is used in many fields such as traffic information systems and illegal intrusion detection systems. Now, to assist with the control of camera-equipped devices, appropriate image processing techniques are needed for moving rather than fixed observers. For achieving this goal, an algorithm should derive the desired results quickly and accurately; thus, this paper considers two characteristics: functional performance (reliability and temporal performance (efficiency. Reliability means how well the desired results can be achieved, and efficiency means how quickly the result can be calculated. This paper suggests an optimized real-time image algorithm based on the integration of the optical flow and Speeded-Up Robust Features (SURF algorithms. This algorithm determines horizontal or vertical movement of the camera and then extracts its displacement. The proposed algorithm can be used to stabilize an Unmanned Aerial Vehicle (UAV in situations where it is drifting due to inertia and external forces, like wind, in parallel. The proposed algorithm is efficient in achieving drift stabilization by movement detection; however, it is not appropriate for image processing in small UAVs. To solve this problem, this study proposes an image processing method that uses a high-performance computer.

  11. Flight route Designing and mission planning Of power line inspecting system Based On multi-sensor UAV

    International Nuclear Information System (INIS)

    Xiaowei, Xie; Zhengjun, Liu; Zhiquan, Zuo

    2014-01-01

    In order to obtain various information of power facilities such as spatial location, geometry, images data and video information in the infrared and ultraviolet band and so on, Unmanned Aerial Vehicle (UAV) power line inspecting system needs to integrate a variety of sensors for data collection. Low altitude and side-looking imaging are required for UAV flight to ensure sensors to acquire high-quality data and device security. In this paper, UAV power line inspecting system is deferent from existing ones that used in Surveying and Mapping. According to characteristics of UAV for example equipped multiple sensor, side-looking imaging, working at low altitude, complex terrain conditions and corridor type flight, this paper puts forward a UAV power line inspecting scheme which comprehensively considered of the UAV performance, sensor parameters and task requirements. The scheme is finally tested in a region of Guangdong province, and the preliminary results show that the scheme is feasible

  12. Vision-IMU based collaborative control of a blind UAV

    NARCIS (Netherlands)

    Hoogervorst, R.; Stramigioli, Stefano; Wopereis, Han Willem; Fumagalli, Matteo

    2015-01-01

    Position estimation of UAVs is usually done using onboard sensors such as GPS and camera. However, in certain practical situations, the measurements of both the GPS and the onboard camera of the UAV might not always be available or reliable. This paper investigates the possibility to overcome

  13. Object Georeferencing in UAV-Based SAR Terrain Images

    Directory of Open Access Journals (Sweden)

    Łabowski Michał

    2016-12-01

    Full Text Available Synthetic aperture radars (SAR allow to obtain high resolution terrain images comparable with the resolution of optical methods. Radar imaging is independent on the weather conditions and the daylight. The process of analysis of the SAR images consists primarily of identifying of interesting objects. The ability to determine their geographical coordinates can increase usability of the solution from a user point of view. The paper presents a georeferencing method of the radar terrain images. The presented images were obtained from the SAR system installed on board an Unmanned Aerial Vehicle (UAV. The system was developed within a project under acronym WATSAR realized by the Military University of Technology and WB Electronics S.A. The source of the navigation data was an INS/GNSS system integrated by the Kalman filter with a feed-backward correction loop. The paper presents the terrain images obtained during flight tests and results of selected objects georeferencing with an assessment of the accuracy of the method.

  14. LUNA: low-flying UAV-based forest monitoring system

    Science.gov (United States)

    Keizer, Jan Jacob; Pereira, Luísa; Pinto, Glória; Alves, Artur; Barros, Antonio; Boogert, Frans-Joost; Cambra, Sílvia; de Jesus, Cláudia; Frankenbach, Silja; Mesquita, Raquel; Serôdio, João; Martins, José; Almendra, Ricardo

    2015-04-01

    The LUNA project is aiming to develop an information system for precision forestry and, in particular, the monitoring of eucalypt plantations that is first and foremost based on multi-spectral imagery acquired using low-flying uav's. The presentation will focus on the first phase of image acquisition, processing and analysis for a series of pot experiments addressing main threats for early-stage eucalypt plantations in Portugal, i.e. acute , chronic and cyclic hydric stress, nutrient stress, fungal infections and insect plague attacks. The imaging results will be compared with spectroscopic measurements as well as with eco-physiological and plant morphological measurements. Furthermore, the presentation will show initial results of the project's second phase, comprising field tests in existing eucalypt plantations in north-central Portugal.

  15. UAV-based NDVI calculation over grassland: An alternative approach

    Science.gov (United States)

    Mejia-Aguilar, Abraham; Tomelleri, Enrico; Asam, Sarah; Zebisch, Marc

    2016-04-01

    The Normalised Difference Vegetation Index (NDVI) is one of the most widely used indicators for monitoring and assessing vegetation in remote sensing. The index relies on the reflectance difference between the near infrared (NIR) and red light and is thus able to track variations of structural, phenological, and biophysical parameters for seasonal and long-term monitoring. Conventionally, NDVI is inferred from space-borne spectroradiometers, such as MODIS, with moderate resolution up to 250 m ground resolution. In recent years, a new generation of miniaturized radiometers and integrated hyperspectral sensors with high resolution became available. Such small and light instruments are particularly adequate to be mounted on airborne unmanned aerial vehicles (UAV) used for monitoring services reaching ground sampling resolution in the order of centimetres. Nevertheless, such miniaturized radiometers and hyperspectral sensors are still very expensive and require high upfront capital costs. Therefore, we propose an alternative, mainly cheaper method to calculate NDVI using a camera constellation consisting of two conventional consumer-grade cameras: (i) a Ricoh GR modified camera that acquires the NIR spectrum by removing the internal infrared filter. A mounted optical filter additionally obstructs all wavelengths below 700 nm. (ii) A Ricoh GR in RGB configuration using two optical filters for blocking wavelengths below 600 nm as well as NIR and ultraviolet (UV) light. To assess the merit of the proposed method, we carry out two comparisons: First, reflectance maps generated by the consumer-grade camera constellation are compared to reflectance maps produced with a hyperspectral camera (Rikola). All imaging data and reflectance maps are processed using the PIX4D software. In the second test, the NDVI at specific points of interest (POI) generated by the consumer-grade camera constellation is compared to NDVI values obtained by ground spectral measurements using a

  16. Swift Ultra Long Endurance (SULE) Unmanned Air Vehicle (UAV), Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Ever since UAV's emerged as a reliable science instrument, the technology has been used to augment satellites, balloon flights, and provide spatial/resolution data...

  17. Omnidirectional vision applied to Unmanned Aerial Vehicles (UAVs) attitude and heading estimation

    OpenAIRE

    Mondragon, Ivan F.; Campoy, Pascual; Martinez, Carol; Olivares Mendez, Miguel Angel

    2010-01-01

    This paper presents an aircraft attitude and heading estimator using catadioptric images as a principal sensor for UAV or as a redundant system for IMU (Inertial Measure Unit) and gyro sensors. First, we explain how the unified theory for central catadioptric cameras is used for attitude and heading estimation, explaining how the skyline is projected on the catadioptric image and how it is segmented and used to calculate the UAV's attitude. Then, we use appearance images to obtain a visual co...

  18. Assessing UAVs in Monitoring Crop Evapotranspiration within a Heterogeneous Soil

    Science.gov (United States)

    Rouze, G.; Neely, H.; Morgan, C.; Kustas, W. P.; McKee, L.; Prueger, J. H.; Cope, D.; Yang, C.; Thomasson, A.; Jung, J.

    2017-12-01

    Airborne and satellite remote sensing methods have been developed to provide ET estimates across entire management fields. However, airborne-based ET is not particularly cost-effective and satellite-based ET provides insufficient spatial/temporal information. ET estimations through remote sensing are also problematic where soils are highly variable within a given management field. Unlike airborne/satellite-based ET, Unmanned Aerial Vehicle (UAV)-based ET has the potential to increase the spatial and temporal detail of these measurements, particularly within a heterogeneous soil landscape. However, it is unclear to what extent UAVs can model ET. The overall goal of this project was to assess the capability of UAVs in modeling ET across a heterogeneous landscape. Within a 20-ha irrigated cotton field in Central Texas, low-altitude UAV surveys were conducted throughout the growing season over two soil types. UAVs were equipped with thermal and multispectral cameras to obtain canopy temperature and NDVI, respectively. UAV data were supplemented simultaneously with ground-truth measurements such as Leaf Area Index (LAI) and plant height. Both remote sensing and ground-truth parameters were used to model ET using a Two-Source Energy Balance (TSEB) model. UAV-based estimations of ET and other energy balance components were validated against energy balance measurements obtained from nearby eddy covariance towers that were installed within each soil type. UAV-based ET fluxes were also compared with airborne and satellite (Landsat 8)-based ET fluxes collected near the time of the UAV survey.

  19. Determination of the State of Strain of Large Floating Covers Using Unmanned Aerial Vehicle (UAV) Aided Photogrammetry

    Science.gov (United States)

    Ong, Wern Hann; Chiu, Wing Kong; Kuen, Thomas; Kodikara, Jayantha

    2017-01-01

    Floating covers used in waste water treatment plants are one of the many structures formed with membrane materials. These structures are usually large and can spread over an area measuring 470 m × 170 m. The aim of this paper is to describe recent work to develop an innovative and effective approach for structural health monitoring (SHM) of such large membrane-like infrastructure. This paper will propose a potentially cost-effective non-contact approach for full-field strain and stress mapping using an unmanned aerial vehicle (UAV) mounted with a digital camera and a global positioning system (GPS) tracker. The aim is to use the images acquired by the UAV to define the geometry of the floating cover using photogrammetry. In this manner, any changes in the geometry of the floating cover due to forces acting beneath resulting from its deployment and usage can be determined. The time-scale for these changes is in terms of weeks and months. The change in the geometry can be implemented as input conditions to a finite element model (FEM) for stress prediction. This will facilitate the determination of the state of distress of the floating cover. This paper investigates the possibility of using data recorded from a UAV to predict the strain level and assess the health of such structures. An investigation was first conducted on a laboratory sized membrane structure instrumented with strain gauges for comparison against strains, which were computed from 3D scans of the membrane geometry. Upon validating the technique in the laboratory, it was applied to a more realistic scenario: an outdoor test membrane structure and capable UAV were constructed to see if the shape of the membrane could be computed. The membrane displacements were then used to calculate the membrane stress and strain, state demonstrating a new way to perform structural health monitoring on membrane structures. PMID:28788081

  20. Woodland Mapping at Single-Tree Levels Using Object-Oriented Classification of Unmanned Aerial Vehicle (uav) Images

    Science.gov (United States)

    Chenari, A.; Erfanifard, Y.; Dehghani, M.; Pourghasemi, H. R.

    2017-09-01

    Remotely sensed datasets offer a reliable means to precisely estimate biophysical characteristics of individual species sparsely distributed in open woodlands. Moreover, object-oriented classification has exhibited significant advantages over different classification methods for delineation of tree crowns and recognition of species in various types of ecosystems. However, it still is unclear if this widely-used classification method can have its advantages on unmanned aerial vehicle (UAV) digital images for mapping vegetation cover at single-tree levels. In this study, UAV orthoimagery was classified using object-oriented classification method for mapping a part of wild pistachio nature reserve in Zagros open woodlands, Fars Province, Iran. This research focused on recognizing two main species of the study area (i.e., wild pistachio and wild almond) and estimating their mean crown area. The orthoimage of study area was consisted of 1,076 images with spatial resolution of 3.47 cm which was georeferenced using 12 ground control points (RMSE=8 cm) gathered by real-time kinematic (RTK) method. The results showed that the UAV orthoimagery classified by object-oriented method efficiently estimated mean crown area of wild pistachios (52.09±24.67 m2) and wild almonds (3.97±1.69 m2) with no significant difference with their observed values (α=0.05). In addition, the results showed that wild pistachios (accuracy of 0.90 and precision of 0.92) and wild almonds (accuracy of 0.90 and precision of 0.89) were well recognized by image segmentation. In general, we concluded that UAV orthoimagery can efficiently produce precise biophysical data of vegetation stands at single-tree levels, which therefore is suitable for assessment and monitoring open woodlands.

  1. Determination of the State of Strain of Large Floating Covers Using Unmanned Aerial Vehicle (UAV) Aided Photogrammetry.

    Science.gov (United States)

    Ong, Wern Hann; Chiu, Wing Kong; Kuen, Thomas; Kodikara, Jayantha

    2017-07-28

    Floating covers used in waste water treatment plants are one of the many structures formed with membrane materials. These structures are usually large and can spread over an area measuring 470 m × 170 m. The aim of this paper is to describe recent work to develop an innovative and effective approach for structural health monitoring (SHM) of such large membrane-like infrastructure. This paper will propose a potentially cost-effective non-contact approach for full-field strain and stress mapping using an unmanned aerial vehicle (UAV) mounted with a digital camera and a global positioning system (GPS) tracker. The aim is to use the images acquired by the UAV to define the geometry of the floating cover using photogrammetry. In this manner, any changes in the geometry of the floating cover due to forces acting beneath resulting from its deployment and usage can be determined. The time-scale for these changes is in terms of weeks and months. The change in the geometry can be implemented as input conditions to a finite element model (FEM) for stress prediction. This will facilitate the determination of the state of distress of the floating cover. This paper investigates the possibility of using data recorded from a UAV to predict the strain level and assess the health of such structures. An investigation was first conducted on a laboratory sized membrane structure instrumented with strain gauges for comparison against strains, which were computed from 3D scans of the membrane geometry. Upon validating the technique in the laboratory, it was applied to a more realistic scenario: an outdoor test membrane structure and capable UAV were constructed to see if the shape of the membrane could be computed. The membrane displacements were then used to calculate the membrane stress and strain, state demonstrating a new way to perform structural health monitoring on membrane structures.

  2. Determination of the State of Strain of Large Floating Covers Using Unmanned Aerial Vehicle (UAV Aided Photogrammetry

    Directory of Open Access Journals (Sweden)

    Wern Hann Ong

    2017-07-01

    Full Text Available Floating covers used in waste water treatment plants are one of the many structures formed with membrane materials. These structures are usually large and can spread over an area measuring 470 m × 170 m. The aim of this paper is to describe recent work to develop an innovative and effective approach for structural health monitoring (SHM of such large membrane-like infrastructure. This paper will propose a potentially cost-effective non-contact approach for full-field strain and stress mapping using an unmanned aerial vehicle (UAV mounted with a digital camera and a global positioning system (GPS tracker. The aim is to use the images acquired by the UAV to define the geometry of the floating cover using photogrammetry. In this manner, any changes in the geometry of the floating cover due to forces acting beneath resulting from its deployment and usage can be determined. The time-scale for these changes is in terms of weeks and months. The change in the geometry can be implemented as input conditions to a finite element model (FEM for stress prediction. This will facilitate the determination of the state of distress of the floating cover. This paper investigates the possibility of using data recorded from a UAV to predict the strain level and assess the health of such structures. An investigation was first conducted on a laboratory sized membrane structure instrumented with strain gauges for comparison against strains, which were computed from 3D scans of the membrane geometry. Upon validating the technique in the laboratory, it was applied to a more realistic scenario: an outdoor test membrane structure and capable UAV were constructed to see if the shape of the membrane could be computed. The membrane displacements were then used to calculate the membrane stress and strain, state demonstrating a new way to perform structural health monitoring on membrane structures.

  3. WOODLAND MAPPING AT SINGLE-TREE LEVELS USING OBJECT-ORIENTED CLASSIFICATION OF UNMANNED AERIAL VEHICLE (UAV IMAGES

    Directory of Open Access Journals (Sweden)

    A. Chenari

    2017-09-01

    Full Text Available Remotely sensed datasets offer a reliable means to precisely estimate biophysical characteristics of individual species sparsely distributed in open woodlands. Moreover, object-oriented classification has exhibited significant advantages over different classification methods for delineation of tree crowns and recognition of species in various types of ecosystems. However, it still is unclear if this widely-used classification method can have its advantages on unmanned aerial vehicle (UAV digital images for mapping vegetation cover at single-tree levels. In this study, UAV orthoimagery was classified using object-oriented classification method for mapping a part of wild pistachio nature reserve in Zagros open woodlands, Fars Province, Iran. This research focused on recognizing two main species of the study area (i.e., wild pistachio and wild almond and estimating their mean crown area. The orthoimage of study area was consisted of 1,076 images with spatial resolution of 3.47 cm which was georeferenced using 12 ground control points (RMSE=8 cm gathered by real-time kinematic (RTK method. The results showed that the UAV orthoimagery classified by object-oriented method efficiently estimated mean crown area of wild pistachios (52.09±24.67 m2 and wild almonds (3.97±1.69 m2 with no significant difference with their observed values (α=0.05. In addition, the results showed that wild pistachios (accuracy of 0.90 and precision of 0.92 and wild almonds (accuracy of 0.90 and precision of 0.89 were well recognized by image segmentation. In general, we concluded that UAV orthoimagery can efficiently produce precise biophysical data of vegetation stands at single-tree levels, which therefore is suitable for assessment and monitoring open woodlands.

  4. Rapid Control Prototyping and PIL Co-Simulation of a Quadrotor UAV Based on NI myRIO-1900 Board

    OpenAIRE

    Soufiene Bouallègue; Rabii Fessi

    2016-01-01

    In this paper, a new Computer Aided Design (CAD) methodology for the Processor-In-the-Loop (PIL) co-simulation and Rapid Control Prototyping (RCP) of a Quadrotor Vertical Take-Off and Landing (VTOL) type of Unmanned Arial Vehicle (UAV) is proposed and successfully implemented around an embedded NI myRIO-1900 target and a host PC. The developed software (SW) and hardware (HW) prototyping platform is based on the Control Design and Simulation (CDSim) module of LabVIEW environment and an establi...

  5. Quantifying the morphodynamics of river restoration schemes using Unmanned Aerial Vehicles (UAVs)

    Science.gov (United States)

    Williams, Richard; Byrne, Patrick; Gilles, Eric; Hart, John; Hoey, Trevor; Maniatis, George; Moir, Hamish; Reid, Helen; Ves, Nikolas

    2017-04-01

    River restoration schemes are particularly sensitive to morphological adjustment during the first set of high-flow events that they are subjected to. Quantifying elevation change associated with morphological adjustment can contribute to improved adaptive decision making to ensure river restoration scheme objectives are achieved. To date the relatively high cost, technical demands and challenging logistics associated with acquiring repeat, high-resolution topographic surveys has resulted in a significant barrier to monitoring the three-dimensional morphodynamics of river restoration schemes. The availability of low-cost, consumer grade Unmanned Aerial Vehicles that are capable of acquiring imagery for processing using Structure-from-Motion Multi-View Stereo (SfM MVS) photogrammetry has the potential to transform the survey the morphodynamics of river restoration schemes. Application guidance does, however, need to be developed to fully exploit the advances of UAV technology and SfM MVS processing techniques. In particular, there is a need to quantify the effect of the number and spatial distribution of ground targets on vertical error. This is particularly significant because vertical errors propagate when mapping morphological change, and thus determine the evidence that is available for decision making. This presentation presents results from a study that investigated how the number and spatial distribution of targets influenced vertical error, and then used the findings to determine survey protocols for a monitoring campaign that has quantified morphological change across a number of restoration schemes. At the Swindale river restoration scheme, Cumbria, England, 31 targets were distributed across a 700 m long reach and the centre of each target was surveyed using RTK-GPS. Using the targets as General Control Points (GCPs) or checkpoints, they were divided into three different spatial patterns (centre, edge and random) and used for processing images acquired

  6. Towards a Transferable UAV-Based Framework for River Hydromorphological Characterization.

    Science.gov (United States)

    Rivas Casado, Mónica; González, Rocío Ballesteros; Ortega, José Fernando; Leinster, Paul; Wright, Ros

    2017-09-26

    The multiple protocols that have been developed to characterize river hydromorphology, partly in response to legislative drivers such as the European Union Water Framework Directive (EU WFD), make the comparison of results obtained in different countries challenging. Recent studies have analyzed the comparability of existing methods, with remote sensing based approaches being proposed as a potential means of harmonizing hydromorphological characterization protocols. However, the resolution achieved by remote sensing products may not be sufficient to assess some of the key hydromorphological features that are required to allow an accurate characterization. Methodologies based on high resolution aerial photography taken from Unmanned Aerial Vehicles (UAVs) have been proposed by several authors as potential approaches to overcome these limitations. Here, we explore the applicability of an existing UAV based framework for hydromorphological characterization to three different fluvial settings representing some of the distinct ecoregions defined by the WFD geographical intercalibration groups (GIGs). The framework is based on the automated recognition of hydromorphological features via tested and validated Artificial Neural Networks (ANNs). Results show that the framework is transferable to the Central-Baltic and Mediterranean GIGs with accuracies in feature identification above 70%. Accuracies of 50% are achieved when the framework is implemented in the Very Large Rivers GIG. The framework successfully identified vegetation, deep water, shallow water, riffles, side bars and shadows for the majority of the reaches. However, further algorithm development is required to ensure a wider range of features (e.g., chutes, structures and erosion) are accurately identified. This study also highlights the need to develop an objective and fit for purpose hydromorphological characterization framework to be adopted within all EU member states to facilitate comparison of results.

  7. Looking Inward to the Use of Unmanned Aerial Vehicle (UAV) for Rice Production Assessment in Indonesia

    Science.gov (United States)

    Komaladara, A. A. S. P.; Ambarawati, I. G. A. A.; Wijaya, I. M. A. S.; Hongo, C.; Mirah Adi, A. A. A.

    2015-12-01

    Rice is the main source of carbohydrate for most Indonesians. Rice production has been very dynamic due to improved infrastructure, research and development, and better farm management. However, rice production is susceptible to loss caused by drought, pest and disease attack and climate change. With the growing concern on sustainable and self-reliance food production in the country, there is an urgency to encourage research and efforts to increase rice productivity. Attempts to provide spatial distribution of rice fields on high resolution optical remote sensing data have been employed to some extent, however this technology could be costly. The use of UAV has been introduced to estimate damage ratio in rice crop recently in Indonesia. This technology is one of the ways to estimate rice production quicker, cost-saving and before harvesting time. This study aims to analyze spatio temporal and damage ratio of rice crop using UAV in Indonesia. The study empirically presents the use of UAV (Phantom 2 Vision +) on rice fields to the soil condition and development of management zone map in Bali as an example. The study concludes that the use of UAV allows researchers to pin point characteristics of crop and land in a specific area of a farm. This will then allow researchers to assist farmers in implementing specific and appropriate solutions to production issues. Key words: UAV, rice production, damage ratio

  8. a Uav-Based Low-Cost Stereo Camera System for Archaeological Surveys - Experiences from Doliche (turkey)

    Science.gov (United States)

    Haubeck, K.; Prinz, T.

    2013-08-01

    The use of Unmanned Aerial Vehicles (UAVs) for surveying archaeological sites is becoming more and more common due to their advantages in rapidity of data acquisition, cost-efficiency and flexibility. One possible usage is the documentation and visualization of historic geo-structures and -objects using UAV-attached digital small frame cameras. These monoscopic cameras offer the possibility to obtain close-range aerial photographs, but - under the condition that an accurate nadir-waypoint flight is not possible due to choppy or windy weather conditions - at the same time implicate the problem that two single aerial images not always meet the required overlap to use them for 3D photogrammetric purposes. In this paper, we present an attempt to replace the monoscopic camera with a calibrated low-cost stereo camera that takes two pictures from a slightly different angle at the same time. Our results show that such a geometrically predefined stereo image pair can be used for photogrammetric purposes e.g. the creation of digital terrain models (DTMs) and orthophotos or the 3D extraction of single geo-objects. Because of the limited geometric photobase of the applied stereo camera and the resulting base-height ratio the accuracy of the DTM however directly depends on the UAV flight altitude.

  9. Implementation Of Vision-Based Landing Target Detection For VTOL UAV Using Raspberry Pi

    Directory of Open Access Journals (Sweden)

    Ei Ei Nyein

    2017-04-01

    Full Text Available This paper presents development and implementation of a real-time vision-based landing system for VTOL UAV. We use vision for precise target detection and recognition. A UAV is equipped with the onboard raspberry pi camera to take images and raspberry pi platform to operate the image processing techniques. Today image processing is used for various applications in this paper it is used for landing target extraction. And vision system is also used for take-off and landing function in VTOL UAV. Our landing target design is used as the helipad H shape. Firstly the image is captured to detect the target by the onboard camera. Next the capture image is operated in the onboard processor. Finally the alert sound signal is sent to the remote control RC for landing VTOL UAV. The information obtained from vision system is used to navigate a safe landing. The experimental results from real tests are presented.

  10. Robust UAV Mission Planning

    NARCIS (Netherlands)

    Evers, L.; Dollevoet, T.; Barros, A.I.; Monsuur, H.

    2014-01-01

    Unmanned Aerial Vehicles (UAVs) can provide significant contributions to information gathering in military missions. UAVs can be used to capture both full motion video and still imagery of specific target locations within the area of interest. In order to improve the effectiveness of a

  11. Robust UAV mission planning

    NARCIS (Netherlands)

    Evers, L.; Dollevoet, T.; Barros, A.I.; Monsuur, H.

    2011-01-01

    Unmanned Areal Vehicles (UAVs) can provide significant contributions to information gathering in military missions. UAVs can be used to capture both full motion video and still imagery of specific target locations within the area of interest. In order to improve the effectiveness of a reconnaissance

  12. Robust UAV Mission Planning

    NARCIS (Netherlands)

    Evers, L.; Dollevoet, T; Barros, A.I.; Monsuur, H.

    2011-01-01

    Unmanned Aerial Vehicles (UAVs) can provide significant contributions to information gathering in military missions. UAVs can be used to capture both full motion video and still imagery of specific target locations within the area of interest. In order to improve the effectiveness of a

  13. Robust UAV Mission Planning

    NARCIS (Netherlands)

    L. Evers (Lanah); T.A.B. Dollevoet (Twan); A.I. Barros (Ana); H. Monsuur (Herman)

    2011-01-01

    textabstractUnmanned Areal Vehicles (UAVs) can provide significant contributions to information gathering in military missions. UAVs can be used to capture both full motion video and still imagery of specific target locations within the area of interest. In order to improve the effectiveness of a

  14. UAV-based Natural Hazard Management in High-Alpine Terrain - Case Studies from Austria

    Science.gov (United States)

    Sotier, Bernadette; Adams, Marc; Lechner, Veronika

    2015-04-01

    Unmanned Aerial Vehicles (UAV) have become a standard tool for geodata collection, as they allow conducting on-demand mapping missions in a flexible, cost-effective manner at an unprecedented level of detail. Easy-to-use, high-performance image matching software make it possible to process the collected aerial images to orthophotos and 3D-terrain models. Such up-to-date geodata have proven to be an important asset in natural hazard management: Processes like debris flows, avalanches, landslides, fluvial erosion and rock-fall can be detected and quantified; damages can be documented and evaluated. In the Alps, these processes mostly originate in remote areas, which are difficult and hazardous to access, thus presenting a challenging task for RPAS data collection. In particular, the problems include finding suitable landing and piloting-places, dealing with bad or no GPS-signals and the installation of ground control points (GCP) for georeferencing. At the BFW, RPAS have been used since 2012 to aid natural hazard management of various processes, of which three case studies are presented below. The first case study deals with the results from an attempt to employ UAV-based multi-spectral remote sensing to monitor the state of natural hazard protection forests. Images in the visible and near-infrared (NIR) band were collected using modified low-cost cameras, combined with different optical filters. Several UAV-flights were performed in the 72 ha large study site in 2014, which lies in the Wattental, Tyrol (Austria) between 1700 and 2050 m a.s.l., where the main tree species are stone pine and mountain pine. The matched aerial images were analysed using different UAV-specific vitality indices, evaluating both single- and dual-camera UAV-missions. To calculate the mass balance of a debris flow in the Tyrolean Halltal (Austria), an RPAS flight was conducted in autumn 2012. The extreme alpine environment was challenging for both the mission and the evaluation of the aerial

  15. 3D Modelling of Inaccessible Areas using UAV-based Aerial Photography and Structure from Motion

    Science.gov (United States)

    Obanawa, Hiroyuki; Hayakawa, Yuichi; Gomez, Christopher

    2014-05-01

    In hardly accessible areas, the collection of 3D point-clouds using TLS (Terrestrial Laser Scanner) can be very challenging, while airborne equivalent would not give a correct account of subvertical features and concave geometries like caves. To solve such problem, the authors have experimented an aerial photography based SfM (Structure from Motion) technique on a 'peninsular-rock' surrounded on three sides by the sea at a Pacific coast in eastern Japan. The research was carried out using UAS (Unmanned Aerial System) combined with a commercial small UAV (Unmanned Aerial Vehicle) carrying a compact camera. The UAV is a DJI PHANTOM: the UAV has four rotors (quadcopter), it has a weight of 1000 g, a payload of 400 g and a maximum flight time of 15 minutes. The camera is a GoPro 'HERO3 Black Edition': resolution 12 million pixels; weight 74 g; and 0.5 sec. interval-shot. The 3D model has been constructed by digital photogrammetry using a commercial SfM software, Agisoft PhotoScan Professional®, which can generate sparse and dense point-clouds, from which polygonal models and orthophotographs can be calculated. Using the 'flight-log' and/or GCPs (Ground Control Points), the software can generate digital surface model. As a result, high-resolution aerial orthophotographs and a 3D model were obtained. The results have shown that it was possible to survey the sea cliff and the wave cut-bench, which are unobservable from land side. In details, we could observe the complexity of the sea cliff that is nearly vertical as a whole while slightly overhanging over the thinner base. The wave cut bench is nearly flat and develops extensively at the base of the cliff. Although there are some evidences of small rockfalls at the upper part of the cliff, there is no evidence of very recent activity, because no fallen rock exists on the wave cut bench. This system has several merits: firstly lower cost than the existing measuring methods such as manned-flight survey and aerial laser

  16. Morphological and structural changes at the Merapi lava dome monitored using Unmanned Aerial Vehicles (UAVs)

    Science.gov (United States)

    Darmawan, H.; Walter, T. R.; Brotopuspito, K. S.; Subandriyo, S.; Nandaka, M. A.

    2017-12-01

    Six gas-driven explosions between 2012 and 2014 had changed the morphology and structures of the Merapi lava dome. The explosions mostly occurred during rainfall season and caused NW-SE elongated open fissures that dissected the lava dome. In this study, we conducted UAVs photogrammetry before and after the explosions to investigate the morphological and structural changes and to assess the quality of the UAV photogrammetry. The first UAV photogrammetry was conducted on 26 April 2012. After the explosions, we conducted Terrestrial Laser Scanning (TLS) survey on 18 September 2014 and repeated UAV photogrammetry on 6 October 2015. We applied Structure from Motion (SfM) algorithm to reconstruct 3D SfM point clouds and photomosaics of the 2012 and 2015 UAVs images. Topography changes has been analyzed by calculating height difference between the 2012 and 2015 SfM point clouds, while structural changes has been investigated by visual comparison between the 2012 and 2015 photo mosaics. Moreover, a quality assessment of the results of UAV photogrammetry has been done by comparing the 3D SfM point clouds to TLS dataset. Result shows that the 2012 and 2015 SfM point clouds have 0.19 and 0.57 m difference compared to the TLS point cloud. Furthermore, topography, and structural changes reveal that the 2012-14 explosions were controlled by pre-existing structures. The volume of the 2012-14 explosions is 26.400 ± 1320 m3 DRE. In addition, we find a structurally delineated unstable block at the southern front of the dome which potentially collapses in the future. We concluded that the 2012-14 explosions occurred due to interaction between magma intrusion and rain water and were facilitated by pre-existing structures. The unstable block potentially leads to a rock avalanche hazard. Furthermore, our drone photogrammetry results show very promising and therefore we recommend to use drone for topography mapping in lava dome building volcanoes.

  17. Fotogrametría usando plataforma aérea UAV (Unmanned Aerial Vehicle)

    OpenAIRE

    Santos Clavero, Daniel

    2014-01-01

    El objetivo del proyecto consiste en el uso de un UAV para realizar un levantamiento fotogramétrico en una zona controlada. Debió a la prohibición de AENA de volar fuera de un campo homologado, se ha hecho el levantamiento en la zona del campo de vuelo de radio control ARC Sant cugat. Para este proyecto se ha construido un UAV de cuatro motores (cuadricóptero). Por su maniobrabilidad en espacios pequeños y reducido tamaño. Este cuadricóptero está diseñado para realizar rutas...

  18. D Reconstruction from Uav-Based Hyperspectral Images

    Science.gov (United States)

    Liu, L.; Xu, L.; Peng, J.

    2018-04-01

    Reconstructing the 3D profile from a set of UAV-based images can obtain hyperspectral information, as well as the 3D coordinate of any point on the profile. Our images are captured from the Cubert UHD185 (UHD) hyperspectral camera, which is a new type of high-speed onboard imaging spectrometer. And it can get both hyperspectral image and panchromatic image simultaneously. The panchromatic image have a higher spatial resolution than hyperspectral image, but each hyperspectral image provides considerable information on the spatial spectral distribution of the object. Thus there is an opportunity to derive a high quality 3D point cloud from panchromatic image and considerable spectral information from hyperspectral image. The purpose of this paper is to introduce our processing chain that derives a database which can provide hyperspectral information and 3D position of each point. First, We adopt a free and open-source software, Visual SFM which is based on structure from motion (SFM) algorithm, to recover 3D point cloud from panchromatic image. And then get spectral information of each point from hyperspectral image by a self-developed program written in MATLAB. The production can be used to support further research and applications.

  19. A UAV-based active AirCore system for measurements of greenhouse gases

    Science.gov (United States)

    Andersen, Truls; Scheeren, Bert; Peters, Wouter; Chen, Huilin

    2018-05-01

    We developed and field-tested an unmanned aerial vehicle (UAV)-based active AirCore for atmospheric mole fraction measurements of CO2, CH4, and CO. The system applies an alternative way of using the AirCore technique invented by NOAA. As opposed to the conventional concept of passively sampling air using the atmospheric pressure gradient during descent, the active AirCore collects atmospheric air samples using a pump to pull the air through the tube during flight, which opens up the possibility to spatially sample atmospheric air. The active AirCore system used for this study weighs ˜ 1.1 kg. It consists of a ˜ 50 m long stainless-steel tube, a small stainless-steel tube filled with magnesium perchlorate, a KNF micropump, and a 45 µm orifice working together to form a critical flow of dried atmospheric air through the active AirCore. A cavity ring-down spectrometer (CRDS) was used to analyze the air samples on site not more than 7 min after landing for mole fraction measurements of CO2, CH4, and CO. We flew the active AirCore system on a UAV near the atmospheric measurement station at Lutjewad, located in the northwest of the city of Groningen in the Netherlands. Five consecutive flights took place over a 5 h period on the same morning, from sunrise until noon. We validated the measurements of CO2 and CH4 from the active AirCore against those from the Lutjewad station at 60 m. The results show a good agreement between the measurements from the active AirCore and the atmospheric station (N = 146; R2CO2: 0.97 and R2CH4: 0.94; and mean differences: ΔCO2: 0.18 ppm and ΔCH4: 5.13 ppb). The vertical and horizontal resolution (for CH4) at typical UAV speeds of 1.5 and 2.5 m s-1 were determined to be ±24.7 to 29.3 and ±41.2 to 48.9 m, respectively, depending on the storage time. The collapse of the nocturnal boundary layer and the buildup of the mixed layer were clearly observed with three consecutive vertical profile measurements in the early morning hours. Besides

  20. Unmanned Aerial Vehicle Remote Sensing for Field-Based Crop Phenotyping: Current Status and Perspectives

    Directory of Open Access Journals (Sweden)

    Guijun Yang

    2017-06-01

    Full Text Available Phenotyping plays an important role in crop science research; the accurate and rapid acquisition of phenotypic information of plants or cells in different environments is helpful for exploring the inheritance and expression patterns of the genome to determine the association of genomic and phenotypic information to increase the crop yield. Traditional methods for acquiring crop traits, such as plant height, leaf color, leaf area index (LAI, chlorophyll content, biomass and yield, rely on manual sampling, which is time-consuming and laborious. Unmanned aerial vehicle remote sensing platforms (UAV-RSPs equipped with different sensors have recently become an important approach for fast and non-destructive high throughput phenotyping and have the advantage of flexible and convenient operation, on-demand access to data and high spatial resolution. UAV-RSPs are a powerful tool for studying phenomics and genomics. As the methods and applications for field phenotyping using UAVs to users who willing to derive phenotypic parameters from large fields and tests with the minimum effort on field work and getting highly reliable results are necessary, the current status and perspectives on the topic of UAV-RSPs for field-based phenotyping were reviewed based on the literature survey of crop phenotyping using UAV-RSPs in the Web of Science™ Core Collection database and cases study by NERCITA. The reference for the selection of UAV platforms and remote sensing sensors, the commonly adopted methods and typical applications for analyzing phenotypic traits by UAV-RSPs, and the challenge for crop phenotyping by UAV-RSPs were considered. The review can provide theoretical and technical support to promote the applications of UAV-RSPs for crop phenotyping.

  1. Geomorphic change detection in proglacial areas using repetitive unmanned aerial vehicle (UAV) surveys

    Science.gov (United States)

    Ewertowski, Marek; Evans, David; Roberts, David; Tomczyk, Aleksandra; Ewertowski, Wojciech

    2017-04-01

    Glacial forelands exposed due to the glacier recession are one of the most dynamically transformed landscapes in Polar and mountainous areas. These areas are supposed to be intensively changed by various geomorphological processes related to the glacial retreat and meltwater activity, as well as paraglacial adjustment of topography. This study deals with landscape transformation in an annual time-scale in the foreland of Hørbyebreen and Rieperbreen (Svalbard) and Fjallsjökull and Kviárjökull (Iceland) to assess landscape changes in 2014-2016 period. The main aim of this study is to map and quantify landforms development in detailed spatial scale to provide an insight into geomorphological processes which occurred shortly after the retreat of the ice margin. Low-altitude aerial photographs were taken using small quadcopter equipped with 12 MP camera. Images were acquired at an elevation between 40 and 60 m above the ground level. The images were subsequently processed using structure-from-motion approach to produce orthomosaics ( 3 cm cell size) and digital elevation models (DEMs) with 5-10 cm cell size. Subtracting DEMs from subsequent time periods created DEMs of Differences — which enabled us to calculate the amount of material loss or deposition. Accuracy of the orthophotos and DEMs was improved using ground control points measured with dGPS. Over the 2014-2016 period repetitive UAV-based surveys revealed and quantify changes in landscape including: (1) glacier thinning; (2) ice-cored moraines degradation; (3) development of terminoglacial and supraglacial lakes; (4) debris flow activity. Short-time dynamics of different components showed very high variability over time and space illustrating relative importance of ice backwasting and downwasting as well as glacifluvial processes for studied forelands The research was founded by Polish National Science Centre (project granted by decision number DEC-2011/01/D/ST10/06494).

  2. U.S. Unmanned Aerial Vehicles (UAVS) and Network Centric Warfare (NCW) impacts on combat aviation tactics from Gulf War I through 2007 Iraq

    OpenAIRE

    Oveyik, Kaan.; Kurkcu, Coskun

    2008-01-01

    Approved for public release; distribution is unlimited Unmanned, aerial vehicles (UAVs) are an increasingly important element of many modern militaries. Their success on battlefields in Afghanistan, Iraq, and around the globe has driven demand for a variety of types of unmanned vehicles. Their proven value consists in low risk and low cost, and their capabilities include persistent surveillance, tactical and combat reconnaissance, resilience, and dynamic re-tasking. This research evaluat...

  3. An UAV scheduling and planning method for post-disaster survey

    Science.gov (United States)

    Li, G. Q.; Zhou, X. G.; Yin, J.; Xiao, Q. Y.

    2014-11-01

    Annually, the extreme climate and special geological environments lead to frequent natural disasters, e.g., earthquakes, floods, etc. The disasters often bring serious casualties and enormous economic losses. Post-disaster surveying is very important for disaster relief and assessment. As the Unmanned Aerial Vehicle (UAV) remote sensing with the advantage of high efficiency, high precision, high flexibility, and low cost, it is widely used in emergency surveying in recent years. As the UAVs used in emergency surveying cannot stop and wait for the happening of the disaster, when the disaster happens the UAVs usually are working at everywhere. In order to improve the emergency surveying efficiency, it is needed to track the UAVs and assign the emergency surveying task for each selected UAV. Therefore, a UAV tracking and scheduling method for post-disaster survey is presented in this paper. In this method, Global Positioning System (GPS), and GSM network are used to track the UAVs; an emergency tracking UAV information database is built in advance by registration, the database at least includes the following information, e.g., the ID of the UAVs, the communication number of the UAVs; when catastrophe happens, the real time location of all UAVs in the database will be gotten using emergency tracking method at first, then the traffic cost time for all UAVs to the disaster region will be calculated based on the UAVs' the real time location and the road network using the nearest services analysis algorithm; the disaster region is subdivided to several emergency surveying regions based on DEM, area, and the population distribution map; the emergency surveying regions are assigned to the appropriated UAV according to shortest cost time rule. The UAVs tracking and scheduling prototype is implemented using SQLServer2008, ArcEnginge 10.1 SDK, Visual Studio 2010 C#, Android, SMS Modem, and Google Maps API.

  4. Quantifying Efficacy and Limits of Unmanned Aerial Vehicle (UAV Technology for Weed Seedling Detection as Affected by Sensor Resolution

    Directory of Open Access Journals (Sweden)

    José M. Peña

    2015-03-01

    Full Text Available In order to optimize the application of herbicides in weed-crop systems, accurate and timely weed maps of the crop-field are required. In this context, this investigation quantified the efficacy and limitations of remote images collected with an unmanned aerial vehicle (UAV for early detection of weed seedlings. The ability to discriminate weeds was significantly affected by the imagery spectral (type of camera, spatial (flight altitude and temporal (the date of the study resolutions. The colour-infrared images captured at 40 m and 50 days after sowing (date 2, when plants had 5–6 true leaves, had the highest weed detection accuracy (up to 91%. At this flight altitude, the images captured before date 2 had slightly better results than the images captured later. However, this trend changed in the visible-light images captured at 60 m and higher, which had notably better results on date 3 (57 days after sowing because of the larger size of the weed plants. Our results showed the requirements on spectral and spatial resolutions needed to generate a suitable weed map early in the growing season, as well as the best moment for the UAV image acquisition, with the ultimate objective of applying site-specific weed management operations.

  5. Quantifying efficacy and limits of unmanned aerial vehicle (UAV) technology for weed seedling detection as affected by sensor resolution.

    Science.gov (United States)

    Peña, José M; Torres-Sánchez, Jorge; Serrano-Pérez, Angélica; de Castro, Ana I; López-Granados, Francisca

    2015-03-06

    In order to optimize the application of herbicides in weed-crop systems, accurate and timely weed maps of the crop-field are required. In this context, this investigation quantified the efficacy and limitations of remote images collected with an unmanned aerial vehicle (UAV) for early detection of weed seedlings. The ability to discriminate weeds was significantly affected by the imagery spectral (type of camera), spatial (flight altitude) and temporal (the date of the study) resolutions. The colour-infrared images captured at 40 m and 50 days after sowing (date 2), when plants had 5-6 true leaves, had the highest weed detection accuracy (up to 91%). At this flight altitude, the images captured before date 2 had slightly better results than the images captured later. However, this trend changed in the visible-light images captured at 60 m and higher, which had notably better results on date 3 (57 days after sowing) because of the larger size of the weed plants. Our results showed the requirements on spectral and spatial resolutions needed to generate a suitable weed map early in the growing season, as well as the best moment for the UAV image acquisition, with the ultimate objective of applying site-specific weed management operations.

  6. Comparisons between high-resolution profiles of squared refractive index gradient M2 measured by the Middle and Upper Atmosphere Radar and unmanned aerial vehicles (UAVs during the Shigaraki UAV-Radar Experiment 2015 campaign

    Directory of Open Access Journals (Sweden)

    H. Luce

    2017-03-01

    Full Text Available New comparisons between the square of the generalized potential refractive index gradient M2, estimated from the very high-frequency (VHF Middle and Upper Atmosphere (MU Radar, located at Shigaraki, Japan, and unmanned aerial vehicle (UAV measurements are presented. These comparisons were performed at unprecedented temporal and range resolutions (1–4 min and  ∼  20 m, respectively in the altitude range  ∼  1.27–4.5 km from simultaneous and nearly collocated measurements made during the ShUREX (Shigaraki UAV-Radar Experiment 2015 campaign. Seven consecutive UAV flights made during daytime on 7 June 2015 were used for this purpose. The MU Radar was operated in range imaging mode for improving the range resolution at vertical incidence (typically a few tens of meters. The proportionality of the radar echo power to M2 is reported for the first time at such high time and range resolutions for stratified conditions for which Fresnel scatter or a reflection mechanism is expected. In more complex features obtained for a range of turbulent layers generated by shear instabilities or associated with convective cloud cells, M2 estimated from UAV data does not reproduce observed radar echo power profiles. Proposed interpretations of this discrepancy are presented.

  7. A guidance law for UAV autonomous aerial refueling based on the iterative computation method

    Directory of Open Access Journals (Sweden)

    Luo Delin

    2014-08-01

    Full Text Available The rendezvous and formation problem is a significant part for the unmanned aerial vehicle (UAV autonomous aerial refueling (AAR technique. It can be divided into two major phases: the long-range guidance phase and the formation phase. In this paper, an iterative computation guidance law (ICGL is proposed to compute a series of state variables to get the solution of a control variable for a UAV conducting rendezvous with a tanker in AAR. The proposed method can make the control variable converge to zero when the tanker and the UAV receiver come to a formation flight eventually. For the long-range guidance phase, the ICGL divides it into two sub-phases: the correction sub-phase and the guidance sub-phase. The two sub-phases share the same iterative process. As for the formation phase, a velocity coordinate system is created by which control accelerations are designed to make the speed of the UAV consistent with that of the tanker. The simulation results demonstrate that the proposed ICGL is effective and robust against wind disturbance.

  8. Pengembangan Sistem Navigasi Otomatis Pada UAV (Unmanned Aerial Vehicle dengan GPS(Global Positioning System Waypoint

    Directory of Open Access Journals (Sweden)

    Rahmad Hidayat

    2017-01-01

    Full Text Available UAV adalah salah satu wahana tanpa awak di udara yang mana dapat terbang tanpa pilot, menggunakan gaya aerodinamik untuk menghasilkan gaya angkat (lift, dapat terbang secara autonomous atau dioperasikan dengan radio kontrol. UAV digunakan untuk berbagai keperluan baik di lingkup militer maupun sipil. Pada tugas akhir ini dirancang dan direalisasikan pengembangan sistem navigasi otomatis pada UAV dengan GPS waypoint. Sistem ini menggunakan kontrol manual dan autopilot. Pada mode manual, pengguna secara manual mengendalikan pergerakan pesawat melalui radio kontroler sedangkan pada mode autopilot pesawat dikendalikan oleh mikrokontroler Arduino Mega 2560 yang mengolah data-data sensor IMU (Inertial Measurement Unit yang didalamnya terdapat gyroscope dan accelerometer, GPS dan barometric altimeter sehingga dapat terbang secara otomatis dengan sesuai waypoint GPS yang dimasukkan. Mikrokontroler menerima dan menolah data dari sensor dan menghasilkan keluaran untuk menggerakkan servo aktuator. Pengolahan data dari sensor menggunakan kontrol PID (Proportional Integral Derivative. Pesawat akan terkoneksi dengan ground station melalui perangkat telemetri untuk mengirimkan data penerbangan ke darat. Sistem navigasi ini diharapkan dapat secara tepat mengarahkan pesawat menuju satu titik atau lebih dengan toleransi kesalahan ≤ 30 meter pada ketinggian 30-100 meter. Selain itu pesawat diharapkan dapat terbang dengan radius ± 2 km dari ground station. Hasil dari pengujian dapat dilaksanakan kontrol manual dan otomatis pada UAV melalui 5 channel (aileron, elevator, throttle, rudder dan saklar. Distorsi pada kontrol manual diminimalisir dengan memperbesar faktor pembagi sinyal PWM sebesar 50μs-100μs. Kontrol otomatis dapat menstabilkan sikap pesawat di udara (sudut roll 45° dan sudut pitch 30° Setting Kp 1,2 dan Ki 0,01, setting Kp navigasi GPS 0,2 Ki 0,01 dan Kd 4 dengan sudut roll maksimal 15°.

  9. A hybrid Radio-vision fault tolerant localization for mini UAV flying in swarm

    DEFF Research Database (Denmark)

    Latroch, Maamar; Abdelhafid, Omari; Koivo, Heikki N.

    2013-01-01

    This paper discuss the localization of one Unmanned Aerial Vehicle (UAV) when a failure of its GPS occurs and will propose a new solution based on the information collected by the swarm to localize it. we propose here an architecture for localization of a UAV with GPS signal failure in three...

  10. Energy-Efficient Power Allocation for UAV Cognitive Radio Systems

    KAUST Repository

    Sboui, Lokman

    2018-02-12

    We study the deployment of unmanned aerial vehicles (UAV) based cognitive system in an area covered by the primary network (PN). An UAV shares the spectrum of the PN and aims to maximize its energy efficiency (EE) by optimizing the transmit power. We focus on the case where the UAV simultaneously communicates with the ground receiver (G), under interference limitation, and with another relaying UAV (A), with a minimal required rate. We analytically develop the power allocation framework that maximizes the EE subject to power budget, interference, and minimal rate constraints. In the numerical results, we show that the minimal rate may cause a transmission outage at low power budget values. We also highlighted the existence of optimal altitudes given the UAV location with respect to the different other terminals.

  11. Energy-Efficient Power Allocation for UAV Cognitive Radio Systems

    KAUST Repository

    Sboui, Lokman; Ghazzai, Hakim; Rezki, Zouheir; Alouini, Mohamed-Slim

    2018-01-01

    We study the deployment of unmanned aerial vehicles (UAV) based cognitive system in an area covered by the primary network (PN). An UAV shares the spectrum of the PN and aims to maximize its energy efficiency (EE) by optimizing the transmit power. We focus on the case where the UAV simultaneously communicates with the ground receiver (G), under interference limitation, and with another relaying UAV (A), with a minimal required rate. We analytically develop the power allocation framework that maximizes the EE subject to power budget, interference, and minimal rate constraints. In the numerical results, we show that the minimal rate may cause a transmission outage at low power budget values. We also highlighted the existence of optimal altitudes given the UAV location with respect to the different other terminals.

  12. A debugging method of the Quadrotor UAV based on infrared thermal imaging

    Science.gov (United States)

    Cui, Guangjie; Hao, Qian; Yang, Jianguo; Chen, Lizhi; Hu, Hongkang; Zhang, Lijun

    2018-01-01

    High-performance UAV has been popular and in great need in recent years. The paper introduces a new method in debugging Quadrotor UAVs. Based on the infrared thermal technology and heat transfer theory, a UAV is under debugging above a hot-wire grid which is composed of 14 heated nichrome wires. And the air flow propelled by the rotating rotors has an influence on the temperature distribution of the hot-wire grid. An infrared thermal imager below observes the distribution and gets thermal images of the hot-wire grid. With the assistance of mathematic model and some experiments, the paper discusses the relationship between thermal images and the speed of rotors. By means of getting debugged UAVs into test, the standard information and thermal images can be acquired. The paper demonstrates that comparing to the standard thermal images, a UAV being debugging in the same test can draw some critical data directly or after interpolation. The results are shown in the paper and the advantages are discussed.

  13. Multiple UAV Cooperation for Wildfire Monitoring

    Science.gov (United States)

    Lin, Zhongjie

    Wildfires have been a major factor in the development and management of the world's forest. An accurate assessment of wildfire status is imperative for fire management. This thesis is dedicated to the topic of utilizing multiple unmanned aerial vehicles (UAVs) to cooperatively monitor a large-scale wildfire. This is achieved through wildfire spreading situation estimation based on on-line measurements and wise cooperation strategy to ensure efficiency. First, based on the understanding of the physical characteristics of the wildfire propagation behavior, a wildfire model and a Kalman filter-based method are proposed to estimate the wildfire rate of spread and the fire front contour profile. With the enormous on-line measurements from on-board sensors of UAVs, the proposed method allows a wildfire monitoring mission to benefit from on-line information updating, increased flexibility, and accurate estimation. An independent wildfire simulator is utilized to verify the effectiveness of the proposed method. Second, based on the filter analysis, wildfire spreading situation and vehicle dynamics, the influence of different cooperation strategies of UAVs to the overall mission performance is studied. The multi-UAV cooperation problem is formulated in a distributed network. A consensus-based method is proposed to help address the problem. The optimal cooperation strategy of UAVs is obtained through mathematical analysis. The derived optimal cooperation strategy is then verified in an independent fire simulation environment to verify its effectiveness.

  14. Research on the attitude of small UAV based on MEMS devices

    Science.gov (United States)

    Shi, Xiaojie; Lu, Libin; Jin, Guodong; Tan, Lining

    2017-05-01

    This paper mainly introduces the research principle and implementation method of the small UAV navigation attitude system based on MEMS devices. The Gauss - Newton method based on least squares is used to calibrate the MEMS accelerometer and gyroscope for calibration. Improve the accuracy of the attitude by using the modified complementary filtering to correct the attitude angle error. The experimental data show that the design of the attitude and attitude system in this paper to meet the requirements of small UAV attitude accuracy to achieve a small, low cost.

  15. Human-Interaction Challenges in UAV-Based Autonomous Surveillance

    Science.gov (United States)

    Freed, Michael; Harris, Robert; Shafto, Michael G.

    2004-01-01

    Autonomous UAVs provide a platform for intelligent surveillance in application domains ranging from security and military operations to scientific information gathering and land management. Surveillance tasks are often long duration, requiring that any approach be adaptive to changes in the environment or user needs. We describe a decision- theoretic model of surveillance, appropriate for use on our autonomous helicopter, that provides a basis for optimizing the value of information returned by the UAV. From this approach arise a range of challenges in making this framework practical for use by human operators lacking specialized knowledge of autonomy and mathematics. This paper describes our platform and approach, then describes human-interaction challenges arising from this approach that we have identified and begun to address.

  16. Evaluation of Rgb-Based Vegetation Indices from Uav Imagery to Estimate Forage Yield in Grassland

    Science.gov (United States)

    Lussem, U.; Bolten, A.; Gnyp, M. L.; Jasper, J.; Bareth, G.

    2018-04-01

    Monitoring forage yield throughout the growing season is of key importance to support management decisions on grasslands/pastures. Especially on intensely managed grasslands, where nitrogen fertilizer and/or manure are applied regularly, precision agriculture applications are beneficial to support sustainable, site-specific management decisions on fertilizer treatment, grazing management and yield forecasting to mitigate potential negative impacts. To support these management decisions, timely and accurate information is needed on plant parameters (e.g. forage yield) with a high spatial and temporal resolution. However, in highly heterogeneous plant communities such as grasslands, assessing their in-field variability non-destructively to determine e.g. adequate fertilizer application still remains challenging. Especially biomass/yield estimation, as an important parameter in assessing grassland quality and quantity, is rather laborious. Forage yield (dry or fresh matter) is mostly measured manually with rising plate meters (RPM) or ultrasonic sensors (handheld or mounted on vehicles). Thus the in-field variability cannot be assessed for the entire field or only with potential disturbances. Using unmanned aerial vehicles (UAV) equipped with consumer grade RGB cameras in-field variability can be assessed by computing RGB-based vegetation indices. In this contribution we want to test and evaluate the robustness of RGB-based vegetation indices to estimate dry matter forage yield on a recently established experimental grassland site in Germany. Furthermore, the RGB-based VIs are compared to indices computed from the Yara N-Sensor. The results show a good correlation of forage yield with RGB-based VIs such as the NGRDI with R2 values of 0.62.

  17. Automated UAV-based video exploitation using service oriented architecture framework

    Science.gov (United States)

    Se, Stephen; Nadeau, Christian; Wood, Scott

    2011-05-01

    Airborne surveillance and reconnaissance are essential for successful military missions. Such capabilities are critical for troop protection, situational awareness, mission planning, damage assessment, and others. Unmanned Aerial Vehicles (UAVs) gather huge amounts of video data but it is extremely labour-intensive for operators to analyze hours and hours of received data. At MDA, we have developed a suite of tools that can process the UAV video data automatically, including mosaicking, change detection and 3D reconstruction, which have been integrated within a standard GIS framework. In addition, the mosaicking and 3D reconstruction tools have also been integrated in a Service Oriented Architecture (SOA) framework. The Visualization and Exploitation Workstation (VIEW) integrates 2D and 3D visualization, processing, and analysis capabilities developed for UAV video exploitation. Visualization capabilities are supported through a thick-client Graphical User Interface (GUI), which allows visualization of 2D imagery, video, and 3D models. The GUI interacts with the VIEW server, which provides video mosaicking and 3D reconstruction exploitation services through the SOA framework. The SOA framework allows multiple users to perform video exploitation by running a GUI client on the operator's computer and invoking the video exploitation functionalities residing on the server. This allows the exploitation services to be upgraded easily and allows the intensive video processing to run on powerful workstations. MDA provides UAV services to the Canadian and Australian forces in Afghanistan with the Heron, a Medium Altitude Long Endurance (MALE) UAV system. On-going flight operations service provides important intelligence, surveillance, and reconnaissance information to commanders and front-line soldiers.

  18. Background Registration-Based Adaptive Noise Filtering of LWIR/MWIR Imaging Sensors for UAV Applications

    Directory of Open Access Journals (Sweden)

    Byeong Hak Kim

    2017-12-01

    Full Text Available Unmanned aerial vehicles (UAVs are equipped with optical systems including an infrared (IR camera such as electro-optical IR (EO/IR, target acquisition and designation sights (TADS, or forward looking IR (FLIR. However, images obtained from IR cameras are subject to noise such as dead pixels, lines, and fixed pattern noise. Nonuniformity correction (NUC is a widely employed method to reduce noise in IR images, but it has limitations in removing noise that occurs during operation. Methods have been proposed to overcome the limitations of the NUC method, such as two-point correction (TPC and scene-based NUC (SBNUC. However, these methods still suffer from unfixed pattern noise. In this paper, a background registration-based adaptive noise filtering (BRANF method is proposed to overcome the limitations of conventional methods. The proposed BRANF method utilizes background registration processing and robust principle component analysis (RPCA. In addition, image quality verification methods are proposed that can measure the noise filtering performance quantitatively without ground truth images. Experiments were performed for performance verification with middle wave infrared (MWIR and long wave infrared (LWIR images obtained from practical military optical systems. As a result, it is found that the image quality improvement rate of BRANF is 30% higher than that of conventional NUC.

  19. Background Registration-Based Adaptive Noise Filtering of LWIR/MWIR Imaging Sensors for UAV Applications

    Science.gov (United States)

    Kim, Byeong Hak; Kim, Min Young; Chae, You Seong

    2017-01-01

    Unmanned aerial vehicles (UAVs) are equipped with optical systems including an infrared (IR) camera such as electro-optical IR (EO/IR), target acquisition and designation sights (TADS), or forward looking IR (FLIR). However, images obtained from IR cameras are subject to noise such as dead pixels, lines, and fixed pattern noise. Nonuniformity correction (NUC) is a widely employed method to reduce noise in IR images, but it has limitations in removing noise that occurs during operation. Methods have been proposed to overcome the limitations of the NUC method, such as two-point correction (TPC) and scene-based NUC (SBNUC). However, these methods still suffer from unfixed pattern noise. In this paper, a background registration-based adaptive noise filtering (BRANF) method is proposed to overcome the limitations of conventional methods. The proposed BRANF method utilizes background registration processing and robust principle component analysis (RPCA). In addition, image quality verification methods are proposed that can measure the noise filtering performance quantitatively without ground truth images. Experiments were performed for performance verification with middle wave infrared (MWIR) and long wave infrared (LWIR) images obtained from practical military optical systems. As a result, it is found that the image quality improvement rate of BRANF is 30% higher than that of conventional NUC. PMID:29280970

  20. Background Registration-Based Adaptive Noise Filtering of LWIR/MWIR Imaging Sensors for UAV Applications.

    Science.gov (United States)

    Kim, Byeong Hak; Kim, Min Young; Chae, You Seong

    2017-12-27

    Unmanned aerial vehicles (UAVs) are equipped with optical systems including an infrared (IR) camera such as electro-optical IR (EO/IR), target acquisition and designation sights (TADS), or forward looking IR (FLIR). However, images obtained from IR cameras are subject to noise such as dead pixels, lines, and fixed pattern noise. Nonuniformity correction (NUC) is a widely employed method to reduce noise in IR images, but it has limitations in removing noise that occurs during operation. Methods have been proposed to overcome the limitations of the NUC method, such as two-point correction (TPC) and scene-based NUC (SBNUC). However, these methods still suffer from unfixed pattern noise. In this paper, a background registration-based adaptive noise filtering (BRANF) method is proposed to overcome the limitations of conventional methods. The proposed BRANF method utilizes background registration processing and robust principle component analysis (RPCA). In addition, image quality verification methods are proposed that can measure the noise filtering performance quantitatively without ground truth images. Experiments were performed for performance verification with middle wave infrared (MWIR) and long wave infrared (LWIR) images obtained from practical military optical systems. As a result, it is found that the image quality improvement rate of BRANF is 30% higher than that of conventional NUC.

  1. Differential GNSS and Vision-Based Tracking to Improve Navigation Performance in Cooperative Multi-UAV Systems

    Directory of Open Access Journals (Sweden)

    Amedeo Rodi Vetrella

    2016-12-01

    Full Text Available Autonomous navigation of micro-UAVs is typically based on the integration of low cost Global Navigation Satellite System (GNSS receivers and Micro-Electro-Mechanical Systems (MEMS-based inertial and magnetic sensors to stabilize and control the flight. The resulting navigation performance in terms of position and attitude accuracy may not suffice for other mission needs, such as the ones relevant to fine sensor pointing. In this framework, this paper presents a cooperative UAV navigation algorithm that allows a chief vehicle, equipped with inertial and magnetic sensors, a Global Positioning System (GPS receiver, and a vision system, to improve its navigation performance (in real time or in the post processing phase exploiting formation flying deputy vehicles equipped with GPS receivers. The focus is set on outdoor environments and the key concept is to exploit differential GPS among vehicles and vision-based tracking (DGPS/Vision to build a virtual additional navigation sensor whose information is then integrated in a sensor fusion algorithm based on an Extended Kalman Filter. The developed concept and processing architecture are described, with a focus on DGPS/Vision attitude determination algorithm. Performance assessment is carried out on the basis of both numerical simulations and flight tests. In the latter ones, navigation estimates derived from the DGPS/Vision approach are compared with those provided by the onboard autopilot system of a customized quadrotor. The analysis shows the potential of the developed approach, mainly deriving from the possibility to exploit magnetic- and inertial-independent accurate attitude information.

  2. Maritime-Based UAVs: A Key to Success for the Joint Force Commander

    Science.gov (United States)

    2015-05-18

    Arabian Peninsula AOR Area of Responsibility BOO Base of Operations BAMS Broad Area Maritime Surveillance CJCS Chairman of the Joint Chiefs of Staff...Afghanistan and Pakistan.”xx But using these UAVs requires months of diplomatic planning and preparation to negotiate a base of operations ( BOO

  3. High spatial resolution mapping of folds and fractures using Unmanned Aerial Vehicle (UAV) photogrammetry

    Science.gov (United States)

    Cruden, A. R.; Vollgger, S.

    2016-12-01

    The emerging capability of UAV photogrammetry combines a simple and cost-effective method to acquire digital aerial images with advanced computer vision algorithms that compute spatial datasets from a sequence of overlapping digital photographs from various viewpoints. Depending on flight altitude and camera setup, sub-centimeter spatial resolution orthophotographs and textured dense point clouds can be achieved. Orientation data can be collected for detailed structural analysis by digitally mapping such high-resolution spatial datasets in a fraction of time and with higher fidelity compared to traditional mapping techniques. Here we describe a photogrammetric workflow applied to a structural study of folds and fractures within alternating layers of sandstone and mudstone at a coastal outcrop in SE Australia. We surveyed this location using a downward looking digital camera mounted on commercially available multi-rotor UAV that autonomously followed waypoints at a set altitude and speed to ensure sufficient image overlap, minimum motion blur and an appropriate resolution. The use of surveyed ground control points allowed us to produce a geo-referenced 3D point cloud and an orthophotograph from hundreds of digital images at a spatial resolution automatically extracted from these high-resolution datasets using open-source software. This resulted in an extensive and statistically relevant orientation dataset that was used to 1) interpret the progressive development of folds and faults in the region, and 2) to generate a 3D structural model that underlines the complex internal structure of the outcrop and quantifies spatial variations in fold geometries. Overall, our work highlights how UAV photogrammetry can contribute to new insights in structural analysis.

  4. Automatic Fault Recognition of Photovoltaic Modules Based on Statistical Analysis of Uav Thermography

    Science.gov (United States)

    Kim, D.; Youn, J.; Kim, C.

    2017-08-01

    As a malfunctioning PV (Photovoltaic) cell has a higher temperature than adjacent normal cells, we can detect it easily with a thermal infrared sensor. However, it will be a time-consuming way to inspect large-scale PV power plants by a hand-held thermal infrared sensor. This paper presents an algorithm for automatically detecting defective PV panels using images captured with a thermal imaging camera from an UAV (unmanned aerial vehicle). The proposed algorithm uses statistical analysis of thermal intensity (surface temperature) characteristics of each PV module to verify the mean intensity and standard deviation of each panel as parameters for fault diagnosis. One of the characteristics of thermal infrared imaging is that the larger the distance between sensor and target, the lower the measured temperature of the object. Consequently, a global detection rule using the mean intensity of all panels in the fault detection algorithm is not applicable. Therefore, a local detection rule based on the mean intensity and standard deviation range was developed to detect defective PV modules from individual array automatically. The performance of the proposed algorithm was tested on three sample images; this verified a detection accuracy of defective panels of 97 % or higher. In addition, as the proposed algorithm can adjust the range of threshold values for judging malfunction at the array level, the local detection rule is considered better suited for highly sensitive fault detection compared to a global detection rule.

  5. AUTOMATIC FAULT RECOGNITION OF PHOTOVOLTAIC MODULES BASED ON STATISTICAL ANALYSIS OF UAV THERMOGRAPHY

    Directory of Open Access Journals (Sweden)

    D. Kim

    2017-08-01

    Full Text Available As a malfunctioning PV (Photovoltaic cell has a higher temperature than adjacent normal cells, we can detect it easily with a thermal infrared sensor. However, it will be a time-consuming way to inspect large-scale PV power plants by a hand-held thermal infrared sensor. This paper presents an algorithm for automatically detecting defective PV panels using images captured with a thermal imaging camera from an UAV (unmanned aerial vehicle. The proposed algorithm uses statistical analysis of thermal intensity (surface temperature characteristics of each PV module to verify the mean intensity and standard deviation of each panel as parameters for fault diagnosis. One of the characteristics of thermal infrared imaging is that the larger the distance between sensor and target, the lower the measured temperature of the object. Consequently, a global detection rule using the mean intensity of all panels in the fault detection algorithm is not applicable. Therefore, a local detection rule based on the mean intensity and standard deviation range was developed to detect defective PV modules from individual array automatically. The performance of the proposed algorithm was tested on three sample images; this verified a detection accuracy of defective panels of 97 % or higher. In addition, as the proposed algorithm can adjust the range of threshold values for judging malfunction at the array level, the local detection rule is considered better suited for highly sensitive fault detection compared to a global detection rule.

  6. THE PERFORMANCE ANALYSIS OF A UAV BASED MOBILE MAPPING SYSTEM PLATFORM

    Directory of Open Access Journals (Sweden)

    M. L. Tsai

    2013-08-01

    Full Text Available To facilitate applications such as environment detection or disaster monitoring, the development of rapid low cost systems for collecting near real-time spatial information is very critical. Rapid spatial information collection has become an emerging trend for remote sensing and mapping applications. This study develops a Direct Georeferencing (DG based fixed-wing Unmanned Aerial Vehicle (UAV photogrammetric platform where an Inertial Navigation System (INS/Global Positioning System (GPS integrated Positioning and Orientation System (POS system is implemented to provide the DG capability of the platform. The performance verification indicates that the proposed platform can capture aerial images successfully. A flight test is performed to verify the positioning accuracy in DG mode without using Ground Control Points (GCP. The preliminary results illustrate that horizontal DG positioning accuracies in the x and y axes are around 5 m with 300 m flight height. The positioning accuracy in the z axis is less than 10 m. Such accuracy is good for near real-time disaster relief. The DG ready function of proposed platform guarantees mapping and positioning capability even in GCP free environments, which is very important for rapid urgent response for disaster relief. Generally speaking, the data processing time for the DG module, including POS solution generalization, interpolation, Exterior Orientation Parameters (EOP generation, and feature point measurements, is less than one hour.

  7. The Performance Analysis of a Uav Based Mobile Mapping System Platform

    Science.gov (United States)

    Tsai, M. L.; Chiang, K. W.; Lo, C. F.; Ch, C. H.

    2013-08-01

    To facilitate applications such as environment detection or disaster monitoring, the development of rapid low cost systems for collecting near real-time spatial information is very critical. Rapid spatial information collection has become an emerging trend for remote sensing and mapping applications. This study develops a Direct Georeferencing (DG) based fixed-wing Unmanned Aerial Vehicle (UAV) photogrammetric platform where an Inertial Navigation System (INS)/Global Positioning System (GPS) integrated Positioning and Orientation System (POS) system is implemented to provide the DG capability of the platform. The performance verification indicates that the proposed platform can capture aerial images successfully. A flight test is performed to verify the positioning accuracy in DG mode without using Ground Control Points (GCP). The preliminary results illustrate that horizontal DG positioning accuracies in the x and y axes are around 5 m with 300 m flight height. The positioning accuracy in the z axis is less than 10 m. Such accuracy is good for near real-time disaster relief. The DG ready function of proposed platform guarantees mapping and positioning capability even in GCP free environments, which is very important for rapid urgent response for disaster relief. Generally speaking, the data processing time for the DG module, including POS solution generalization, interpolation, Exterior Orientation Parameters (EOP) generation, and feature point measurements, is less than one hour.

  8. UAV-based detection and spatial analyses of periglacial landforms on Demay Point (King George Island, South Shetland Islands, Antarctica)

    Science.gov (United States)

    Dąbski, Maciej; Zmarz, Anna; Pabjanek, Piotr; Korczak-Abshire, Małgorzata; Karsznia, Izabela; Chwedorzewska, Katarzyna J.

    2017-08-01

    High-resolution aerial images allow detailed analyses of periglacial landforms, which is of particular importance in light of climate change and resulting changes in active layer thickness. The aim of this study is to show possibilities of using UAV-based photography to perform spatial analysis of periglacial landforms on the Demay Point peninsula, King George Island, and hence to supplement previous geomorphological studies of the South Shetland Islands. Photogrammetric flights were performed using a PW-ZOOM fixed-winged unmanned aircraft vehicle. Digital elevation models (DEM) and maps of slope and contour lines were prepared in ESRI ArcGIS 10.3 with the Spatial Analyst extension, and three-dimensional visualizations in ESRI ArcScene 10.3 software. Careful interpretation of orthophoto and DEM, allowed us to vectorize polygons of landforms, such as (i) solifluction landforms (solifluction sheets, tongues, and lobes); (ii) scarps, taluses, and a protalus rampart; (iii) patterned ground (hummocks, sorted circles, stripes, nets and labyrinths, and nonsorted nets and stripes); (iv) coastal landforms (cliffs and beaches); (v) landslides and mud flows; and (vi) stone fields and bedrock outcrops. We conclude that geomorphological studies based on commonly accessible aerial and satellite images can underestimate the spatial extent of periglacial landforms and result in incomplete inventories. The PW-ZOOM UAV is well suited to gather detailed geomorphological data and can be used in spatial analysis of periglacial landforms in the Western Antarctic Peninsula region.

  9. Design of UAVs-Based 3D Antenna Arrays for a Maximum Performance in Terms of Directivity and SLL

    Directory of Open Access Journals (Sweden)

    Jesus Garza

    2016-01-01

    Full Text Available This paper presents a design of UAVs-based 3D antenna arrays for a maximum performance in terms of directivity and side lobe level (SLL. This paper illustrates how to model the UAVs formation flight using 3D nonuniform antenna arrays. This design of 3D antenna arrays considers the optimization of the positions of the antenna elements to model the UAVs formation flight. In this case, a disk patch antenna is chosen to be used as element in each UAV. The disk patch antenna is formulated by the well-known cavity model. The synthesis process is carried out by the method of Differential Evolution for Multiobjective Optimization (DEMO. Furthermore, a comparison of the performance of 3D nonuniform antenna arrays is provided with respect to the most conventional arrays (circular, planar, linear, and the cubic for UAVs formation flight.

  10. Vehicle Based Vector Sensor

    Science.gov (United States)

    2015-09-28

    buoyant underwater vehicle with an interior space in which a length of said underwater vehicle is equal to one tenth of the acoustic wavelength...underwater vehicle with an interior space in which a length of said underwater vehicle is equal to one tenth of the acoustic wavelength; an...unmanned underwater vehicle that can function as an acoustic vector sensor. (2) Description of the Prior Art [0004] It is known that a propagating

  11. Prototyping a GNSS-Based Passive Radar for UAVs: An Instrument to Classify the Water Content Feature of Lands

    Directory of Open Access Journals (Sweden)

    Micaela Troglia Gamba

    2015-11-01

    Full Text Available Global Navigation Satellite Systems (GNSS broadcast signals for positioning and navigation, which can be also employed for remote sensing applications. Indeed, the satellites of any GNSS can be seen as synchronized sources of electromagnetic radiation, and specific processing of the signals reflected back from the ground can be used to estimate the geophysical properties of the Earth’s surface. Several experiments have successfully demonstrated GNSS-reflectometry (GNSS-R, whereas new applications are continuously emerging and are presently under development, either from static or dynamic platforms. GNSS-R can be implemented at a low cost, primarily if small devices are mounted on-board unmanned aerial vehicles (UAVs, which today can be equipped with several types of sensors for environmental monitoring. So far, many instruments for GNSS-R have followed the GNSS bistatic radar architecture and consisted of custom GNSS receivers, often requiring a personal computer and bulky systems to store large amounts of data. This paper presents the development of a GNSS-based sensor for UAVs and small manned aircraft, used to classify lands according to their soil water content. The paper provides details on the design of the major hardware and software components, as well as the description of the results obtained through field tests.

  12. UAV Inspection of Electrical Transmission Infrastructure with Path Conformance Autonomy and Lidar-Based Geofences NASA Report on UTM Reference Mission Flights at Southern Company Flights November 2016

    Science.gov (United States)

    Moore, Andrew J.; Schubert, Matthew; Rymer, Nicholas; Balachandran, Swee; Consiglio, Maria; Munoz, Cesar; Smith, Joshua; Lewis, Dexter; Schneider, Paul

    2017-01-01

    Flights at low altitudes in close proximity to electrical transmission infrastructure present serious navigational challenges: GPS and radio communication quality is variable and yet tight position control is needed to measure defects while avoiding collisions with ground structures. To advance unmanned aerial vehicle (UAV) navigation technology while accomplishing a task with economic and societal benefit, a high voltage electrical infrastructure inspection reference mission was designed. An integrated air-ground platform was developed for this mission and tested in two days of experimental flights to determine whether navigational augmentation was needed to successfully conduct a controlled inspection experiment. The airborne component of the platform was a multirotor UAV built from commercial off-the-shelf hardware and software, and the ground component was a commercial laptop running open source software. A compact ultraviolet sensor mounted on the UAV can locate 'hot spots' (potential failure points in the electric grid), so long as the UAV flight path adequately samples the airspace near the power grid structures. To improve navigation, the platform was supplemented with two navigation technologies: lidar-to-polyhedron preflight processing for obstacle demarcation and inspection distance planning, and trajectory management software to enforce inspection standoff distance. Both navigation technologies were essential to obtaining useful results from the hot spot sensor in this obstacle-rich, low-altitude airspace. Because the electrical grid extends into crowded airspaces, the UAV position was tracked with NASA unmanned aerial system traffic management (UTM) technology. The following results were obtained: (1) Inspection of high-voltage electrical transmission infrastructure to locate 'hot spots' of ultraviolet emission requires navigation methods that are not broadly available and are not needed at higher altitude flights above ground structures. (2) The

  13. Experimental and rendering-based investigation of laser radar cross sections of small unmanned aerial vehicles

    Science.gov (United States)

    Laurenzis, Martin; Bacher, Emmanuel; Christnacher, Frank

    2017-12-01

    Laser imaging systems are prominent candidates for detection and tracking of small unmanned aerial vehicles (UAVs) in current and future security scenarios. Laser reflection characteristics for laser imaging (e.g., laser gated viewing) of small UAVs are investigated to determine their laser radar cross section (LRCS) by analyzing the intensity distribution of laser reflection in high resolution images. For the first time, LRCSs are determined in a combined experimental and computational approaches by high resolution laser gated viewing and three-dimensional rendering. An optimized simple surface model is calculated taking into account diffuse and specular reflectance properties based on the Oren-Nayar and the Cook-Torrance reflectance models, respectively.

  14. UAV BASED BRDF-MEASUREMENTS OF AGRICULTURAL SURFACES WITH PFIFFIKUS

    Directory of Open Access Journals (Sweden)

    G. J. Grenzdörffer

    2012-09-01

    Full Text Available BRDF is a common problem in remote sensing and also in oblique photogrammetry. Common approaches of BRDF-measurement with a field goniometer are costly and rather cumbersome. UAVs may offer an interesting alternative by using a special flight pattern of oblique and converging images. The main part of this paper is the description of a photogrammetric workflow in order to determine the anisotropic reflection properties of a given surface. Due to the relatively low flying heights standard procedures from close range photogrammetry were adopted for outdoor usage. The photogrammetric processing delivered automatic and highly accurate orientation information with the aid of coded targets. The interior orientation of the consumer grade camera is more or less stable. The radiometrically corrected oblique images are converted into ortho photos. The azimuth and elevation angle of every point may then be computed. The calculated anisotropy of a winter wheat plot is shown. A system four diagonally-looking cameras (Four Vision and an additional nadir looking camera is under development. The multi camera system especially designed for a Micro- UAV with a payload of min 1 kg. The system is composed of five industrial digital frame cameras (1.3 Mpix CCD-chips, 15 fp/s with fixed lenses. Also special problems with the construction of a light weight housing of the multi camera solution are covered in the paper.

  15. Characterization of UAV Performance and Development of a Formation Flight Controller for Multiple Small UAVS

    National Research Council Canada - National Science Library

    McCarthy, Patrick A

    2006-01-01

    ... (UAV). One area of particular interest is using multiple small UAVs cooperatively to improve mission efficiency, as well as perform missions that couldn't be performed using vehicles independently...

  16. Reproducibility of crop surface maps extracted from Unmanned Aerial Vehicle (UAV) derived digital surface maps

    KAUST Repository

    Parkes, Stephen

    2016-10-25

    Crop height measured from UAVs fitted with commercially available RGB cameras provide an affordable alternative to retrieve field scale high resolution estimates. The study presents an assessment of between flight reproducibility of Crop Surface Maps (CSM) extracted from Digital Surface Maps (DSM) generated by Structure from Motion (SfM) algorithms. Flights were conducted over a centre pivot irrigation system covered with an alfalfa crop. An important step in calculating the absolute crop height from the UAV derived DSM is determining the height of the underlying terrain. Here we use automatic thresholding techniques applied to RGB vegetation index maps to classify vegetated and soil pixels. From interpolation of classified soil pixels, a terrain map is calculated and subtracted from the DSM. The influence of three different thresholding techniques on CSMs are investigated. Median Alfalfa crop heights determined with the different thresholding methods varied from 18cm for K means thresholding to 13cm for Otsu thresholding methods. Otsu thresholding also gave the smallest range of crop heights and K means thresholding the largest. Reproducibility of median crop heights between flight surveys was 4-6cm for all thresholding techniques. For the flight conducted later in the afternoon shadowing caused soil pixels to be classified as vegetation in key locations around the domain, leading to lower crop height estimates. The range of crop heights was similar for both flights using K means thresholding (35-36cm), local minimum thresholding depended on whether raw or normalised RGB intensities were used to calculate vegetation indices (30-35cm), while Otsu thresholding had a smaller range of heights and varied most between flights (26-30cm). This study showed that crop heights from multiple survey flights are comparable, however, they were dependent on the thresholding method applied to classify soil pixels and the time of day the flight was conducted.

  17. Reproducibility of crop surface maps extracted from Unmanned Aerial Vehicle (UAV) derived digital surface maps

    KAUST Repository

    Parkes, Stephen; McCabe, Matthew; Al-Mashhawari, Samir K.; Rosas, Jorge

    2016-01-01

    Crop height measured from UAVs fitted with commercially available RGB cameras provide an affordable alternative to retrieve field scale high resolution estimates. The study presents an assessment of between flight reproducibility of Crop Surface Maps (CSM) extracted from Digital Surface Maps (DSM) generated by Structure from Motion (SfM) algorithms. Flights were conducted over a centre pivot irrigation system covered with an alfalfa crop. An important step in calculating the absolute crop height from the UAV derived DSM is determining the height of the underlying terrain. Here we use automatic thresholding techniques applied to RGB vegetation index maps to classify vegetated and soil pixels. From interpolation of classified soil pixels, a terrain map is calculated and subtracted from the DSM. The influence of three different thresholding techniques on CSMs are investigated. Median Alfalfa crop heights determined with the different thresholding methods varied from 18cm for K means thresholding to 13cm for Otsu thresholding methods. Otsu thresholding also gave the smallest range of crop heights and K means thresholding the largest. Reproducibility of median crop heights between flight surveys was 4-6cm for all thresholding techniques. For the flight conducted later in the afternoon shadowing caused soil pixels to be classified as vegetation in key locations around the domain, leading to lower crop height estimates. The range of crop heights was similar for both flights using K means thresholding (35-36cm), local minimum thresholding depended on whether raw or normalised RGB intensities were used to calculate vegetation indices (30-35cm), while Otsu thresholding had a smaller range of heights and varied most between flights (26-30cm). This study showed that crop heights from multiple survey flights are comparable, however, they were dependent on the thresholding method applied to classify soil pixels and the time of day the flight was conducted.

  18. Bridge Crack Detection Using Multi-Rotary Uav and Object-Base Image Analysis

    Science.gov (United States)

    Rau, J. Y.; Hsiao, K. W.; Jhan, J. P.; Wang, S. H.; Fang, W. C.; Wang, J. L.

    2017-08-01

    Bridge is an important infrastructure for human life. Thus, the bridge safety monitoring and maintaining is an important issue to the government. Conventionally, bridge inspection were conducted by human in-situ visual examination. This procedure sometimes require under bridge inspection vehicle or climbing under the bridge personally. Thus, its cost and risk is high as well as labor intensive and time consuming. Particularly, its documentation procedure is subjective without 3D spatial information. In order cope with these challenges, this paper propose the use of a multi-rotary UAV that equipped with a SONY A7r2 high resolution digital camera, 50 mm fixed focus length lens, 135 degrees up-down rotating gimbal. The target bridge contains three spans with a total of 60 meters long, 20 meters width and 8 meters height above the water level. In the end, we took about 10,000 images, but some of them were acquired by hand held method taken on the ground using a pole with 2-8 meters long. Those images were processed by Agisoft PhotoscanPro to obtain exterior and interior orientation parameters. A local coordinate system was defined by using 12 ground control points measured by a total station. After triangulation and camera self-calibration, the RMS of control points is less than 3 cm. A 3D CAD model that describe the bridge surface geometry was manually measured by PhotoscanPro. They were composed of planar polygons and will be used for searching related UAV images. Additionally, a photorealistic 3D model can be produced for 3D visualization. In order to detect cracks on the bridge surface, we utilize object-based image analysis (OBIA) technique to segment the image into objects. Later, we derive several object features, such as density, area/bounding box ratio, length/width ratio, length, etc. Then, we can setup a classification rule set to distinguish cracks. Further, we apply semi-global-matching (SGM) to obtain 3D crack information and based on image scale we

  19. BRIDGE CRACK DETECTION USING MULTI-ROTARY UAV AND OBJECT-BASE IMAGE ANALYSIS

    Directory of Open Access Journals (Sweden)

    J. Y. Rau

    2017-08-01

    Full Text Available Bridge is an important infrastructure for human life. Thus, the bridge safety monitoring and maintaining is an important issue to the government. Conventionally, bridge inspection were conducted by human in-situ visual examination. This procedure sometimes require under bridge inspection vehicle or climbing under the bridge personally. Thus, its cost and risk is high as well as labor intensive and time consuming. Particularly, its documentation procedure is subjective without 3D spatial information. In order cope with these challenges, this paper propose the use of a multi-rotary UAV that equipped with a SONY A7r2 high resolution digital camera, 50 mm fixed focus length lens, 135 degrees up-down rotating gimbal. The target bridge contains three spans with a total of 60 meters long, 20 meters width and 8 meters height above the water level. In the end, we took about 10,000 images, but some of them were acquired by hand held method taken on the ground using a pole with 2–8 meters long. Those images were processed by Agisoft PhotoscanPro to obtain exterior and interior orientation parameters. A local coordinate system was defined by using 12 ground control points measured by a total station. After triangulation and camera self-calibration, the RMS of control points is less than 3 cm. A 3D CAD model that describe the bridge surface geometry was manually measured by PhotoscanPro. They were composed of planar polygons and will be used for searching related UAV images. Additionally, a photorealistic 3D model can be produced for 3D visualization. In order to detect cracks on the bridge surface, we utilize object-based image analysis (OBIA technique to segment the image into objects. Later, we derive several object features, such as density, area/bounding box ratio, length/width ratio, length, etc. Then, we can setup a classification rule set to distinguish cracks. Further, we apply semi-global-matching (SGM to obtain 3D crack information and based

  20. NPP post-accident monitoring system based on unmanned aircraft vehicle:concept, design principles

    International Nuclear Information System (INIS)

    Sachenko, A.A.; Kochan, V.V.; Kharchenko, V.S.; Yanovskij, M.Eh.; Yastrebenetskij, M.A.; Fesenko, G.V.

    2016-01-01

    The paper presents a concept of designing the post-accident system for monitoring the equipment and territory of nuclear power plant after a severe accident based on unmanned aircraft vehicle (UAVs). Wired power and communications networks are found out as the most vulnerable ones during the accident monitoring, and informativity, reliability and veracity are recognized as system basic parameters. It is proposed to equip measurement and control modules with backup wireless communication channels and deploy the repeaters network based on UAVs to ensure the informativity. Modules possess the backup power battery, and repeaters appear in the appropriate places after the accident to provide the survivability. Moreover, an optimization of UAVs' location is proposed according to the minimum energy consumption criterion. To ensure the veracity, it is expected to design the noise-immune protocol for message exchange and archiving and self-diagnostics of all system components

  1. A UAV-based active AirCore system for measurements of greenhouse gases

    Directory of Open Access Journals (Sweden)

    T. Andersen

    2018-05-01

    Full Text Available We developed and field-tested an unmanned aerial vehicle (UAV-based active AirCore for atmospheric mole fraction measurements of CO2, CH4, and CO. The system applies an alternative way of using the AirCore technique invented by NOAA. As opposed to the conventional concept of passively sampling air using the atmospheric pressure gradient during descent, the active AirCore collects atmospheric air samples using a pump to pull the air through the tube during flight, which opens up the possibility to spatially sample atmospheric air. The active AirCore system used for this study weighs ∼ 1.1 kg. It consists of a ∼ 50 m long stainless-steel tube, a small stainless-steel tube filled with magnesium perchlorate, a KNF micropump, and a 45 µm orifice working together to form a critical flow of dried atmospheric air through the active AirCore. A cavity ring-down spectrometer (CRDS was used to analyze the air samples on site not more than 7 min after landing for mole fraction measurements of CO2, CH4, and CO. We flew the active AirCore system on a UAV near the atmospheric measurement station at Lutjewad, located in the northwest of the city of Groningen in the Netherlands. Five consecutive flights took place over a 5 h period on the same morning, from sunrise until noon. We validated the measurements of CO2 and CH4 from the active AirCore against those from the Lutjewad station at 60 m. The results show a good agreement between the measurements from the active AirCore and the atmospheric station (N  =  146; R2CO2: 0.97 and R2CH4: 0.94; and mean differences: ΔCO2: 0.18 ppm and ΔCH4: 5.13 ppb. The vertical and horizontal resolution (for CH4 at typical UAV speeds of 1.5 and 2.5 m s−1 were determined to be ±24.7 to 29.3 and ±41.2 to 48.9 m, respectively, depending on the storage time. The collapse of the nocturnal boundary layer and the buildup of the mixed layer were clearly observed with three consecutive vertical

  2. A survey of hybrid Unmanned Aerial Vehicles

    Science.gov (United States)

    Saeed, Adnan S.; Younes, Ahmad Bani; Cai, Chenxiao; Cai, Guowei

    2018-04-01

    This article presents a comprehensive overview on the recent advances of miniature hybrid Unmanned Aerial Vehicles (UAVs). For now, two conventional types, i.e., fixed-wing UAV and Vertical Takeoff and Landing (VTOL) UAV, dominate the miniature UAVs. Each type has its own inherent limitations on flexibility, payload, flight range, cruising speed, takeoff and landing requirements and endurance. Enhanced popularity and interest are recently gained by the newer type, named hybrid UAV, that integrates the beneficial features of both conventional ones. In this survey paper, a systematic categorization method for the hybrid UAV's platform designs is introduced, first presenting the technical features and representative examples. Next, the hybrid UAV's flight dynamics model and flight control strategies are explained addressing several representative modeling and control work. In addition, key observations, existing challenges and conclusive remarks based on the conducted review are discussed accordingly.

  3. A new framework for UAV-based remote sensing data processing and its application in almond water stress quantification

    Science.gov (United States)

    With the rapid development of small imaging sensors and unmanned aerial vehicles (UAVs), remote sensing is undergoing a revolution with greatly increased spatial and temporal resolutions. While more relevant detail becomes available, it is a challenge to analyze the large number of images to extract...

  4. Optimal trajectory planning for a UAV glider using atmospheric thermals

    Science.gov (United States)

    Kagabo, Wilson B.

    An Unmanned Aerial Vehicle Glider (UAV glider) uses atmospheric energy in its different forms to remain aloft for extended flight durations. This UAV glider's aim is to extract atmospheric thermal energy and use it to supplement its battery energy usage and increase the mission period. Given an infrared camera identified atmospheric thermal of known strength and location; current wind speed and direction; current battery level; altitude and location of the UAV glider; and estimating the expected altitude gain from the thermal, is it possible to make an energy-efficient based motivation to fly to an atmospheric thermal so as to achieve UAV glider extended flight time? For this work, an infrared thermal camera aboard the UAV glider takes continuous forward-looking ground images of "hot spots". Through image processing a candidate atmospheric thermal strength and location is estimated. An Intelligent Decision Model incorporates this information with the current UAV glider status and weather conditions to provide an energy-based recommendation to modify the flight path of the UAV glider. Research, development, and simulation of the Intelligent Decision Model is the primary focus of this work. Three models are developed: (1) Battery Usage Model, (2) Intelligent Decision Model, and (3) Altitude Gain Model. The Battery Usage Model comes from the candidate flight trajectory, wind speed & direction and aircraft dynamic model. Intelligent Decision Model uses a fuzzy logic based approach. The Altitude Gain Model requires the strength and size of the thermal and is found a priori.

  5. Synthesis of Control Algorithm for a Leaderheaded UAVs Group

    Directory of Open Access Journals (Sweden)

    I. O. Samodov

    2015-01-01

    Full Text Available Currently, a defense sphere uses unmanned aerial vehicles (UAVs. UAVs have several advantages over manned aircrafts such as small size, reduced combat losses of personnel, etc. In addition, in threat environment, it is necessary to arrange both bringing together distant from each other UAVs in a group and their undetected in radar fields compact flying in terms of the joint flight security.However, the task to control a UAVs group is much more difficult than to control a single UAV, since it is necessary not only to control the aircraft, but also take into account the relative position of objects in the group.To solve this problem two ways are possible: using a network exchange between members of the group on the "everyone with everyone" principle and organizing the leader-headed flight.The aim of the article is to develop and study a possible option of the UAVs group control with arranging a leader-headed flight to provide the undetected in radar fields compact flying in terms of the joint flight security.The article develops a universal algorithm to control leader-headed group, based on a new modification of the statistical theory of optimal control. It studies effectiveness of the algorithm. While solving this task, a flight of seven UAVs was simulated in the horizontal plane in a rectangular coordinate system. Control time, linear errors of desired alignment of UAV, and control errors with respect to angular coordinates are used as measures of merit.The study results of the algorithm to control a leader-headed group of UAVs confirmed that it is possible to fulfill tasks of flying free-of-collision group of UAVs with essentially reduced computational costs.

  6. A case study of a precision fertilizer application task generation for wheat based on classified hyperspectral data from UAV combined with farm history data

    Science.gov (United States)

    Kaivosoja, Jere; Pesonen, Liisa; Kleemola, Jouko; Pölönen, Ilkka; Salo, Heikki; Honkavaara, Eija; Saari, Heikki; Mäkynen, Jussi; Rajala, Ari

    2013-10-01

    Different remote sensing methods for detecting variations in agricultural fields have been studied in last two decades. There are already existing systems for planning and applying e.g. nitrogen fertilizers to the cereal crop fields. However, there are disadvantages such as high costs, adaptability, reliability, resolution aspects and final products dissemination. With an unmanned aerial vehicle (UAV) based airborne methods, data collection can be performed cost-efficiently with desired spatial and temporal resolutions, below clouds and under diverse weather conditions. A new Fabry-Perot interferometer based hyperspectral imaging technology implemented in an UAV has been introduced. In this research, we studied the possibilities of exploiting classified raster maps from hyperspectral data to produce a work task for a precision fertilizer application. The UAV flight campaign was performed in a wheat test field in Finland in the summer of 2012. Based on the campaign, we have classified raster maps estimating the biomass and nitrogen contents at approximately stage 34 in the Zadoks scale. We combined the classified maps with farm history data such as previous yield maps. Then we generalized the combined results and transformed it to a vectorized zonal task map suitable for farm machinery. We present the selected weights for each dataset in the processing chain and the resultant variable rate application (VRA) task. The additional fertilization according to the generated task was shown to be beneficial for the amount of yield. However, our study is indicating that there are still many uncertainties within the process chain.

  7. Research for new UAV capabilities

    Energy Technology Data Exchange (ETDEWEB)

    Canavan, G.H.; Leadabrand, R.

    1996-07-01

    This paper discusses research for new Unmanned Aerial Vehicles (UAV) capabilities. Findings indicate that UAV performance could be greatly enhanced by modest research. Improved sensors and communications enhance near term cost effectiveness. Improved engines, platforms, and stealth improve long term effectiveness.

  8. A Simple Aerial Photogrammetric Mapping System Overview and Image Acquisition Using Unmanned Aerial Vehicles (UAVs

    Directory of Open Access Journals (Sweden)

    Wenang Anurogo

    2017-06-01

    Full Text Available Aerial photogrammetry is one of the Alternative technologies for more detailed data, real time, fast and cheaper. Nowadays, many photogrammetric mapping methods have used UAV / unmanned drones or drones to retrieve and record data from an object in the earth. The application of drones in the field of geospatial science today is in great demand because of its relatively easy operation and relatively affordable cost compared to satellite systems especially high - resolution satellite imagery.  This research aims to determine the stage or overview of data retrieval process with DJI Phantom 4 (multi - rotor quad - copter drone with processing using third party software. This research also produces 2 - dimensional high resolution image data on the research area. Utilization of third party software (Agisoft PhotoScan making it easier to acquire and process aerial photogrammetric data. The results of aerial photogrammetric recording with a flying altitude of 70 meters obtained high resolution images with a spatial resolution of 2 inches / pixels.

  9. Design of uav robust autopilot based on adaptive neuro-fuzzy inference system

    Directory of Open Access Journals (Sweden)

    Mohand Achour Touat

    2008-04-01

    Full Text Available  This paper is devoted to the application of adaptive neuro-fuzzy inference systems to the robust control of the UAV longitudinal motion. The adaptive neore-fuzzy inference system model needs to be trained by input/output data. This data were obtained from the modeling of a ”crisp” robust control system. The synthesis of this system is based on the separation theorem, which defines the structure and parameters of LQG-optimal controller, and further - robust optimization of this controller, based on the genetic algorithm. Such design procedure can define the rule base and parameters of fuzzyfication and defuzzyfication algorithms of the adaptive neore-fuzzy inference system controller, which ensure the robust properties of the control system. Simulation of the closed loop control system of UAV longitudinal motion with adaptive neore-fuzzy inference system controller demonstrates high efficiency of proposed design procedure.

  10. UAV Controller Based on Adaptive Neuro-Fuzzy Inference System and PID

    Directory of Open Access Journals (Sweden)

    Ali Moltajaei Farid

    2013-01-01

    Full Text Available ANFIS is combining a neural network with a fuzzy system results in a hybrid neuro-fuzzy system, capable of reasoning and learning in an uncertain and imprecise environment. In this paper, an adaptive neuro-fuzzy inference system (ANFIS is employed to control an unmanned aircraft vehicle (UAV.  First, autopilots structure is defined, and then ANFIS controller is applied, to control UAVs lateral position. The results of ANFIS and PID lateral controllers are compared, where it shows the two controllers have similar results. ANFIS controller is capable to adaptation in nonlinear conditions, while PID has to be tuned to preserves proper control in some conditions. The simulation results generated by Matlab using Aerosim Aeronautical Simulation Block Set, which provides a complete set of tools for development of six degree-of-freedom. Nonlinear Aerosonde unmanned aerial vehicle model with ANFIS controller is simulated to verify the capability of the system. Moreover, the results are validated by FlightGear flight simulator.

  11. Introduction to UAV systems

    CERN Document Server

    Fahlstrom, Paul

    2012-01-01

    Unmanned aerial vehicles (UAVs) have been widely adopted in the military world over the last decade and the success of these military applications is increasingly driving efforts to establish unmanned aircraft in non-military roles. Introduction to UAV Systems, 4th edition provides a comprehensive introduction to all of the elements of a complete Unmanned Aircraft System (UAS). It addresses the air vehicle, mission planning and control, several types of mission payloads, data links and how they interact with mission performance, and launch and recovery concepts. This

  12. A UAV-Based Fog Collector Design for Fine-Scale Aerobiological Sampling

    Science.gov (United States)

    Gentry, Diana; Guarro, Marcello; Demachkie, Isabella Siham; Stumfall, Isabel; Dahlgren, Robert P.

    2017-01-01

    Airborne microbes are found throughout the troposphere and into the stratosphere. Knowing how the activity of airborne microorganisms can alter water, carbon, and other geochemical cycles is vital to a full understanding of local and global ecosystems. Just as on the land or in the ocean, atmospheric regions vary in habitability; the underlying geochemical, climatic, and ecological dynamics must be characterized at different scales to be effectively modeled. Most aerobiological studies have focused on a high level: 'How high are airborne microbes found?' and 'How far can they travel?' Most fog and cloud water studies collect from stationary ground stations (point) or along flight transects (1D). To complement and provide context for this data, we have designed a UAV-based modified fog and cloud water collector to retrieve 4D-resolved samples for biological and chemical analysis.Our design uses a passive impacting collector hanging from a rigid rod suspended between two multi-rotor UAVs. The suspension design reduces the effect of turbulence and potential for contamination from the UAV downwash. The UAVs are currently modeled in a leader-follower configuration, taking advantage of recent advances in modular UAVs, UAV swarming, and flight planning.The collector itself is a hydrophobic mesh. Materials including Tyvek, PTFE, nylon, and polypropylene monofilament fabricated via laser cutting, CNC knife, or 3D printing were characterized for droplet collection efficiency using a benchtop atomizer and particle counter. Because the meshes can be easily and inexpensively fabricated, a set can be pre-sterilized and brought to the field for 'hot swapping' to decrease cross-contamination between flight sessions or use as negative controls.An onboard sensor and logging system records the time and location of each sample; when combined with flight tracking data, the samples can be resolved into a 4D volumetric map of the fog bank. Collected samples can be returned to the lab for

  13. Uav-Based Crops Classification with Joint Features from Orthoimage and Dsm Data

    Science.gov (United States)

    Liu, B.; Shi, Y.; Duan, Y.; Wu, W.

    2018-04-01

    Accurate crops classification remains a challenging task due to the same crop with different spectra and different crops with same spectrum phenomenon. Recently, UAV-based remote sensing approach gains popularity not only for its high spatial and temporal resolution, but also for its ability to obtain spectraand spatial data at the same time. This paper focus on how to take full advantages of spatial and spectrum features to improve crops classification accuracy, based on an UAV platform equipped with a general digital camera. Texture and spatial features extracted from the RGB orthoimage and the digital surface model of the monitoring area are analysed and integrated within a SVM classification framework. Extensive experiences results indicate that the overall classification accuracy is drastically improved from 72.9 % to 94.5 % when the spatial features are combined together, which verified the feasibility and effectiveness of the proposed method.

  14. Unmanned aerial vehicle-based structure from motion biomass inventory estimates

    Science.gov (United States)

    Bedell, Emily; Leslie, Monique; Fankhauser, Katie; Burnett, Jonathan; Wing, Michael G.; Thomas, Evan A.

    2017-04-01

    Riparian vegetation restoration efforts require cost-effective, accurate, and replicable impact assessments. We present a method to use an unmanned aerial vehicle (UAV) equipped with a GoPro digital camera to collect photogrammetric data of a 0.8-ha riparian restoration. A three-dimensional point cloud was created from the photos using "structure from motion" techniques. The point cloud was analyzed and compared to traditional, ground-based monitoring techniques. Ground-truth data were collected on 6.3% of the study site and averaged across the entire site to report stem heights in stems/ha in three height classes. The project site was divided into four analysis sections, one for derivation of parameters used in the UAV data analysis and the remaining three sections reserved for method validation. Comparing the ground-truth data to the UAV generated data produced an overall error of 21.6% and indicated an R2 value of 0.98. A Bland-Altman analysis indicated a 95% probability that the UAV stems/section result will be within 61 stems/section of the ground-truth data. The ground-truth data are reported with an 80% confidence interval of ±1032 stems/ha thus, the UAV was able to estimate stems well within this confidence interval.

  15. Reproducibility of UAV-based earth topography reconstructions based on Structure-from-Motion algorithms

    Science.gov (United States)

    Clapuyt, Francois; Vanacker, Veerle; Van Oost, Kristof

    2016-05-01

    Combination of UAV-based aerial pictures and Structure-from-Motion (SfM) algorithm provides an efficient, low-cost and rapid framework for remote sensing and monitoring of dynamic natural environments. This methodology is particularly suitable for repeated topographic surveys in remote or poorly accessible areas. However, temporal analysis of landform topography requires high accuracy of measurements and reproducibility of the methodology as differencing of digital surface models leads to error propagation. In order to assess the repeatability of the SfM technique, we surveyed a study area characterized by gentle topography with an UAV platform equipped with a standard reflex camera, and varied the focal length of the camera and location of georeferencing targets between flights. Comparison of different SfM-derived topography datasets shows that precision of measurements is in the order of centimetres for identical replications which highlights the excellent performance of the SfM workflow, all parameters being equal. The precision is one order of magnitude higher for 3D topographic reconstructions involving independent sets of ground control points, which results from the fact that the accuracy of the localisation of ground control points strongly propagates into final results.

  16. VISUAL UAV TRAJECTORY PLAN SYSTEM BASED ON NETWORK MAP

    Directory of Open Access Journals (Sweden)

    X. L. Li

    2012-07-01

    Full Text Available The base map of the current software UP-30 using in trajectory plan for Unmanned Aircraft Vehicle is vector diagram. UP-30 draws navigation points manually. But in the field of operation process, the efficiency and the quality of work is influenced because of insufficient information, screen reflection, calculate inconveniently and other factors. If we do this work in indoor, the effect of external factors on the results would be eliminated, the network earth users can browse the free world high definition satellite images through downloading a client software, and can export the high resolution image by standard file format. This brings unprecedented convenient of trajectory plan. But the images must be disposed by coordinate transformation, geometric correction. In addition, according to the requirement of mapping scale ,camera parameters and overlap degree we can calculate exposure hole interval and trajectory distance between the adjacent trajectory automatically . This will improve the degree of automation of data collection. Software will judge the position of next point according to the intersection of the trajectory and the survey area and ensure the position of point according to trajectory distance. We can undertake the points artificially. So the trajectory plan is automatic and flexible. Considering safety, the date can be used in flying after simulating flight. Finally we can export all of the date using a key

  17. Visual Uav Trajectory Plan System Based on Network Map

    Science.gov (United States)

    Li, X. L.; Lin, Z. J.; Su, G. Z.; Wu, B. Y.

    2012-07-01

    The base map of the current software UP-30 using in trajectory plan for Unmanned Aircraft Vehicle is vector diagram. UP-30 draws navigation points manually. But in the field of operation process, the efficiency and the quality of work is influenced because of insufficient information, screen reflection, calculate inconveniently and other factors. If we do this work in indoor, the effect of external factors on the results would be eliminated, the network earth users can browse the free world high definition satellite images through downloading a client software, and can export the high resolution image by standard file format. This brings unprecedented convenient of trajectory plan. But the images must be disposed by coordinate transformation, geometric correction. In addition, according to the requirement of mapping scale ,camera parameters and overlap degree we can calculate exposure hole interval and trajectory distance between the adjacent trajectory automatically . This will improve the degree of automation of data collection. Software will judge the position of next point according to the intersection of the trajectory and the survey area and ensure the position of point according to trajectory distance. We can undertake the points artificially. So the trajectory plan is automatic and flexible. Considering safety, the date can be used in flying after simulating flight. Finally we can export all of the date using a key

  18. A UAV and S2A data-based estimation of the initial biomass of green algae in the South Yellow Sea.

    Science.gov (United States)

    Xu, Fuxiang; Gao, Zhiqiang; Jiang, Xiaopeng; Shang, Weitao; Ning, Jicai; Song, Debin; Ai, Jinquan

    2018-03-01

    Previous studies have shown that the initial biomass of green tide was the green algae attaching to Pyropia aquaculture rafts in the Southern Yellow Sea. In this study, the green algae was identified with unmanned aerial vehicle (UAV), an biomass estimation model was proposed for green algae biomass in the radial sand ridge area based on Sentinel-2A image (S2A) and UAV images. The result showed that the green algae was detected highly accurately with the normalized green-red difference index (NGRDI); approximately 1340 tons and 700 tons of green algae were attached to rafts and raft ropes respectively, and the lower biomass might be the main cause for the smaller scale of green tide in 2017. In addition, UAV play an important role in raft-attaching green algae monitoring and long-term research of its biomass would provide a scientific basis for the control and forecast of green tide in the Yellow Sea. Copyright © 2018 Elsevier Ltd. All rights reserved.

  19. UAV-borne lidar with MEMS mirror-based scanning capability

    Science.gov (United States)

    Kasturi, Abhishek; Milanovic, Veljko; Atwood, Bryan H.; Yang, James

    2016-05-01

    Firstly, we demonstrated a wirelessly controlled MEMS scan module with imaging and laser tracking capability which can be mounted and flown on a small UAV quadcopter. The MEMS scan module was reduced down to a small volume of smartphone via Bluetooth while flying on a drone, and could project vector content, text, and perform laser based tracking. Also, a "point-and-range" LiDAR module was developed for UAV applications based on low SWaP (Size, Weight and Power) gimbal-less MEMS mirror beam-steering technology and off-the-shelf OEM LRF modules. For demonstration purposes of an integrated laser range finder module, we used a simple off-the-shelf OEM laser range finder (LRF) with a 100m range, +/-1.5mm accuracy, and 4Hz ranging capability. The LRFs receiver optics were modified to accept 20° of angle, matching the transmitter's FoR. A relatively large (5.0mm) diameter MEMS mirror with +/-10° optical scanning angle was utilized in the demonstration to maintain the small beam divergence of the module. The complete LiDAR prototype can fit into a small volume of battery. The MEMS mirror based LiDAR system allows for ondemand ranging of points or areas within the FoR without altering the UAV's position. Increasing the LRF ranging frequency and stabilizing the pointing of the laser beam by utilizing the onboard inertial sensors and the camera are additional goals of the next design.

  20. UAV-Based Thermal Imaging for High-Throughput Field Phenotyping of Black Poplar Response to Drought.

    Science.gov (United States)

    Ludovisi, Riccardo; Tauro, Flavia; Salvati, Riccardo; Khoury, Sacha; Mugnozza Scarascia, Giuseppe; Harfouche, Antoine

    2017-01-01

    Poplars are fast-growing, high-yielding forest tree species, whose cultivation as second-generation biofuel crops is of increasing interest and can efficiently meet emission reduction goals. Yet, breeding elite poplar trees for drought resistance remains a major challenge. Worldwide breeding programs are largely focused on intra/interspecific hybridization, whereby Populus nigra L. is a fundamental parental pool. While high-throughput genotyping has resulted in unprecedented capabilities to rapidly decode complex genetic architecture of plant stress resistance, linking genomics to phenomics is hindered by technically challenging phenotyping. Relying on unmanned aerial vehicle (UAV)-based remote sensing and imaging techniques, high-throughput field phenotyping (HTFP) aims at enabling highly precise and efficient, non-destructive screening of genotype performance in large populations. To efficiently support forest-tree breeding programs, ground-truthing observations should be complemented with standardized HTFP. In this study, we develop a high-resolution (leaf level) HTFP approach to investigate the response to drought of a full-sib F 2 partially inbred population (termed here 'POP6'), whose F 1 was obtained from an intraspecific P. nigra controlled cross between genotypes with highly divergent phenotypes. We assessed the effects of two water treatments (well-watered and moderate drought) on a population of 4603 trees (503 genotypes) hosted in two adjacent experimental plots (1.67 ha) by conducting low-elevation (25 m) flights with an aerial drone and capturing 7836 thermal infrared (TIR) images. TIR images were undistorted, georeferenced, and orthorectified to obtain radiometric mosaics. Canopy temperature ( T c ) was extracted using two independent semi-automated segmentation techniques, eCognition- and Matlab-based, to avoid the mixed-pixel problem. Overall, results showed that the UAV platform-based thermal imaging enables to effectively assess genotype

  1. UAV-Based Thermal Imaging for High-Throughput Field Phenotyping of Black Poplar Response to Drought

    Directory of Open Access Journals (Sweden)

    Riccardo Ludovisi

    2017-09-01

    Full Text Available Poplars are fast-growing, high-yielding forest tree species, whose cultivation as second-generation biofuel crops is of increasing interest and can efficiently meet emission reduction goals. Yet, breeding elite poplar trees for drought resistance remains a major challenge. Worldwide breeding programs are largely focused on intra/interspecific hybridization, whereby Populus nigra L. is a fundamental parental pool. While high-throughput genotyping has resulted in unprecedented capabilities to rapidly decode complex genetic architecture of plant stress resistance, linking genomics to phenomics is hindered by technically challenging phenotyping. Relying on unmanned aerial vehicle (UAV-based remote sensing and imaging techniques, high-throughput field phenotyping (HTFP aims at enabling highly precise and efficient, non-destructive screening of genotype performance in large populations. To efficiently support forest-tree breeding programs, ground-truthing observations should be complemented with standardized HTFP. In this study, we develop a high-resolution (leaf level HTFP approach to investigate the response to drought of a full-sib F2 partially inbred population (termed here ‘POP6’, whose F1 was obtained from an intraspecific P. nigra controlled cross between genotypes with highly divergent phenotypes. We assessed the effects of two water treatments (well-watered and moderate drought on a population of 4603 trees (503 genotypes hosted in two adjacent experimental plots (1.67 ha by conducting low-elevation (25 m flights with an aerial drone and capturing 7836 thermal infrared (TIR images. TIR images were undistorted, georeferenced, and orthorectified to obtain radiometric mosaics. Canopy temperature (Tc was extracted using two independent semi-automated segmentation techniques, eCognition- and Matlab-based, to avoid the mixed-pixel problem. Overall, results showed that the UAV platform-based thermal imaging enables to effectively assess genotype

  2. Energy-Efficient Systems Eliminate Icing Danger for UAVs

    Science.gov (United States)

    2010-01-01

    Ames Research Center engineer Leonard Haslim invented an anti-icing t echnology called an electroexpulsive separation system, which uses m echanical force to shatter potentially dangerous ice buildup on an ai rcraft surface. Temecula, California-based Ice Management Systems (no w known as IMS-ESS) licensed the technology from Ames and has discov ered a niche market for the lightweight, energy-efficient technology: unmanned aerial vehicles (UAVs). IMS-ESS systems now prevent damagi ng ice accumulation on military UAVs, allowing the vehicles to carry out crucial missions year round.

  3. Uav-Based Photogrammetric Point Clouds and Hyperspectral Imaging for Mapping Biodiversity Indicators in Boreal Forests

    Science.gov (United States)

    Saarinen, N.; Vastaranta, M.; Näsi, R.; Rosnell, T.; Hakala, T.; Honkavaara, E.; Wulder, M. A.; Luoma, V.; Tommaselli, A. M. G.; Imai, N. N.; Ribeiro, E. A. W.; Guimarães, R. B.; Holopainen, M.; Hyyppä, J.

    2017-10-01

    Biodiversity is commonly referred to as species diversity but in forest ecosystems variability in structural and functional characteristics can also be treated as measures of biodiversity. Small unmanned aerial vehicles (UAVs) provide a means for characterizing forest ecosystem with high spatial resolution, permitting measuring physical characteristics of a forest ecosystem from a viewpoint of biodiversity. The objective of this study is to examine the applicability of photogrammetric point clouds and hyperspectral imaging acquired with a small UAV helicopter in mapping biodiversity indicators, such as structural complexity as well as the amount of deciduous and dead trees at plot level in southern boreal forests. Standard deviation of tree heights within a sample plot, used as a proxy for structural complexity, was the most accurately derived biodiversity indicator resulting in a mean error of 0.5 m, with a standard deviation of 0.9 m. The volume predictions for deciduous and dead trees were underestimated by 32.4 m3/ha and 1.7 m3/ha, respectively, with standard deviation of 50.2 m3/ha for deciduous and 3.2 m3/ha for dead trees. The spectral features describing brightness (i.e. higher reflectance values) were prevailing in feature selection but several wavelengths were represented. Thus, it can be concluded that structural complexity can be predicted reliably but at the same time can be expected to be underestimated with photogrammetric point clouds obtained with a small UAV. Additionally, plot-level volume of dead trees can be predicted with small mean error whereas identifying deciduous species was more challenging at plot level.

  4. Mini-Uav LIDAR for Power Line Inspection

    Science.gov (United States)

    Teng, G. E.; Zhou, M.; Li, C. R.; Wu, H. H.; Li, W.; Meng, F. R.; Zhou, C. C.; Ma, L.

    2017-09-01

    Light detection and ranging (LIDAR) system based on unmanned aerial vehicles (UAVs) recently are in rapid advancement, meanwhile portable and flexible mini-UAV-borne laser scanners have been a hot research field, especially for the complex terrain survey in the mountains and other areas. This study proposes a power line inspection system solution based on mini-UAV-borne LIDAR system-AOEagle, developed by Academy of Opto-Electronics, Chinese Academy of Sciences, which mounted on a Multi-rotor unmanned aerial vehicle for complex terrain survey according to real test. Furthermore, the point cloud data was explored to validate its applicability for power line inspection, in terms of corridor and line laser point clouds; deformation detection of power towers, etc. The feasibility and advantages of AOEagle have been demonstrated by the promising results based on the real-measured data in the field of power line inspection.

  5. Artificial Neural Network to Predict Vine Water Status Spatial Variability Using Multispectral Information Obtained from an Unmanned Aerial Vehicle (UAV).

    Science.gov (United States)

    Poblete, Tomas; Ortega-Farías, Samuel; Moreno, Miguel Angel; Bardeen, Matthew

    2017-10-30

    Water stress, which affects yield and wine quality, is often evaluated using the midday stem water potential (Ψ stem ). However, this measurement is acquired on a per plant basis and does not account for the assessment of vine water status spatial variability. The use of multispectral cameras mounted on unmanned aerial vehicle (UAV) is capable to capture the variability of vine water stress in a whole field scenario. It has been reported that conventional multispectral indices (CMI) that use information between 500-800 nm, do not accurately predict plant water status since they are not sensitive to water content. The objective of this study was to develop artificial neural network (ANN) models derived from multispectral images to predict the Ψ stem spatial variability of a drip-irrigated Carménère vineyard in Talca, Maule Region, Chile. The coefficient of determination (R²) obtained between ANN outputs and ground-truth measurements of Ψ stem were between 0.56-0.87, with the best performance observed for the model that included the bands 550, 570, 670, 700 and 800 nm. Validation analysis indicated that the ANN model could estimate Ψ stem with a mean absolute error (MAE) of 0.1 MPa, root mean square error (RMSE) of 0.12 MPa, and relative error (RE) of -9.1%. For the validation of the CMI, the MAE, RMSE and RE values were between 0.26-0.27 MPa, 0.32-0.34 MPa and -24.2-25.6%, respectively.

  6. Artificial Neural Network to Predict Vine Water Status Spatial Variability Using Multispectral Information Obtained from an Unmanned Aerial Vehicle (UAV

    Directory of Open Access Journals (Sweden)

    Tomas Poblete

    2017-10-01

    Full Text Available Water stress, which affects yield and wine quality, is often evaluated using the midday stem water potential (Ψstem. However, this measurement is acquired on a per plant basis and does not account for the assessment of vine water status spatial variability. The use of multispectral cameras mounted on unmanned aerial vehicle (UAV is capable to capture the variability of vine water stress in a whole field scenario. It has been reported that conventional multispectral indices (CMI that use information between 500–800 nm, do not accurately predict plant water status since they are not sensitive to water content. The objective of this study was to develop artificial neural network (ANN models derived from multispectral images to predict the Ψstem spatial variability of a drip-irrigated Carménère vineyard in Talca, Maule Region, Chile. The coefficient of determination (R2 obtained between ANN outputs and ground-truth measurements of Ψstem were between 0.56–0.87, with the best performance observed for the model that included the bands 550, 570, 670, 700 and 800 nm. Validation analysis indicated that the ANN model could estimate Ψstem with a mean absolute error (MAE of 0.1 MPa, root mean square error (RMSE of 0.12 MPa, and relative error (RE of −9.1%. For the validation of the CMI, the MAE, RMSE and RE values were between 0.26–0.27 MPa, 0.32–0.34 MPa and −24.2–25.6%, respectively.

  7. Saliency Detection and Deep Learning-Based Wildfire Identification in UAV Imagery.

    Science.gov (United States)

    Zhao, Yi; Ma, Jiale; Li, Xiaohui; Zhang, Jie

    2018-02-27

    An unmanned aerial vehicle (UAV) equipped with global positioning systems (GPS) can provide direct georeferenced imagery, mapping an area with high resolution. So far, the major difficulty in wildfire image classification is the lack of unified identification marks, the fire features of color, shape, texture (smoke, flame, or both) and background can vary significantly from one scene to another. Deep learning (e.g., DCNN for Deep Convolutional Neural Network) is very effective in high-level feature learning, however, a substantial amount of training images dataset is obligatory in optimizing its weights value and coefficients. In this work, we proposed a new saliency detection algorithm for fast location and segmentation of core fire area in aerial images. As the proposed method can effectively avoid feature loss caused by direct resizing; it is used in data augmentation and formation of a standard fire image dataset 'UAV_Fire'. A 15-layered self-learning DCNN architecture named 'Fire_Net' is then presented as a self-learning fire feature exactor and classifier. We evaluated different architectures and several key parameters (drop out ratio, batch size, etc.) of the DCNN model regarding its validation accuracy. The proposed architecture outperformed previous methods by achieving an overall accuracy of 98%. Furthermore, 'Fire_Net' guarantied an average processing speed of 41.5 ms per image for real-time wildfire inspection. To demonstrate its practical utility, Fire_Net is tested on 40 sampled images in wildfire news reports and all of them have been accurately identified.

  8. Multi-UAV Flight using Virtual Structure Combined with Behavioral Approach

    Directory of Open Access Journals (Sweden)

    Kownacki Cezary

    2016-06-01

    Full Text Available Implementations of multi-UAV systems can be divided mainly into two different approaches, centralised system that synchronises positions of each vehicle by a ground station and an autonomous system based on decentralised control, which offers more flexibility and independence. Decentralisation of multi-UAV control entails the need for information sharing between all vehicles, what in some cases could be problematic due to a significant amount of data to be sent over the wireless network. To improve the reliability and the throughput of information sharing inside the formation of UAVs, this paper proposes an approach that combines virtual structure with a leader and two flocking behaviours. Each UAV has assigned different virtual migration point referenced to the leader's position which is simultaneously the origin of a formation reference frame. All migration points create together a virtual rigid structure. Each vehicle uses local behaviours of cohesion and repulsion respectively, to track its own assigned point in the structure and to avoid a collision with the previous UAV in the structure. To calculate parameters of local behaviours, each UAV should know position and attitude of the leader to define the formation reference frame and also the actual position of the previous UAV in the structure. Hence, information sharing can be based on a chain of local peer-to-peer communication between two consecutive vehicles in the structure. In such solution, the information about the leader could be sequentially transmitted from one UAV to another. Numerical simulations were prepared and carried out to verify the effectiveness of the presented approach. Trajectories recorded during those simulations show collective, coherence and collision-free flights of the formation created with five UAVs.

  9. UAV based mapping of variation in grassland yield for forage production in Arctic environments

    Science.gov (United States)

    Davids, C.; Karlsen, S. R.; Jørgensen, M.; Ancin Murguzur, F. J.

    2017-12-01

    Grassland cultivation for animal feed is the key agricultural activity in northern Norway. Even though the growing season has increased by at least a week in the last 30 years, grassland yields appear to have declined, probably due to more challenging winter conditions and changing agronomy practices. The ability for local and regional crop productivity forecasting would assist farmers with management decisions and would provide local and national authorities with a better overview over productivity and potential problems due to e.g. winter damage. Remote sensing technology has long been used to estimate and map the variability of various biophysical parameters, but calibration is important. In order to establish the relationship between spectral reflectance and grass yield in northern European environments we combine Sentinel-2 time series, UAV-based multispectral measurements, and ground-based spectroradiometry, with biomass analyses and observations of species composition. In this presentation we will focus on the results from the UAV data acquisition. We used a multirotor UAV with different sensors (a multispectral Rikola camera, and NDVI and RGB cameras) to image a number of cultivated grasslands of different age and productivity in northern Norway in June/July 2016 and 2017. Following UAV data acquisition, 10 to 20 in situ measurements were made per field using a FieldSpec3 (350-2500 nm). In addition, samples were taken to determine biomass and grass species composition. The imaging and sampling was done immediately prior to harvesting. The Rikola camera, when used as a stand-alone camera mounted on a UAV, can collect 15 bands with a spectral width of 10-15 nm in the range between 500-890 nm. In the initial analysis of the 2016 data we investigated how well different vegetation indices correlated with biomass and showed that vegetation indices that include red edge bands perform better than widely used indices such as NDVI. We will extend the analysis with

  10. Miniature UAVs : An overview

    NARCIS (Netherlands)

    Weimar, P.W.L.; Kerkkamp, J.S.F.; Wiel, R.A.N.; Meiller, P.P.; Bos, J.G.H.

    2014-01-01

    With this book TNO provides an overview of topics related to Miniature Unmanned Aerial Vehicles (MUAVs). Both novices and experts may find this publication valuable. The Netherlands Organisation for Applied Scientific Research TNO conducts research on UAVs and MUAVs, see for example [1], on the

  11. Online UAV Mission Planning

    NARCIS (Netherlands)

    Evers, L.; Barros, A.I.; Monsuur, H.; Wagelmans, A.P.M.

    2014-01-01

    Unmanned Aerial Vehicles (UAVs) have become an essential asset for military and law enforcement operations. In particular their use for surveillance and reconnaissance tasks has been growing due to the quick developments in the areal systems themselves, sensor technology, and image processing

  12. Review of the current state of UAV regulations

    NARCIS (Netherlands)

    Stöcker, Elvira Claudia; Bennett, Rohan; Nex, Francesco; Gerke, Markus; Zevenbergen, Jaap

    2017-01-01

    UAVs-unmanned aerial vehicles-facilitate data acquisition at temporal and spatial scales that still remain unachievable for traditional remote sensing platforms. However, current legal frameworks that regulate UAVs present significant barriers to research and development. To highlight the

  13. Evaluation and development of unmanned aircraft (UAV) for UDOT needs.

    Science.gov (United States)

    2012-05-01

    This research involved the use of high-resolution aerial photography obtained from Unmanned Aerial Vehicles (UAV) to aid UDOT in monitoring and documenting State Roadway structures and associated issues. Using geo-referenced UAV high resolution aeria...

  14. Multi-UAVs Formation Autonomous Control Method Based on RQPSO-FSM-DMPC

    Directory of Open Access Journals (Sweden)

    Shao-lei Zhou

    2016-01-01

    Full Text Available For various threats in the enemy defense area, in order to achieve covert penetration and implement effective combat against enemy, the unmanned aerial vehicles formation needs to be reconfigured in the process of penetration; the mutual collision avoidance problems and communication constraint problems among the formation also need to be considered. By establishing the virtual-leader formation model, this paper puts forward distributed model predictive control and finite state machine formation manager. Combined with distributed cooperative strategy establishing the formation reconfiguration cost function, this paper proposes that adopting the revised quantum-behaved particle swarm algorithm solves the cost function, and it is compared with the result which is solved by particle swarm algorithm. Simulation result shows that this algorithm can control multiple UAVs formation autonomous reconfiguration effectively and achieve covert penetration safely.

  15. RAPID EXTRACTION OF LANDSLIDE AND SPATIAL DISTRIBUTION ANALYSIS AFTER JIUZHAIGOU Ms7.0 EARTHQUAKE BASED ON UAV IMAGES

    OpenAIRE

    Q. S. Jiao; Y. Luo; W. H. Shen; Q. Li; X. Wang

    2018-01-01

    Jiuzhaigou earthquake led to the collapse of the mountains and formed lots of landslides in Jiuzhaigou scenic spot and surrounding roads which caused road blockage and serious ecological damage. Due to the urgency of the rescue, the authors carried unmanned aerial vehicle (UAV) and entered the disaster area as early as August 9 to obtain the aerial images near the epicenter. On the basis of summarizing the earthquake landslides characteristics in aerial images, by using the object-oriented an...

  16. An Application of UAV Attitude Estimation Using a Low-Cost Inertial Navigation System

    Science.gov (United States)

    Eure, Kenneth W.; Quach, Cuong Chi; Vazquez, Sixto L.; Hogge, Edward F.; Hill, Boyd L.

    2013-01-01

    Unmanned Aerial Vehicles (UAV) are playing an increasing role in aviation. Various methods exist for the computation of UAV attitude based on low cost microelectromechanical systems (MEMS) and Global Positioning System (GPS) receivers. There has been a recent increase in UAV autonomy as sensors are becoming more compact and onboard processing power has increased significantly. Correct UAV attitude estimation will play a critical role in navigation and separation assurance as UAVs share airspace with civil air traffic. This paper describes attitude estimation derived by post-processing data from a small low cost Inertial Navigation System (INS) recorded during the flight of a subscale commercial off the shelf (COTS) UAV. Two discrete time attitude estimation schemes are presented here in detail. The first is an adaptation of the Kalman Filter to accommodate nonlinear systems, the Extended Kalman Filter (EKF). The EKF returns quaternion estimates of the UAV attitude based on MEMS gyro, magnetometer, accelerometer, and pitot tube inputs. The second scheme is the complementary filter which is a simpler algorithm that splits the sensor frequency spectrum based on noise characteristics. The necessity to correct both filters for gravity measurement errors during turning maneuvers is demonstrated. It is shown that the proposed algorithms may be used to estimate UAV attitude. The effects of vibration on sensor measurements are discussed. Heuristic tuning comments pertaining to sensor filtering and gain selection to achieve acceptable performance during flight are given. Comparisons of attitude estimation performance are made between the EKF and the complementary filter.

  17. Design of a Helium Vapor Shroud for Liquid Hydrogen Fueling of an Unmanned Aerial Vehicle (UAV)

    Science.gov (United States)

    Cavender, K.; Evans, C.; Haney, J.; Leachman, J.

    2017-12-01

    Filling a vehicular liquid hydrogen fuel tank presents the potential for flammable mixtures due to oxygen concentration from liquid air condensation. Current liquid hydrogen tank designs utilize insulating paradigms such as aerogel/fiberglass materials, vacuum jackets, or inert gas purge systems to keep the outer surface from reaching the condensation temperature of air. This work examines the heat transfer at the refuelling connection of the tank to identify potential areas of condensation, as well as the surface temperature gradient. A shrouded inert gas purge was designed to minimize vehicle weight and refuelling time. The design of a shrouded inert gas purge system is presented to displace air preventing air condensation. The design investigates 3D printed materials for an inert gas shroud, as well as low-temperature sealing designs. Shroud designs and temperature profiles were measured and tested by running liquid nitrogen through the filling manifold. Materials for the inert gas shroud are discussed and experimental results are compared to analytical model predictions. Suggestions for future design improvements are made.

  18. Ultra-Tightly Coupled GNSS/INS for small UAVs

    DEFF Research Database (Denmark)

    Olesen, Daniel; Jakobsen, Jakob; Knudsen, Per

    2017-01-01

    This paper describes an ultra-tight integration of a Global Navigation Satellite System ( GNSS) receiver and an Inertial Navigation System ( INS) for small Unmanned Aerial Vehicles ( UAVs). The system is based on a low-cost and low-weight GNSS Intermediate Frequency ( IF) sampler which has been...

  19. Spectrum correction algorithm for detectors in airborne radioactivity monitoring equipment NH-UAV based on a ratio processing method

    International Nuclear Information System (INIS)

    Cao, Ye; Tang, Xiao-Bin; Wang, Peng; Meng, Jia; Huang, Xi; Wen, Liang-Sheng; Chen, Da

    2015-01-01

    The unmanned aerial vehicle (UAV) radiation monitoring method plays an important role in nuclear accidents emergency. In this research, a spectrum correction algorithm about the UAV airborne radioactivity monitoring equipment NH-UAV was studied to measure the radioactive nuclides within a small area in real time and in a fixed place. The simulation spectra of the high-purity germanium (HPGe) detector and the lanthanum bromide (LaBr 3 ) detector in the equipment were obtained using the Monte Carlo technique. Spectrum correction coefficients were calculated after performing ratio processing techniques about the net peak areas between the double detectors on the detection spectrum of the LaBr 3 detector according to the accuracy of the detection spectrum of the HPGe detector. The relationship between the spectrum correction coefficient and the size of the source term was also investigated. A good linear relation exists between the spectrum correction coefficient and the corresponding energy (R 2 =0.9765). The maximum relative deviation from the real condition reduced from 1.65 to 0.035. The spectrum correction method was verified as feasible. - Highlights: • An airborne radioactivity monitoring equipment NH-UAV was developed to measure radionuclide after a nuclear accident. • A spectrum correction algorithm was proposed to obtain precise information on the detected radioactivity within a small area. • The spectrum correction method was verified as feasible. • The corresponding spectrum correction coefficients increase first and then stay constant

  20. Spectrum correction algorithm for detectors in airborne radioactivity monitoring equipment NH-UAV based on a ratio processing method

    Energy Technology Data Exchange (ETDEWEB)

    Cao, Ye [Department of Nuclear Science and Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016 (China); Tang, Xiao-Bin, E-mail: tangxiaobin@nuaa.edu.cn [Department of Nuclear Science and Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016 (China); Jiangsu Key Laboratory of Nuclear Energy Equipment Materials Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016 (China); Wang, Peng; Meng, Jia; Huang, Xi; Wen, Liang-Sheng [Department of Nuclear Science and Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016 (China); Chen, Da [Department of Nuclear Science and Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016 (China); Jiangsu Key Laboratory of Nuclear Energy Equipment Materials Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016 (China)

    2015-10-11

    The unmanned aerial vehicle (UAV) radiation monitoring method plays an important role in nuclear accidents emergency. In this research, a spectrum correction algorithm about the UAV airborne radioactivity monitoring equipment NH-UAV was studied to measure the radioactive nuclides within a small area in real time and in a fixed place. The simulation spectra of the high-purity germanium (HPGe) detector and the lanthanum bromide (LaBr{sub 3}) detector in the equipment were obtained using the Monte Carlo technique. Spectrum correction coefficients were calculated after performing ratio processing techniques about the net peak areas between the double detectors on the detection spectrum of the LaBr{sub 3} detector according to the accuracy of the detection spectrum of the HPGe detector. The relationship between the spectrum correction coefficient and the size of the source term was also investigated. A good linear relation exists between the spectrum correction coefficient and the corresponding energy (R{sup 2}=0.9765). The maximum relative deviation from the real condition reduced from 1.65 to 0.035. The spectrum correction method was verified as feasible. - Highlights: • An airborne radioactivity monitoring equipment NH-UAV was developed to measure radionuclide after a nuclear accident. • A spectrum correction algorithm was proposed to obtain precise information on the detected radioactivity within a small area. • The spectrum correction method was verified as feasible. • The corresponding spectrum correction coefficients increase first and then stay constant.

  1. Exploring the contributions of vegetation and dune size to early dune development using unmanned aerial vehicle (UAV) imaging

    Science.gov (United States)

    van Puijenbroek, Marinka E. B.; Nolet, Corjan; de Groot, Alma V.; Suomalainen, Juha M.; Riksen, Michel J. P. M.; Berendse, Frank; Limpens, Juul

    2017-12-01

    Dune development along highly dynamic land-sea boundaries is the result of interaction between vegetation and dune size with sedimentation and erosion processes. Disentangling the contribution of vegetation characteristics from that of dune size would improve predictions of nebkha dune development under a changing climate, but has proven difficult due to the scarcity of spatially continuous monitoring data. This study explored the contributions of vegetation and dune size to dune development for locations differing in shelter from the sea. We monitored a natural nebkha dune field of 8 ha, along the coast of the island Texel, the Netherlands, for 1 year using an unmanned aerial vehicle (UAV) with camera. After constructing a digital surface model and orthomosaic we derived for each dune (1) vegetation characteristics (species composition, vegetation density, and maximum vegetation height), (2) dune size (dune volume, area, and maximum height), (3) degree of shelter (proximity to other nebkha dunes and the sheltering by the foredune). Changes in dune volume over summer and winter were related to vegetation, dune size and degree of shelter. We found that a positive change in dune volume (dune growth) was linearly related to initial dune volume over summer but not over winter. Big dunes accumulated more sand than small dunes due to their larger surface area. Exposed dunes increased more in volume (0.81 % per dune per week) than sheltered dunes (0.2 % per dune per week) over summer, while the opposite occurred over winter. Vegetation characteristics did not significantly affect dune growth in summer, but did significantly affect dune growth in winter. Over winter, dunes dominated by Ammophila arenaria, a grass species with high vegetation density throughout the year, increased more in volume than dunes dominated by Elytrigia juncea, a grass species with lower vegetation density (0.43 vs. 0.42 (m3 m-3) week-1). The effect of species was irrespective of dune size or

  2. Object Based Building Extraction and Building Period Estimation from Unmanned Aerial Vehicle Data

    Science.gov (United States)

    Comert, Resul; Kaplan, Onur

    2018-04-01

    The aim of this study is to examine whether it is possible to estimate the building periods with respect to the building heights in the urban scale seismic performance assessment studies by using the building height retrieved from the unmanned aerial vehicle (UAV) data. For this purpose, a small area, which includes eight residential reinforced concrete buildings, was selected in Eskisehir (Turkey) city center. In this paper, the possibilities of obtaining the building heights that are used in the estimation of building periods from UAV based data, have been investigated. The investigations were carried out in 3 stages; (i) Building boundary extraction with Object Based Image Analysis (OBIA), (ii) height calculation for buildings of interest from nDSM and accuracy assessment with the terrestrial survey. (iii) Estimation of building period using height information. The average difference between the periods estimated according to the heights obtained from field measurements and from the UAV data is 2.86 % and the maximum difference is 13.2 %. Results of this study have shown that the building heights retrieved from the UAV data can be used in the building period estimation in the urban scale vulnerability assessments.

  3. Data Gathering and Energy Transfer Dilemma in UAV-Assisted Flying Access Network for IoT.

    Science.gov (United States)

    Arabi, Sara; Sabir, Essaid; Elbiaze, Halima; Sadik, Mohamed

    2018-05-11

    Recently, Unmanned Aerial Vehicles (UAVs) have emerged as an alternative solution to assist wireless networks, thanks to numerous advantages they offer in comparison to terrestrial fixed base stations. For instance, a UAV can be used to embed a flying base station providing an on-demand nomadic access to network services. A UAV can also be used to wirelessly recharge out-of-battery ground devices. In this paper, we aim to deal with both data collection and recharging depleted ground Internet-of-Things (IoT) devices through a UAV station used as a flying base station. To extend the network lifetime, we present a novel use of UAV with energy harvesting module and wireless recharging capabilities. However, the UAV is used as an energy source to empower depleted IoT devices. On one hand, the UAV charges depleted ground IoT devices under three policies: (1) low-battery first scheme; (2) high-battery first scheme; and (3) random scheme. On the other hand, the UAV station collects data from IoT devices that have sufficient energy to transmit their packets, and in the same phase, the UAV exploits the Radio Frequency (RF) signals transmitted by IoT devices to extract and harvest energy. Furthermore, and as the UAV station has a limited coverage time due to its energy constraints, we propose and investigate an efficient trade-off between ground users recharging time and data gathering time. Furthermore, we suggest to control and optimize the UAV trajectory in order to complete its travel within a minimum time, while minimizing the energy spent and/or enhancing the network lifetime. Extensive numerical results and simulations show how the system behaves under different scenarios and using various metrics in which we examine the added value of UAV with energy harvesting module.

  4. Data Gathering and Energy Transfer Dilemma in UAV-Assisted Flying Access Network for IoT

    Directory of Open Access Journals (Sweden)

    Sara Arabi

    2018-05-01

    Full Text Available Recently, Unmanned Aerial Vehicles (UAVs have emerged as an alternative solution to assist wireless networks, thanks to numerous advantages they offer in comparison to terrestrial fixed base stations. For instance, a UAV can be used to embed a flying base station providing an on-demand nomadic access to network services. A UAV can also be used to wirelessly recharge out-of-battery ground devices. In this paper, we aim to deal with both data collection and recharging depleted ground Internet-of-Things (IoT devices through a UAV station used as a flying base station. To extend the network lifetime, we present a novel use of UAV with energy harvesting module and wireless recharging capabilities. However, the UAV is used as an energy source to empower depleted IoT devices. On one hand, the UAV charges depleted ground IoT devices under three policies: (1 low-battery first scheme; (2 high-battery first scheme; and (3 random scheme. On the other hand, the UAV station collects data from IoT devices that have sufficient energy to transmit their packets, and in the same phase, the UAV exploits the Radio Frequency (RF signals transmitted by IoT devices to extract and harvest energy. Furthermore, and as the UAV station has a limited coverage time due to its energy constraints, we propose and investigate an efficient trade-off between ground users recharging time and data gathering time. Furthermore, we suggest to control and optimize the UAV trajectory in order to complete its travel within a minimum time, while minimizing the energy spent and/or enhancing the network lifetime. Extensive numerical results and simulations show how the system behaves under different scenarios and using various metrics in which we examine the added value of UAV with energy harvesting module.

  5. Lightweight Hyperspectral Mapping System and a Novel Photogrammetric Processing Chain for UAV-based Sensing

    Science.gov (United States)

    Suomalainen, Juha; Franke, Jappe; Anders, Niels; Iqbal, Shahzad; Wenting, Philip; Becker, Rolf; Kooistra, Lammert

    2014-05-01

    We have developed a lightweight Hyperspectral Mapping System (HYMSY) and a novel processing chain for UAV based mapping. The HYMSY consists of a custom pushbroom spectrometer (range 450-950nm, FWHM 9nm, ~20 lines/s, 328 pixels/line), a consumer camera (collecting 16MPix raw image every 2 seconds), a GPS-Inertia Navigation System (GPS-INS), and synchronization and data storage units. The weight of the system at take-off is 2.0kg allowing us to mount it on a relatively small octocopter. The novel processing chain exploits photogrammetry in the georectification process of the hyperspectral data. At first stage the photos are processed in a photogrammetric software producing a high-resolution RGB orthomosaic, a Digital Surface Model (DSM), and photogrammetric UAV/camera position and attitude at the moment of each photo. These photogrammetric camera positions are then used to enhance the internal accuracy of GPS-INS data. These enhanced GPS-INS data are then used to project the hyperspectral data over the photogrammetric DSM, producing a georectified end product. The presented photogrammetric processing chain allows fully automated georectification of hyperspectral data using a compact GPS-INS unit while still producingin UAV use higher georeferencing accuracy than would be possible using the traditional processing method. During 2013, we have operated HYMSY on 150+ octocopter flights at 60+ sites or days. On typical flight we have produced for a 2-10ha area: a RGB orthoimagemosaic at 1-5cm resolution, a DSM in 5-10cm resolution, and hyperspectral datacube at 10-50cm resolution. The targets have mostly consisted of vegetated targets including potatoes, wheat, sugar beets, onions, tulips, coral reefs, and heathlands,. In this poster we present the Hyperspectral Mapping System and the photogrammetric processing chain with some of our first mapping results.

  6. UAV-guided navigation for ground robot tele-operation in a military reconnaissance environment.

    Science.gov (United States)

    Chen, Jessie Y C

    2010-08-01

    A military reconnaissance environment was simulated to examine the performance of ground robotics operators who were instructed to utilise streaming video from an unmanned aerial vehicle (UAV) to navigate his/her ground robot to the locations of the targets. The effects of participants' spatial ability on their performance and workload were also investigated. Results showed that participants' overall performance (speed and accuracy) was better when she/he had access to images from larger UAVs with fixed orientations, compared with other UAV conditions (baseline- no UAV, micro air vehicle and UAV with orbiting views). Participants experienced the highest workload when the UAV was orbiting. Those individuals with higher spatial ability performed significantly better and reported less workload than those with lower spatial ability. The results of the current study will further understanding of ground robot operators' target search performance based on streaming video from UAVs. The results will also facilitate the implementation of ground/air robots in military environments and will be useful to the future military system design and training community.

  7. Integration of UAV and ground-based Structure from Motion with Multi-View Stereo photogrammetry and hydrological data to quantify hillslope gully erosion processes in tropical savanna

    Science.gov (United States)

    Koci, J.; Jarihani, B.; Sidle, R. C.; Wilkinson, S. N.; Bartley, R.

    2017-12-01

    Structure from Motion with Multi-View Stereo (SfM-MVS) photogrammetry provides a cost-effective method of rapidly acquiring high resolution (sub-meter) topographic data, but is rarely used in hydrogeomorphic investigations of gully erosion. This study integrates high resolution topographic and land cover data derived from an unmanned aerial vehicle (UAV) and ground-based SfM-MVS photogrammetry, with rainfall and gully discharge data, to elucidate hydrogeomorphic processes driving hillslope gully erosion. The study is located within a small (13 km2) dry-tropical savanna catchment within the Burdekin River Basin, northeast Australia, which is a major contributor sediments and nutrients to the Great Barrier Reef World Heritage Area. A pre-wet season UAV survey covered an entire hillslope gully system (0.715 km2), and is used to derive topography, ground cover and hydrological flow pathways in the gully contributing area. Ground-based surveys of a single active gully (650 m2) within the broader hillslope are compared between pre- and post-wet season conditions to quantify gully geomorphic change. Rainfall, recorded near to the head of the gully, is related to gully discharge during sporadic storm events. The study provides valuable insights into the relationships among hydrological flow pathways, ground cover, rainfall and runoff, and spatial patterns of gully morphologic change. We demonstrate how UAV and ground-based SfM-MVS photogrammetry can be used to improve hydrogeomorphic process understanding and aid in the modelling and management of hillslope gully systems.

  8. a Uav Based 3-D Positioning Framework for Detecting Locations of Buried Persons in Collapsed Disaster Area

    Science.gov (United States)

    Moon, H.; Kim, C.; Lee, W.

    2016-06-01

    Regarding spatial location positioning, indoor location positioning theories based on wireless communication techniques such as Wi-Fi, beacon, UWB and Bluetooth has widely been developing across the world. These techniques are mainly focusing on spatial location detection of customers using fixed wireless APs and unique Tags in the indoor environment. Besides, since existing detection equipment and techniques using ultrasound or sound etc. to detect buried persons and identify survival status for them cause 2nd damages on the collapsed debris for rescuers. In addition, it might take time to check the buried persons. However, the collapsed disaster sites should consider both outdoor and indoor environments because empty spaces under collapsed debris exists. In order to detect buried persons from the empty spaces, we should collect wireless signals with Wi-Fi from their mobile phone. Basically, the Wi-Fi signal measure 2-D location. However, since the buried persons have Z value with burial depth, we also should collect barometer sensor data from their mobile phones in order to measure Z values according to weather conditions. Specially, for quick accessibility to the disaster area, a drone (UAV; Unmanned Arial Vehicle) system, which is equipped with a wireless detection module, was introduced. Using these framework, this study aims to provide the rescuers with effective rescue information by calculating 3-D location for buried persons based on the wireless and barometer sensor fusion.

  9. A UAV BASED 3-D POSITIONING FRAMEWORK FOR DETECTING LOCATIONS OF BURIED PERSONS IN COLLAPSED DISASTER AREA

    Directory of Open Access Journals (Sweden)

    H. Moon

    2016-06-01

    Full Text Available Regarding spatial location positioning, indoor location positioning theories based on wireless communication techniques such as Wi-Fi, beacon, UWB and Bluetooth has widely been developing across the world. These techniques are mainly focusing on spatial location detection of customers using fixed wireless APs and unique Tags in the indoor environment. Besides, since existing detection equipment and techniques using ultrasound or sound etc. to detect buried persons and identify survival status for them cause 2nd damages on the collapsed debris for rescuers. In addition, it might take time to check the buried persons. However, the collapsed disaster sites should consider both outdoor and indoor environments because empty spaces under collapsed debris exists. In order to detect buried persons from the empty spaces, we should collect wireless signals with Wi-Fi from their mobile phone. Basically, the Wi-Fi signal measure 2-D location. However, since the buried persons have Z value with burial depth, we also should collect barometer sensor data from their mobile phones in order to measure Z values according to weather conditions. Specially, for quick accessibility to the disaster area, a drone (UAV; Unmanned Arial Vehicle system, which is equipped with a wireless detection module, was introduced. Using these framework, this study aims to provide the rescuers with effective rescue information by calculating 3-D location for buried persons based on the wireless and barometer sensor fusion.

  10. Saliency Detection and Deep Learning-Based Wildfire Identification in UAV Imagery

    Directory of Open Access Journals (Sweden)

    Yi Zhao

    2018-02-01

    Full Text Available An unmanned aerial vehicle (UAV equipped with global positioning systems (GPS can provide direct georeferenced imagery, mapping an area with high resolution. So far, the major difficulty in wildfire image classification is the lack of unified identification marks, the fire features of color, shape, texture (smoke, flame, or both and background can vary significantly from one scene to another. Deep learning (e.g., DCNN for Deep Convolutional Neural Network is very effective in high-level feature learning, however, a substantial amount of training images dataset is obligatory in optimizing its weights value and coefficients. In this work, we proposed a new saliency detection algorithm for fast location and segmentation of core fire area in aerial images. As the proposed method can effectively avoid feature loss caused by direct resizing; it is used in data augmentation and formation of a standard fire image dataset ‘UAV_Fire’. A 15-layered self-learning DCNN architecture named ‘Fire_Net’ is then presented as a self-learning fire feature exactor and classifier. We evaluated different architectures and several key parameters (drop out ratio, batch size, etc. of the DCNN model regarding its validation accuracy. The proposed architecture outperformed previous methods by achieving an overall accuracy of 98%. Furthermore, ‘Fire_Net’ guarantied an average processing speed of 41.5 ms per image for real-time wildfire inspection. To demonstrate its practical utility, Fire_Net is tested on 40 sampled images in wildfire news reports and all of them have been accurately identified.

  11. An Integrative Object-Based Image Analysis Workflow for Uav Images

    Science.gov (United States)

    Yu, Huai; Yan, Tianheng; Yang, Wen; Zheng, Hong

    2016-06-01

    In this work, we propose an integrative framework to process UAV images. The overall process can be viewed as a pipeline consisting of the geometric and radiometric corrections, subsequent panoramic mosaicking and hierarchical image segmentation for later Object Based Image Analysis (OBIA). More precisely, we first introduce an efficient image stitching algorithm after the geometric calibration and radiometric correction, which employs a fast feature extraction and matching by combining the local difference binary descriptor and the local sensitive hashing. We then use a Binary Partition Tree (BPT) representation for the large mosaicked panoramic image, which starts by the definition of an initial partition obtained by an over-segmentation algorithm, i.e., the simple linear iterative clustering (SLIC). Finally, we build an object-based hierarchical structure by fully considering the spectral and spatial information of the super-pixels and their topological relationships. Moreover, an optimal segmentation is obtained by filtering the complex hierarchies into simpler ones according to some criterions, such as the uniform homogeneity and semantic consistency. Experimental results on processing the post-seismic UAV images of the 2013 Ya'an earthquake demonstrate the effectiveness and efficiency of our proposed method.

  12. AN INTEGRATIVE OBJECT-BASED IMAGE ANALYSIS WORKFLOW FOR UAV IMAGES

    Directory of Open Access Journals (Sweden)

    H. Yu

    2016-06-01

    Full Text Available In this work, we propose an integrative framework to process UAV images. The overall process can be viewed as a pipeline consisting of the geometric and radiometric corrections, subsequent panoramic mosaicking and hierarchical image segmentation for later Object Based Image Analysis (OBIA. More precisely, we first introduce an efficient image stitching algorithm after the geometric calibration and radiometric correction, which employs a fast feature extraction and matching by combining the local difference binary descriptor and the local sensitive hashing. We then use a Binary Partition Tree (BPT representation for the large mosaicked panoramic image, which starts by the definition of an initial partition obtained by an over-segmentation algorithm, i.e., the simple linear iterative clustering (SLIC. Finally, we build an object-based hierarchical structure by fully considering the spectral and spatial information of the super-pixels and their topological relationships. Moreover, an optimal segmentation is obtained by filtering the complex hierarchies into simpler ones according to some criterions, such as the uniform homogeneity and semantic consistency. Experimental results on processing the post-seismic UAV images of the 2013 Ya’an earthquake demonstrate the effectiveness and efficiency of our proposed method.

  13. Uav-Based Detection of Unknown Radioactive Biomass Deposits in Chernobyl's Exclusion Zone

    Science.gov (United States)

    Briechle, S.; Sizov, A.; Tretyak, O.; Antropov, V.; Molitor, N.; Krzystek, P.

    2018-05-01

    Shortly after the explosion of the Chernobyl nuclear power plant (ChNPP) in 1986, radioactive fall-out and contaminated trees (socalled Red Forest) were buried in the Chernobyl Exclusion Zone (ChEZ). These days, exact locations of the buried contaminated material are needed. Moreover, 3D vegetation maps are necessary to simulate the impact of tornados and forest fire. After 30 years, some of the so-called trenches and clamps are visible. However, some of them are overgrown and have slightly settled in the centimeter and decimeter range. This paper presents a pipeline that comprises 3D vegetation mapping and machine learning methods to precisely map trenches and clamps from remote sensing data. The dataset for our experiments consists of UAV-based LiDAR data, multi-spectral data, and aerial gamma-spectrometry data. Depending on the study areas overall accuracies ranging from 95.6 % to 99.0 % were reached for the classification of radioactive deposits. Our first results demonstrate an accurate and reliable UAV-based detection of unknown radioactive biomass deposits in the ChEZ.

  14. UAV-BASED DETECTION OF UNKNOWN RADIOACTIVE BIOMASS DEPOSITS IN CHERNOBYL’S EXCLUSION ZONE

    Directory of Open Access Journals (Sweden)

    S. Briechle

    2018-05-01

    Full Text Available Shortly after the explosion of the Chernobyl nuclear power plant (ChNPP in 1986, radioactive fall-out and contaminated trees (socalled Red Forest were buried in the Chernobyl Exclusion Zone (ChEZ. These days, exact locations of the buried contaminated material are needed. Moreover, 3D vegetation maps are necessary to simulate the impact of tornados and forest fire. After 30 years, some of the so-called trenches and clamps are visible. However, some of them are overgrown and have slightly settled in the centimeter and decimeter range. This paper presents a pipeline that comprises 3D vegetation mapping and machine learning methods to precisely map trenches and clamps from remote sensing data. The dataset for our experiments consists of UAV-based LiDAR data, multi-spectral data, and aerial gamma-spectrometry data. Depending on the study areas overall accuracies ranging from 95.6 % to 99.0 % were reached for the classification of radioactive deposits. Our first results demonstrate an accurate and reliable UAV-based detection of unknown radioactive biomass deposits in the ChEZ.

  15. Attitude Optimal Backstepping Controller Based Quaternion for a UAV

    OpenAIRE

    Djamel, Kaddouri; Abdellah, Mokhtari; Benallegue, Abdelaziz

    2016-01-01

    A hierarchical controller design based on nonlinear H∞ theory and backstepping technique is developed for a nonlinear and coupled dynamic attitude system using conventional quaternion based method. The derived controller combines the attractive features of H∞ optimal controller and the advantages of the backstepping technique leading to a control law which avoids winding phenomena. Performance issues of the controller are illustrated in a simulation study made for a four-rotor vertical take-o...

  16. UAV-Based Photogrammetry and Integrated Technologies for Architectural Applications—Methodological Strategies for the After-Quake Survey of Vertical Structures in Mantua (Italy)

    Science.gov (United States)

    Achille, Cristiana; Adami, Andrea; Chiarini, Silvia; Cremonesi, Stefano; Fassi, Francesco; Fregonese, Luigi; Taffurelli, Laura

    2015-01-01

    This paper examines the survey of tall buildings in an emergency context like in the case of post-seismic events. The after-earthquake survey has to guarantee time-savings, high precision and security during the operational stages. The main goal is to optimize the application of methodologies based on acquisition and automatic elaborations of photogrammetric data even with the use of Unmanned Aerial Vehicle (UAV) systems in order to provide fast and low cost operations. The suggested methods integrate new technologies with commonly used technologies like TLS and topographic acquisition. The value of the photogrammetric application is demonstrated by a test case, based on the comparison of acquisition, calibration and 3D modeling results in case of use of a laser scanner, metric camera and amateur reflex camera. The test would help us to demonstrate the efficiency of image based methods in the acquisition of complex architecture. The case study is Santa Barbara Bell tower in Mantua. The applied survey solution allows a complete 3D database of the complex architectural structure to be obtained for the extraction of all the information needed for significant intervention. This demonstrates the applicability of the photogrammetry using UAV for the survey of vertical structures, complex buildings and difficult accessible architectural parts, providing high precision results. PMID:26134108

  17. UAV-Based Photogrammetry and Integrated Technologies for Architectural Applications—Methodological Strategies for the After-Quake Survey of Vertical Structures in Mantua (Italy

    Directory of Open Access Journals (Sweden)

    Cristiana Achille

    2015-06-01

    Full Text Available This paper examines the survey of tall buildings in an emergency context like in the case of post-seismic events. The after-earthquake survey has to guarantee time-savings, high precision and security during the operational stages. The main goal is to optimize the application of methodologies based on acquisition and automatic elaborations of photogrammetric data even with the use of Unmanned Aerial Vehicle (UAV systems in order to provide fast and low cost operations. The suggested methods integrate new technologies with commonly used technologies like TLS and topographic acquisition. The value of the photogrammetric application is demonstrated by a test case, based on the comparison of acquisition, calibration and 3D modeling results in case of use of a laser scanner, metric camera and amateur reflex camera. The test would help us to demonstrate the efficiency of image based methods in the acquisition of complex architecture. The case study is Santa Barbara Bell tower in Mantua. The applied survey solution allows a complete 3D database of the complex architectural structure to be obtained for the extraction of all the information needed for significant intervention. This demonstrates the applicability of the photogrammetry using UAV for the survey of vertical structures, complex buildings and difficult accessible architectural parts, providing high precision results.

  18. UAV-Based Photogrammetry and Integrated Technologies for Architectural Applications--Methodological Strategies for the After-Quake Survey of Vertical Structures in Mantua (Italy).

    Science.gov (United States)

    Achille, Cristiana; Adami, Andrea; Chiarini, Silvia; Cremonesi, Stefano; Fassi, Francesco; Fregonese, Luigi; Taffurelli, Laura

    2015-06-30

    This paper examines the survey of tall buildings in an emergency context like in the case of post-seismic events. The after-earthquake survey has to guarantee time-savings, high precision and security during the operational stages. The main goal is to optimize the application of methodologies based on acquisition and automatic elaborations of photogrammetric data even with the use of Unmanned Aerial Vehicle (UAV) systems in order to provide fast and low cost operations. The suggested methods integrate new technologies with commonly used technologies like TLS and topographic acquisition. The value of the photogrammetric application is demonstrated by a test case, based on the comparison of acquisition, calibration and 3D modeling results in case of use of a laser scanner, metric camera and amateur reflex camera. The test would help us to demonstrate the efficiency of image based methods in the acquisition of complex architecture. The case study is Santa Barbara Bell tower in Mantua. The applied survey solution allows a complete 3D database of the complex architectural structure to be obtained for the extraction of all the information needed for significant intervention. This demonstrates the applicability of the photogrammetry using UAV for the survey of vertical structures, complex buildings and difficult accessible architectural parts, providing high precision results.

  19. UAV State Estimation Modeling Techniques in AHRS

    Science.gov (United States)

    Razali, Shikin; Zhahir, Amzari

    2017-11-01

    Autonomous unmanned aerial vehicle (UAV) system is depending on state estimation feedback to control flight operation. Estimation on the correct state improves navigation accuracy and achieves flight mission safely. One of the sensors configuration used in UAV state is Attitude Heading and Reference System (AHRS) with application of Extended Kalman Filter (EKF) or feedback controller. The results of these two different techniques in estimating UAV states in AHRS configuration are displayed through position and attitude graphs.

  20. Attitude Optimal Backstepping Controller Based Quaternion for a UAV

    Directory of Open Access Journals (Sweden)

    Kaddouri Djamel

    2016-01-01

    Full Text Available A hierarchical controller design based on nonlinear H∞ theory and backstepping technique is developed for a nonlinear and coupled dynamic attitude system using conventional quaternion based method. The derived controller combines the attractive features of H∞ optimal controller and the advantages of the backstepping technique leading to a control law which avoids winding phenomena. Performance issues of the controller are illustrated in a simulation study made for a four-rotor vertical take-off and landing (VTOL aerial robot prototype known as the quadrotor aircraft.

  1. Modeling and Testing of Growth Status for Chinese Cabbage and White Radish with UAV-Based RGB Imagery

    Directory of Open Access Journals (Sweden)

    Dong-Wook Kim

    2018-04-01

    Full Text Available Conventional crop-monitoring methods are time-consuming and labor-intensive, necessitating new techniques to provide faster measurements and higher sampling intensity. This study reports on mathematical modeling and testing of growth status for Chinese cabbage and white radish using unmanned aerial vehicle-red, green and blue (UAV-RGB imagery for measurement of their biophysical properties. Chinese cabbage seedlings and white radish seeds were planted at 7–10-day intervals to provide a wide range of growth rates. Remotely sensed digital imagery data were collected for test fields at approximately one-week intervals using a UAV platform equipped with an RGB digital camera flying at 2 m/s at 20 m above ground. Radiometric calibrations for the RGB band sensors were performed on every UAV flight using standard calibration panels to minimize the effect of ever-changing light conditions on the RGB images. Vegetation fractions (VFs of crops in each region of interest from the mosaicked ortho-images were calculated as the ratio of pixels classified as crops segmented using the Otsu threshold method and a vegetation index of excess green (ExG. Plant heights (PHs were estimated using the structure from motion (SfM algorithm to create 3D surface models from crop canopy data. Multiple linear regression equations consisting of three predictor variables (VF, PH, and VF × PH and four different response variables (fresh weight, leaf length, leaf width, and leaf count provided good fits with coefficients of determination (R2 ranging from 0.66 to 0.90. The validation results using a dataset of crop growth obtained in a different year also showed strong linear relationships (R2 > 0.76 between the developed regression models and standard methods, confirming that the models make it possible to use UAV-RGB images for quantifying spatial and temporal variability in biophysical properties of Chinese cabbage and white radish over the growing season.

  2. Port-based Telemanipulation Control of Underactuated Flying Vehicles

    NARCIS (Netherlands)

    Mersha, A.Y.; Carloni, Raffaella; Stramigioli, Stefano

    2011-01-01

    Recently, the interest in the field of unmanned aerial vehicles (UAVs) is increasing due to the existence of diverse potential applications in civilian sector. These applications often require high level reasoning, which, in some cases, need specialist in the led. The step forward towards achieving

  3. Use of unmanned aerial vehicle (UAV) for the detection and surveillance of marine oil spills in the Belgian part of the North Sea

    International Nuclear Information System (INIS)

    Donnay, E.

    2009-01-01

    This paper discussed the use of unmanned aerial vehicles (UAV) deployed by the Belgian Army in order to detect oil spills as well as for intelligence, reconnaissance and surveillance missions. The UAV are fitted with a dual sensor gyro-stabilized turret which combines a daylight camera and a thermal infrared camera. Live images of the sensors are transmitted in real time to control stations. All Belgian marine pollution surveillance platforms are coordinated by the Maritime Security Center of the Belgian Coast Guard. Satellite surveillance services provide real time information related to potential oil spills and other anomalies on the sea surface. Stand-by helicopters are also used for the rapid assessment of reported spills. The B-Hunter system is undetectable due to its small size and low noise signature, and can be used for the continuous monitoring of specific areas or for the tracking of suspect vessels. The system will also be used to monitor the progress of oil spill response operations as well as to provide information and guidance to response vessels. 6 refs., 2 figs

  4. Use of unmanned aerial vehicle (UAV) for the detection and surveillance of marine oil spills in the Belgian part of the North Sea

    Energy Technology Data Exchange (ETDEWEB)

    Donnay, E. [Federal Public Service Health, Food Chain Safety and Environment, Brussels (Belgium)

    2009-07-01

    This paper discussed the use of unmanned aerial vehicles (UAV) deployed by the Belgian Army in order to detect oil spills as well as for intelligence, reconnaissance and surveillance missions. The UAV are fitted with a dual sensor gyro-stabilized turret which combines a daylight camera and a thermal infrared camera. Live images of the sensors are transmitted in real time to control stations. All Belgian marine pollution surveillance platforms are coordinated by the Maritime Security Center of the Belgian Coast Guard. Satellite surveillance services provide real time information related to potential oil spills and other anomalies on the sea surface. Stand-by helicopters are also used for the rapid assessment of reported spills. The B-Hunter system is undetectable due to its small size and low noise signature, and can be used for the continuous monitoring of specific areas or for the tracking of suspect vessels. The system will also be used to monitor the progress of oil spill response operations as well as to provide information and guidance to response vessels. 6 refs., 2 figs.

  5. Comparing and combining terrestrial laser scanning with ground-and UAV-based imaging for national-level assessment of soil erosion

    Science.gov (United States)

    McShane, Gareth; James, Mike R.; Quinton, John; Anderson, Karen; DeBell, Leon; Evans, Martin; Farrow, Luke; Glendell, Miriam; Jones, Lee; Kirkham, Matthew; Lark, Murray; Rawlins, Barry; Rickson, Jane; Quine, Tim; Wetherelt, Andy; Brazier, Richard

    2014-05-01

    3D topographic or surface models are increasingly being utilised for a wide range of applications and are established tools in geomorphological research. In this pilot study 'a cost effective framework for monitoring soil erosion in England and Wales', funded by the UK Department for Environment, Food and Rural Affairs (Defra), we compare methods of collecting topographic measurements via remote sensing for detailed studies of dynamic processes such as erosion and mass movement. The techniques assessed are terrestrial laser scanning (TLS), and unmanned aerial vehicle (UAV) photography and ground-based photography, processed using structure-from-motion (SfM) 3D reconstruction software. The methods will be applied in regions of different land use, including arable and horticultural, upland and semi natural habitats, and grassland, to quantify visible erosion pathways at the site scale. Volumetric estimates of soil loss will be quantified using the digital surface models (DSMs) provided by each technique and a modelled pre-erosion surface. Visible erosion and severity will be independently established through each technique, with their results compared and combined effectiveness assessed. A fixed delta-wing UAV (QuestUAV, http://www.questuav.com/) captures photos from a range of altitudes and angles over the study area, with automated SfM-based processing enabling rapid orthophoto production to support ground-based data acquisition. At sites with suitable scale erosion features, UAV data will also provide a DSM for volume loss measurement. Terrestrial laser scanning will provide detailed, accurate, high density measurements of the ground surface over long (100s m) distances. Ground-based photography is anticipated to be most useful for characterising small and difficult to view features. By using a consumer-grade digital camera and an SfM-based approach (using Agisoft Photoscan version 1.0.0, http://www.agisoft.ru/products/photoscan/), less expertise and fewer control

  6. Thermocouple-based Temperature Sensing System for Chemical Cell Inside Micro UAV Device

    Science.gov (United States)

    Han, Yanhui; Feng, Yue; Lou, Haozhe; Zhang, Xinzhao

    2018-03-01

    Environmental temperature of UAV system is crucial for chemical cell component inside. Once the temperature of this chemical cell is over 259 °C and keeps more than 20 min, the high thermal accumulation would result in an explosion, which seriously damage the whole UAV system. Therefore, we develop a micro temperature sensing system for monitoring the temperature of chemical cell thermally influenced by UAV device deployed in a 300 °C temperature environment, which is quite useful for insensitive munitions and UAV safety enhancement technologies.

  7. Application of Artificial Intelligence Techniques in Uninhabited Aerial Vehicle Flight

    Science.gov (United States)

    Dufrene, Warren R., Jr.

    2004-01-01

    This paper describes the development of an application of Artificial Intelligence (AI) for Unmanned Aerial Vehicle (UAV) control. The project was done as part of the requirements for a class in AI at NOVA Southeastearn University and a beginning project at NASA Wallops Flight Facility for a resilient, robust, and intelligent UAV flight control system. A method is outlined which allows a base level application for applying an Artificial Intelligence method, Fuzzy Logic, to aspects of Control Logic for UAV flight. One element of UAV flight, automated altitude hold, has been implemented and preliminary results displayed.

  8. Application of Artificial Intelligence Techniques in Uninhabitated Aerial Vehicle Flight

    Science.gov (United States)

    Dufrene, Warren R., Jr.

    2003-01-01

    This paper describes the development of an application of Artificial Intelligence (AI) for Unmanned Aerial Vehicle (UAV) control. The project was done as part of the requirements for a class in AI at NOVA southeastern University and a beginning project at NASA Wallops Flight Facility for a resilient, robust, and intelligent UAV flight control system. A method is outlined which allows a base level application for applying an Artificial Intelligence method, Fuzzy Logic, to aspects of Control Logic for UAV flight. One element of UAV flight, automated altitude hold, has been implemented and preliminary results displayed.

  9. Assessment of Photogrammetric Mapping Accuracy Based on Variation Flying Altitude Using Unmanned Aerial Vehicle

    International Nuclear Information System (INIS)

    Udin, W S; Ahmad, A

    2014-01-01

    Photogrammetry is the earliest technique used to collect data for topographic mapping. The recent development in aerial photogrammetry is the used of large format digital aerial camera for producing topographic map. The aerial photograph can be in the form of metric or non-metric imagery. The cost of mapping using aerial photogrammetry is very expensive. In certain application, there is a need to map small area with limited budget. Due to the development of technology, small format aerial photogrammetry technology has been introduced and offers many advantages. Currently, digital map can be extracted from digital aerial imagery of small format camera mounted on light weight platform such as unmanned aerial vehicle (UAV). This study utilizes UAV system for large scale stream mapping. The first objective of this study is to investigate the use of light weight rotary-wing UAV for stream mapping based on different flying height. Aerial photograph were acquired at 60% forward lap and 30% sidelap specifications. Ground control points and check points were established using Total Station technique. The digital camera attached to the UAV was calibrated and the recovered camera calibration parameters were then used in the digital images processing. The second objective is to determine the accuracy of the photogrammetric output. In this study, the photogrammetric output such as stereomodel in three dimensional (3D), contour lines, digital elevation model (DEM) and orthophoto were produced from a small stream of 200m long and 10m width. The research output is evaluated for planimetry and vertical accuracy using root mean square error (RMSE). Based on the finding, sub-meter accuracy is achieved and the RMSE value decreases as the flying height increases. The difference is relatively small. Finally, this study shows that UAV is very useful platform for obtaining aerial photograph and subsequently used for photogrammetric mapping and other applications

  10. Spurious RF signals emitted by mini-UAVs

    NARCIS (Netherlands)

    Schleijpen, R.; Voogt, V.; Zwamborn, P.; Oever, J. van den

    2016-01-01

    This paper presents experimental work on the detection of spurious RF emissions of mini Unmanned Aerial Vehicles (mini-UAV). Many recent events have shown that mini-UAVs can be considered as a potential threat for civil security. For this reason the detection of mini-UAVs has become of interest to

  11. Vision-Based SLAM System for Unmanned Aerial Vehicles

    Directory of Open Access Journals (Sweden)

    Rodrigo Munguía

    2016-03-01

    Full Text Available The present paper describes a vision-based simultaneous localization and mapping system to be applied to Unmanned Aerial Vehicles (UAVs. The main contribution of this work is to propose a novel estimator relying on an Extended Kalman Filter. The estimator is designed in order to fuse the measurements obtained from: (i an orientation sensor (AHRS; (ii a position sensor (GPS; and (iii a monocular camera. The estimated state consists of the full state of the vehicle: position and orientation and their first derivatives, as well as the location of the landmarks observed by the camera. The position sensor will be used only during the initialization period in order to recover the metric scale of the world. Afterwards, the estimated map of landmarks will be used to perform a fully vision-based navigation when the position sensor is not available. Experimental results obtained with simulations and real data show the benefits of the inclusion of camera measurements into the system. In this sense the estimation of the trajectory of the vehicle is considerably improved, compared with the estimates obtained using only the measurements from the position sensor, which are commonly low-rated and highly noisy.

  12. Vision-Based SLAM System for Unmanned Aerial Vehicles.

    Science.gov (United States)

    Munguía, Rodrigo; Urzua, Sarquis; Bolea, Yolanda; Grau, Antoni

    2016-03-15

    The present paper describes a vision-based simultaneous localization and mapping system to be applied to Unmanned Aerial Vehicles (UAVs). The main contribution of this work is to propose a novel estimator relying on an Extended Kalman Filter. The estimator is designed in order to fuse the measurements obtained from: (i) an orientation sensor (AHRS); (ii) a position sensor (GPS); and (iii) a monocular camera. The estimated state consists of the full state of the vehicle: position and orientation and their first derivatives, as well as the location of the landmarks observed by the camera. The position sensor will be used only during the initialization period in order to recover the metric scale of the world. Afterwards, the estimated map of landmarks will be used to perform a fully vision-based navigation when the position sensor is not available. Experimental results obtained with simulations and real data show the benefits of the inclusion of camera measurements into the system. In this sense the estimation of the trajectory of the vehicle is considerably improved, compared with the estimates obtained using only the measurements from the position sensor, which are commonly low-rated and highly noisy.

  13. Aeromagnetic Compensation for UAVs

    Science.gov (United States)

    Naprstek, T.; Lee, M. D.

    2017-12-01

    Aeromagnetic data is one of the most widely collected types of data in exploration geophysics. With the continuing prevalence of unmanned air vehicles (UAVs) in everyday life there is a strong push for aeromagnetic data collection using UAVs. However, apart from the many political and legal barriers to overcome in the development of UAVs as aeromagnetic data collection platforms, there are also significant scientific hurdles, primary of which is magnetic compensation. This is a well-established process in manned aircraft achieved through a combination of platform magnetic de-noising and compensation routines. However, not all of this protocol can be directly applied to UAVs due to fundamental differences in the platforms, most notably the decrease in scale causing magnetometers to be significantly closer to the avionics. As such, the methodology must be suitably adjusted. The National Research Council of Canada has collaborated with Aeromagnetic Solutions Incorporated to develop a standardized approach to de-noising and compensating UAVs, which is accomplished through a series of static and dynamic experiments. On the ground, small static tests are conducted on individual components to determine their magnetization. If they are highly magnetic, they are removed, demagnetized, or characterized such that they can be accounted for in the compensation. Dynamic tests can include measuring specific components as they are powered on and off to assess their potential effect on airborne data. The UAV is then flown, and a modified compensation routine is applied. These modifications include utilizing onboard autopilot current sensors as additional terms in the compensation algorithm. This process has been applied with success to fixed-wing and rotary-wing platforms, with both a standard manned-aircraft magnetometer, as well as a new atomic magnetometer, much smaller in scale.

  14. Adaptation of Dubins Paths for UAV Ground Obstacle Avoidance When Using a Low Cost On-Board GNSS Sensor.

    Science.gov (United States)

    Kikutis, Ramūnas; Stankūnas, Jonas; Rudinskas, Darius; Masiulionis, Tadas

    2017-09-28

    Current research on Unmanned Aerial Vehicles (UAVs) shows a lot of interest in autonomous UAV navigation. This interest is mainly driven by the necessity to meet the rules and restrictions for small UAV flights that are issued by various international and national legal organizations. In order to lower these restrictions, new levels of automation and flight safety must be reached. In this paper, a new method for ground obstacle avoidance derived by using UAV navigation based on the Dubins paths algorithm is presented. The accuracy of the proposed method has been tested, and research results have been obtained by using Software-in-the-Loop (SITL) simulation and real UAV flights, with the measurements done with a low cost Global Navigation Satellite System (GNSS) sensor. All tests were carried out in a three-dimensional space, but the height accuracy was not assessed. The GNSS navigation data for the ground obstacle avoidance algorithm is evaluated statistically.

  15. Adaptation of Dubins Paths for UAV Ground Obstacle Avoidance When Using a Low Cost On-Board GNSS Sensor

    Directory of Open Access Journals (Sweden)

    Ramūnas Kikutis

    2017-09-01

    Full Text Available Current research on Unmanned Aerial Vehicles (UAVs shows a lot of interest in autonomous UAV navigation. This interest is mainly driven by the necessity to meet the rules and restrictions for small UAV flights that are issued by various international and national legal organizations. In order to lower these restrictions, new levels of automation and flight safety must be reached. In this paper, a new method for ground obstacle avoidance derived by using UAV navigation based on the Dubins paths algorithm is presented. The accuracy of the proposed method has been tested, and research results have been obtained by using Software-in-the-Loop (SITL simulation and real UAV flights, with the measurements done with a low cost Global Navigation Satellite System (GNSS sensor. All tests were carried out in a three-dimensional space, but the height accuracy was not assessed. The GNSS navigation data for the ground obstacle avoidance algorithm is evaluated statistically.

  16. Sensor-Oriented Path Planning for Multiregion Surveillance with a Single Lightweight UAV SAR.

    Science.gov (United States)

    Li, Jincheng; Chen, Jie; Wang, Pengbo; Li, Chunsheng

    2018-02-11

    In the surveillance of interested regions by unmanned aerial vehicle (UAV), system performance relies greatly on the motion control strategy of the UAV and the operation characteristics of the onboard sensors. This paper investigates the 2D path planning problem for the lightweight UAV synthetic aperture radar (SAR) system in an environment of multiple regions of interest (ROIs), the sizes of which are comparable to the radar swath width. Taking into account the special requirements of the SAR system on the motion of the platform, we model path planning for UAV SAR as a constrained multiobjective optimization problem (MOP). Based on the fact that the UAV route can be designed in the map image, an image-based path planner is proposed in this paper. First, the neighboring ROIs are merged by the morphological operation. Then, the parts of routes for data collection of the ROIs can be located according to the geometric features of the ROIs and the observation geometry of UAV SAR. Lastly, the route segments for ROIs surveillance are connected by a path planning algorithm named the sampling-based sparse A* search (SSAS) algorithm. Simulation experiments in real scenarios demonstrate that the proposed sensor-oriented path planner can improve the reconnaissance performance of lightweight UAV SAR greatly compared with the conventional zigzag path planner.

  17. Sensor-Oriented Path Planning for Multiregion Surveillance with a Single Lightweight UAV SAR

    Science.gov (United States)

    Li, Jincheng; Chen, Jie; Wang, Pengbo; Li, Chunsheng

    2018-01-01

    In the surveillance of interested regions by unmanned aerial vehicle (UAV), system performance relies greatly on the motion control strategy of the UAV and the operation characteristics of the onboard sensors. This paper investigates the 2D path planning problem for the lightweight UAV synthetic aperture radar (SAR) system in an environment of multiple regions of interest (ROIs), the sizes of which are comparable to the radar swath width. Taking into account the special requirements of the SAR system on the motion of the platform, we model path planning for UAV SAR as a constrained multiobjective optimization problem (MOP). Based on the fact that the UAV route can be designed in the map image, an image-based path planner is proposed in this paper. First, the neighboring ROIs are merged by the morphological operation. Then, the parts of routes for data collection of the ROIs can be located according to the geometric features of the ROIs and the observation geometry of UAV SAR. Lastly, the route segments for ROIs surveillance are connected by a path planning algorithm named the sampling-based sparse A* search (SSAS) algorithm. Simulation experiments in real scenarios demonstrate that the proposed sensor-oriented path planner can improve the reconnaissance performance of lightweight UAV SAR greatly compared with the conventional zigzag path planner. PMID:29439447

  18. Ground Stereo Vision-Based Navigation for Autonomous Take-off and Landing of UAVs: A Chan-Vese Model Approach

    Directory of Open Access Journals (Sweden)

    Dengqing Tang

    2016-04-01

    Full Text Available This article aims at flying target detection and localization of a fixed-wing unmanned aerial vehicle (UAV autonomous take-off and landing within Global Navigation Satellite System (GNSS-denied environments. A Chan-Vese model–based approach is proposed and developed for ground stereo vision detection. Extended Kalman Filter (EKF is fused into state estimation to reduce the localization inaccuracy caused by measurement errors of object detection and Pan-Tilt unit (PTU attitudes. Furthermore, the region-of-interest (ROI setting up is conducted to improve the real-time capability. The present work contributes to real-time, accurate and robust features, compared with our previous works. Both offline and online experimental results validate the effectiveness and better performances of the proposed method against the traditional triangulation-based localization algorithm.

  19. Intercomparison of unmanned aerial vehicle and ground-based narrow band spectrometers applied to crop trait monitoring in organic potato production

    NARCIS (Netherlands)

    Domingues Franceschini, Marston; Bartholomeus, Harm; Apeldoorn, van Dirk; Suomalainen, Juha; Kooistra, Lammert

    2017-01-01

    Vegetation properties can be estimated using optical sensors, acquiring data on board of different platforms. For instance, ground-based and Unmanned Aerial Vehicle (UAV)-borne spectrometers can measure reflectance in narrow spectral bands, while different modelling approaches, like regressions

  20. UAV-Based Estimation of Carbon Exports from Heterogeneous Soil Landscapes--A Case Study from the CarboZALF Experimental Area.

    Science.gov (United States)

    Wehrhan, Marc; Rauneker, Philipp; Sommer, Michael

    2016-02-19

    The advantages of remote sensing using Unmanned Aerial Vehicles (UAVs) are a high spatial resolution of images, temporal flexibility and narrow-band spectral data from different wavelengths domains. This enables the detection of spatio-temporal dynamics of environmental variables, like plant-related carbon dynamics in agricultural landscapes. In this paper, we quantify spatial patterns of fresh phytomass and related carbon (C) export using imagery captured by a 12-band multispectral camera mounted on the fixed wing UAV Carolo P360. The study was performed in 2014 at the experimental area CarboZALF-D in NE Germany. From radiometrically corrected and calibrated images of lucerne (Medicago sativa), the performance of four commonly used vegetation indices (VIs) was tested using band combinations of six near-infrared bands. The highest correlation between ground-based measurements of fresh phytomass of lucerne and VIs was obtained for the Enhanced Vegetation Index (EVI) using near-infrared band b899. The resulting map was transformed into dry phytomass and finally upscaled to total C export by harvest. The observed spatial variability at field- and plot-scale could be attributed to small-scale soil heterogeneity in part.

  1. FluidCam 1&2 - UAV-based Fluid Lensing Instruments for High-Resolution 3D Subaqueous Imaging and Automated Remote Biosphere Assessment of Reef Ecosystems

    Science.gov (United States)

    Chirayath, V.; Instrella, R.

    2016-02-01

    We present NASA ESTO FluidCam 1 & 2, Visible and NIR Fluid-Lensing-enabled imaging payloads for Unmanned Aerial Vehicles (UAVs). Developed as part of a focused 2014 earth science technology grant, FluidCam 1&2 are Fluid-Lensing-based computational optical imagers designed for automated 3D mapping and remote sensing of underwater coastal targets from airborne platforms. Fluid Lensing has been used to map underwater reefs in 3D in American Samoa and Hamelin Pool, Australia from UAV platforms at sub-cm scale, which has proven a valuable tool in modern marine research for marine biosphere assessment and conservation. We share FluidCam 1&2 instrument validation and testing results as well as preliminary processed data from field campaigns. Petabyte-scale aerial survey efforts using Fluid Lensing to image at-risk reefs demonstrate broad applicability to large-scale automated species identification, morphology studies and reef ecosystem characterization for shallow marine environments and terrestrial biospheres, of crucial importance to improving bathymetry data for physical oceanographic models and understanding climate change's impact on coastal zones, global oxygen production, carbon sequestration.

  2. SLIC superpixels for object delineation UAV data

    NARCIS (Netherlands)

    Crommelinck, Sophie Charlotte; Bennett, R.M.; Gerke, Markus; Koeva, M.N.; Yang, M.Y.; Vosselman, G.; Stachniss, C.; Förstner, W.; Schneider, J.

    2017-01-01

    Unmanned aerial vehicles (UAV) are increasingly investigated with regard to their potential to create and update (cadastral) maps. UAVs provide a flexible and low-cost platform for high-resolution data, from which object outlines can be accurately delineated. This delineation could be automated with

  3. Applications of advanced sensors on unmanned aerial vehicles (UAV's) for the protection of high value targets and support of response forces

    International Nuclear Information System (INIS)

    Oppenheimer, D.; Morf, M.; Schleicher, S.

    2005-01-01

    Full text: Fixed imaging systems using visible light cameras typically meet the security needs of conventional facilities that are concerned primarily with asset protection. Facilities where enhanced security needs are both to protect the facility and the theft of valuable assets may choose to use thermal imaging forward looking infrared (FLIR) cameras in addition to visible light cameras. These FLIR cameras provide a 'hot' target in very low light conditions or when camouflaged as well as the heat signatures of people and vehicles. These imagers are usually in fixed points of view and can scan areas of a scene. The cost of thermal cameras often means that a few selected points have this capability and the majority of cameras are visible light only. Non-conventional facilities managing nuclear power, processing, or storage of nuclear materials may find fixed camera systems inadequate. Attackers have evaluated camera locations and often understand the limitations of such systems. In addition using these two imaging options does not provide the command and control structure or the response force with adequate situational awareness of the threats they face. The presence of chemicals not observable using the visible or thermal IR cameras such as nerve agents or other dangerous gases could be used as a mechanism to disable reaction forces and as a force multiplier for the attackers. These same visible, thermal infrared cameras with the addition of a hyperspectral sensor on an unmanned aerial vehicle (UAV) such as a General Atomics Predator (RQ-1) can provide significant standoff capabilities with an unpredictability of camera view by the attackers and close the gap between visible and thermal imaging systems. Such a system could be flown at a particular altitude to avoid detection by the attackers and conflict with response force aircraft entering the area. This enhanced spectral information will allow better command decisions as well as providing real-time fused

  4. Comparisons of feature extraction algorithm based on unmanned aerial vehicle image

    Directory of Open Access Journals (Sweden)

    Xi Wenfei

    2017-07-01

    Full Text Available Feature point extraction technology has become a research hotspot in the photogrammetry and computer vision. The commonly used point feature extraction operators are SIFT operator, Forstner operator, Harris operator and Moravec operator, etc. With the high spatial resolution characteristics, UAV image is different from the traditional aviation image. Based on these characteristics of the unmanned aerial vehicle (UAV, this paper uses several operators referred above to extract feature points from the building images, grassland images, shrubbery images, and vegetable greenhouses images. Through the practical case analysis, the performance, advantages, disadvantages and adaptability of each algorithm are compared and analyzed by considering their speed and accuracy. Finally, the suggestions of how to adapt different algorithms in diverse environment are proposed.

  5. From random process to chaotic behavior in swarms of UAVs

    OpenAIRE

    Rosalie , Martin; Danoy , Grégoire; Chaumette , Serge; Bouvry , Pascal

    2016-01-01

    International audience; Unmanned Aerial Vehicles (UAVs) applications have seen an important increase in the last decade for both military and civilian applications ranging from fire and high seas rescue to military surveillance and target detection. While this technology is now mature for a single UAV, new methods are needed to operate UAVs in swarms, also referred to as fleets. This work focuses on the mobility management of one single autonomous swarm of UAVs which mission is to cover a giv...

  6. Ubiquitous UAVs: a cloud based framework for storing, accessing and processing huge amount of video footage in an efficient way

    Science.gov (United States)

    Efstathiou, Nectarios; Skitsas, Michael; Psaroudakis, Chrysostomos; Koutras, Nikolaos

    2017-09-01

    Nowadays, video surveillance cameras are used for the protection and monitoring of a huge number of facilities worldwide. An important element in such surveillance systems is the use of aerial video streams originating from onboard sensors located on Unmanned Aerial Vehicles (UAVs). Video surveillance using UAVs represent a vast amount of video to be transmitted, stored, analyzed and visualized in a real-time way. As a result, the introduction and development of systems able to handle huge amount of data become a necessity. In this paper, a new approach for the collection, transmission and storage of aerial videos and metadata is introduced. The objective of this work is twofold. First, the integration of the appropriate equipment in order to capture and transmit real-time video including metadata (i.e. position coordinates, target) from the UAV to the ground and, second, the utilization of the ADITESS Versatile Media Content Management System (VMCMS-GE) for storing of the video stream and the appropriate metadata. Beyond the storage, VMCMS-GE provides other efficient management capabilities such as searching and processing of videos, along with video transcoding. For the evaluation and demonstration of the proposed framework we execute a use case where the surveillance of critical infrastructure and the detection of suspicious activities is performed. Collected video Transcodingis subject of this evaluation as well.

  7. UAV Swarm Tactics: An Agent-Based Simulation and Markov Process Analysis

    Science.gov (United States)

    2013-06-01

    research UAV platforms, namely the (a) Procerus Unicorn UAV and (b) modified Ritewing ZephyrII RC plane, for ongoing live-fly field experimentation of the...number of possible states would grow exponentially, but short excursions with baseline two-on-one models, as found in the literature, could provide

  8. Estimating Biomass of Barley Using Crop Surface Models (CSMs Derived from UAV-Based RGB Imaging

    Directory of Open Access Journals (Sweden)

    Juliane Bendig

    2014-10-01

    Full Text Available Crop monitoring is important in precision agriculture. Estimating above-ground biomass helps to monitor crop vitality and to predict yield. In this study, we estimated fresh and dry biomass on a summer barley test site with 18 cultivars and two nitrogen (N-treatments using the plant height (PH from crop surface models (CSMs. The super-high resolution, multi-temporal (1 cm/pixel CSMs were derived from red, green, blue (RGB images captured from a small unmanned aerial vehicle (UAV. Comparison with PH reference measurements yielded an R2 of 0.92. The test site with different cultivars and treatments was monitored during “Biologische Bundesanstalt, Bundessortenamt und CHemische Industrie” (BBCH Stages 24–89. A high correlation was found between PH from CSMs and fresh biomass (R2 = 0.81 and dry biomass (R2 = 0.82. Five models for above-ground fresh and dry biomass estimation were tested by cross-validation. Modelling biomass between different N-treatments for fresh biomass produced the best results (R2 = 0.71. The main limitation was the influence of lodging cultivars in the later growth stages, producing irregular plant heights. The method has potential for future application by non-professionals, i.e., farmers.

  9. Development of an innovative uav-mounted screening tool for landfill gas emissions

    DEFF Research Database (Denmark)

    Fjelsted, Lotte; Thomasen, T. B.; Valbjørn, I. L.

    2015-01-01

    Identification of landfill gas emission hot spots are potentially a very time consuming process, and the use of an Unmanned Aerial Vehicle (UAV) based screening tool could be an effective investigation strategy. In this study, the potential use of a long-wave thermal infrared camera was investiga......Identification of landfill gas emission hot spots are potentially a very time consuming process, and the use of an Unmanned Aerial Vehicle (UAV) based screening tool could be an effective investigation strategy. In this study, the potential use of a long-wave thermal infrared camera...

  10. A proposed UAV for indoor patient care.

    Science.gov (United States)

    Todd, Catherine; Watfa, Mohamed; El Mouden, Yassine; Sahir, Sana; Ali, Afrah; Niavarani, Ali; Lutfi, Aoun; Copiaco, Abigail; Agarwal, Vaibhavi; Afsari, Kiyan; Johnathon, Chris; Okafor, Onyeka; Ayad, Marina

    2015-09-10

    Indoor flight, obstacle avoidance and client-server communication of an Unmanned Aerial Vehicle (UAV) raises several unique research challenges. This paper examines current methods and associated technologies adapted within the literature toward autonomous UAV flight, for consideration in a proposed system for indoor healthcare administration with a quadcopter. We introduce Healthbuddy, a unique research initiative towards overcoming challenges associated with indoor navigation, collision detection and avoidance, stability, wireless drone-server communications and automated decision support for patient care in a GPS-denied environment. To address the identified research deficits, a drone-based solution is presented. The solution is preliminary as we develop and refine the suggested algorithms and hardware system to achieve the research objectives.

  11. Hankel Matrix Correlation Function-Based Subspace Identification Method for UAV Servo System

    Directory of Open Access Journals (Sweden)

    Minghong She

    2018-01-01

    Full Text Available For the identification problem of closed-loop subspace model, we propose a zero space projection method based on the estimation of correlation function to fill the block Hankel matrix of identification model by combining the linear algebra with geometry. By using the same projection of related data in time offset set and LQ decomposition, the multiplication operation of projection is achieved and dynamics estimation of the unknown equipment system model is obtained. Consequently, we have solved the problem of biased estimation caused when the open-loop subspace identification algorithm is applied to the closed-loop identification. A simulation example is given to show the effectiveness of the proposed approach. In final, the practicability of the identification algorithm is verified by hardware test of UAV servo system in real environment.

  12. The orthorectified technology for UAV aerial remote sensing image based on the Programmable GPU

    International Nuclear Information System (INIS)

    Jin, Liu; Ying-cheng, Li; De-long, Li; Chang-sheng, Teng; Wen-hao, Zhang

    2014-01-01

    Considering the time requirements of the disaster emergency aerial remote sensing data acquisition and processing, this paper introduced the GPU parallel processing in orthorectification algorithm. Meanwhile, our experiments verified the correctness and feasibility of CUDA parallel processing algorithm, and the algorithm can effectively solve the problem of calculation large, time-consuming for ortho rectification process, realized fast processing of UAV airborne remote sensing image orthorectification based on GPU. The experimental results indicate that using the assumption of same accuracy of proposed method with CPU, the processing time is reduced obviously, maximum acceleration can reach more than 12 times, which greatly enhances the emergency surveying and mapping processing of rapid reaction rate, and has a broad application

  13. Accuracy assessment of topographic mapping using UAV image integrated with satellite images

    International Nuclear Information System (INIS)

    Azmi, S M; Ahmad, Baharin; Ahmad, Anuar

    2014-01-01

    Unmanned Aerial Vehicle or UAV is extensively applied in various fields such as military applications, archaeology, agriculture and scientific research. This study focuses on topographic mapping and map updating. UAV is one of the alternative ways to ease the process of acquiring data with lower operating costs, low manufacturing and operational costs, plus it is easy to operate. Furthermore, UAV images will be integrated with QuickBird images that are used as base maps. The objective of this study is to make accuracy assessment and comparison between topographic mapping using UAV images integrated with aerial photograph and satellite image. The main purpose of using UAV image is as a replacement for cloud covered area which normally exists in aerial photograph and satellite image, and for updating topographic map. Meanwhile, spatial resolution, pixel size, scale, geometric accuracy and correction, image quality and information contents are important requirements needed for the generation of topographic map using these kinds of data. In this study, ground control points (GCPs) and check points (CPs) were established using real time kinematic Global Positioning System (RTK-GPS) technique. There are two types of analysis that are carried out in this study which are quantitative and qualitative assessments. Quantitative assessment is carried out by calculating root mean square error (RMSE). The outputs of this study include topographic map and orthophoto. From this study, the accuracy of UAV image is ± 0.460 m. As conclusion, UAV image has the potential to be used for updating of topographic maps

  14. Use of Model-Based Design Methods for Enhancing Resiliency Analysis of Unmanned Aerial Vehicles

    Science.gov (United States)

    Knox, Lenora A.

    The most common traditional non-functional requirement analysis is reliability. With systems becoming more complex, networked, and adaptive to environmental uncertainties, system resiliency has recently become the non-functional requirement analysis of choice. Analysis of system resiliency has challenges; which include, defining resilience for domain areas, identifying resilience metrics, determining resilience modeling strategies, and understanding how to best integrate the concepts of risk and reliability into resiliency. Formal methods that integrate all of these concepts do not currently exist in specific domain areas. Leveraging RAMSoS, a model-based reliability analysis methodology for Systems of Systems (SoS), we propose an extension that accounts for resiliency analysis through evaluation of mission performance, risk, and cost using multi-criteria decision-making (MCDM) modeling and design trade study variability modeling evaluation techniques. This proposed methodology, coined RAMSoS-RESIL, is applied to a case study in the multi-agent unmanned aerial vehicle (UAV) domain to investigate the potential benefits of a mission architecture where functionality to complete a mission is disseminated across multiple UAVs (distributed) opposed to being contained in a single UAV (monolithic). The case study based research demonstrates proof of concept for the proposed model-based technique and provides sufficient preliminary evidence to conclude which architectural design (distributed vs. monolithic) is most resilient based on insight into mission resilience performance, risk, and cost in addition to the traditional analysis of reliability.

  15. Real-time UAV trajectory generation using feature points matching between video image sequences

    Science.gov (United States)

    Byun, Younggi; Song, Jeongheon; Han, Dongyeob

    2017-09-01

    Unmanned aerial vehicles (UAVs), equipped with navigation systems and video capability, are currently being deployed for intelligence, reconnaissance and surveillance mission. In this paper, we present a systematic approach for the generation of UAV trajectory using a video image matching system based on SURF (Speeded up Robust Feature) and Preemptive RANSAC (Random Sample Consensus). Video image matching to find matching points is one of the most important steps for the accurate generation of UAV trajectory (sequence of poses in 3D space). We used the SURF algorithm to find the matching points between video image sequences, and removed mismatching by using the Preemptive RANSAC which divides all matching points to outliers and inliers. The inliers are only used to determine the epipolar geometry for estimating the relative pose (rotation and translation) between image sequences. Experimental results from simulated video image sequences showed that our approach has a good potential to be applied to the automatic geo-localization of the UAVs system

  16. Cooperative control of UAVs for localization of intermittently emitting mobile targets.

    Science.gov (United States)

    Pack, Daniel J; Delima, Pedro; Toussaint, Gregory J; York, George

    2009-08-01

    Compared with a single platform, cooperative autonomous unmanned aerial vehicles (UAVs) offer efficiency and robustness in performing complex tasks. Focusing on ground mobile targets that intermittently emit radio frequency signals, this paper presents a decentralized control architecture for multiple UAVs, equipped only with rudimentary sensors, to search, detect, and locate targets over large areas. The proposed architecture has in its core a decision logic which governs the state of operation for each UAV based on sensor readings and communicated data. To support the findings, extensive simulation results are presented, focusing primarily on two success measures that the UAVs seek to minimize: overall time to search for a group of targets and the final target localization error achieved. The results of the simulations have provided support for hardware flight tests.

  17. Geometry correction Algorithm for UAV Remote Sensing Image Based on Improved Neural Network

    Science.gov (United States)

    Liu, Ruian; Liu, Nan; Zeng, Beibei; Chen, Tingting; Yin, Ninghao

    2018-03-01

    Aiming at the disadvantage of current geometry correction algorithm for UAV remote sensing image, a new algorithm is proposed. Adaptive genetic algorithm (AGA) and RBF neural network are introduced into this algorithm. And combined with the geometry correction principle for UAV remote sensing image, the algorithm and solving steps of AGA-RBF are presented in order to realize geometry correction for UAV remote sensing. The correction accuracy and operational efficiency is improved through optimizing the structure and connection weight of RBF neural network separately with AGA and LMS algorithm. Finally, experiments show that AGA-RBF algorithm has the advantages of high correction accuracy, high running rate and strong generalization ability.

  18. UAV Mission Planning: From Robust to Agile

    NARCIS (Netherlands)

    Evers, L.; Barros, A.I.; Monsuur, H.; Wagelmans, A.

    2015-01-01

    Unmanned Aerial Vehicles (UAVs) are important assets for information gathering in Intelligence Surveillance and Reconnaissance (ISR) missions. Depending on the uncertainty in the planning parameters, the complexity of the mission and its constraints and requirements, different planning methods might

  19. Standing "the Watches" with Armed UAVs

    National Research Council Canada - National Science Library

    McCulloch, Francis

    2002-01-01

    This paper addresses the additional Options available to the operational commander in charge of conducting 'presence and monitoring' missions with the introduction of an armed capability on Unmanned Aerial Vehicles (UAVs...

  20. Taxonomy of Conflict Detection and Resolution Approaches for Unmanned Aerial Vehicle in an Integrated Airspace

    NARCIS (Netherlands)

    Jenie, Y.I.; van Kampen, E.; Ellerbroek, J.; Hoekstra, J.M.

    2016-01-01

    This paper proposes a taxonomy of Conflict Detection and Resolution (CD&R) approaches for Unmanned Aerial Vehicles (UAV) operation in an integrated airspace. Possible approaches for UAVs are surveyed and broken down based on their types of surveillance, coordination, maneuver, and autonomy. The

  1. A Survey of Channel Modeling for UAV Communications

    KAUST Repository

    Khuwaja, Aziz Altaf; Chen, Yunfei; Zhao, Nan; Alouini, Mohamed-Slim; Dobbins, Paul

    2018-01-01

    Unmanned aerial vehicles (UAVs) have gained great interest for rapid deployment in both civil and military applications. UAV communication has its own distinctive channel characteristics compared with widely used cellular and satellite systems. Thus, accurate channel characterization is crucial for the performance optimization and design of efficient UAV communication systems. However, several challenges exist in UAV channel modeling. For example, propagation characteristics of UAV channels are still less explored for spatial and temporal variations in non-stationary channels. Also, airframe shadowing has not yet been investigated for small size rotary UAVs. This paper provides an extensive survey on the measurement campaigns launched for UAV channel modeling using low altitude platforms and discusses various channel characterization efforts. We also review the contemporary perspective of UAV channel modeling approaches and outline some future research challenges in this domain.

  2. A Survey of Channel Modeling for UAV Communications

    KAUST Repository

    Khuwaja, Aziz Altaf

    2018-01-23

    Unmanned aerial vehicles (UAVs) have gained great interest for rapid deployment in both civil and military applications. UAV communication has its own distinctive channel characteristics compared with widely used cellular and satellite systems. Thus, accurate channel characterization is crucial for the performance optimization and design of efficient UAV communication systems. However, several challenges exist in UAV channel modeling. For example, propagation characteristics of UAV channels are still less explored for spatial and temporal variations in non-stationary channels. Also, airframe shadowing has not yet been investigated for small size rotary UAVs. This paper provides an extensive survey on the measurement campaigns launched for UAV channel modeling using low altitude platforms and discusses various channel characterization efforts. We also review the contemporary perspective of UAV channel modeling approaches and outline some future research challenges in this domain.

  3. A Robust Vision-based Runway Detection and Tracking Algorithm for Automatic UAV Landing

    KAUST Repository

    Abu Jbara, Khaled F.

    2015-01-01

    and attitude angle estimates to allow a more robust tracking of the runway under turbulence. We illustrate the performance of the proposed lane detection and tracking scheme on various experimental UAV flights conducted by the Saudi Aerospace Research Center

  4. Low complexity video encoding for UAV inspection

    DEFF Research Database (Denmark)

    Søgaard, Jacob; Zhang, Ruo; Forchhammer, Søren

    2016-01-01

    In this work we present several methods for fast integer motion estimation of videos recorded aboard an Unmanned Aerial Vehicle (UAV). Different from related work, the field depth is not considered to be consistent. The novel methods designed for low complexity MV prediction in H.264/AVC and anal......In this work we present several methods for fast integer motion estimation of videos recorded aboard an Unmanned Aerial Vehicle (UAV). Different from related work, the field depth is not considered to be consistent. The novel methods designed for low complexity MV prediction in H.264/AVC...... for UAV infrared (IR) video are also provided....

  5. An Efficient Genetic Algorithm for Routing Multiple UAVs under Flight Range and Service Time Window Constraints

    OpenAIRE

    KARAKAYA, Murat; SEVİNÇ, Ender

    2017-01-01

    Recently using Unmanned Aerial Vehicles (UAVs) either for military or civilian purposes is getting popularity. However, UAVs have their own limitations which require adopted approaches to satisfy the Quality of Service (QoS) promised by the applications depending on effective use of UAVs. One of the important limitations of the UAVs encounter is the flight range. Most of the time, UAVs have very scarce energy resources and, thus, they have relatively short flight ranges. Besides, for the appl...

  6. Thrust sensing for small UAVs

    Science.gov (United States)

    Marchman, Christopher Scott

    Unmanned aerial vehicles (UAVs) have become prevalent in both military and civilian applications. UAVs have many size categories from large-scale aircraft to micro air vehicles. The performance, health, and efficiency for UAVs of smaller sizes can be difficult to assess and few associated instrumentation systems have been developed. Thrust measurements on the ground can characterize systems especially when combined with simultaneous motor power measurements. This thesis demonstrates the use of strain measurements to measure the thrust produced by motor/propeller combinations for such small UAVs. A full-bridge Wheatstone circuit and electrical resistance strain gauges were used in conjunction with constant-stress cantilever beams for static tests and dynamic wind tunnel tests. An associated instrumentation module monitored power from the electric motor. Monitoring the thrust data over time can provide insights into optimal propeller and motor selection and early detection of problems such as component failure. The approach provides a system for laboratory or field measurements that can be scaled for a wide range of small UAVs.

  7. UAV based 3D digital surface model to estimate paleolandscape in high mountainous environment

    Science.gov (United States)

    Mészáros, János; Árvai, Mátyás; Kohán, Balázs; Deák, Márton; Nagy, Balázs

    2016-04-01

    Our method to present current state of a peat bog was focused on the possible use of a UAV-system and later Structure-from-motion algorithms as processing technique. The peat bog site is located on the Vinderel Plateau, Farcǎu Massif, Maramures Mountains (Romania). The peat bog (1530 m a.s.l., N47°54'11", E24°26'37") lies below Rugasu ridge (c. 1820 m a.s.l.) and the locality serves as a conservation area for fallen down coniferous trees. Peat deposits were formed in a landslide concavity on the western slope of Farcǎu Massif. Nowadays the site is surrounded by a completely deforested landscape, and Farcǎu Massif lies above the depressed treeline. The peat bog has an extraordinary geomorphological situation, because a gully reached the bog and drained the water. In the recent past sedimentological and dendrochronological researches have been initiated. However, an accurate 3D digital surface model also needed for a complex paleoenvironmental research. Last autumn the bog and its surroundings were finally surveyed by a multirotor UAV developed in-house based on an open-source flight management unit and its firmware. During this survey a lightweight action camera (mainly to decrease payload weight) was used to take aerial photographs. While our quadcopter is capable to fly automatically on a predefined flight route, several over- and sidelapping flight lines were generated prior to the actual survey on the ground using a control software running on a notebook. Despite those precautions, limited number of batteries and severe weather affected our final flights, resulting a reduced surveyed area around peat bog. Later, during the processing we looked for a reliable tool which powerful enough to process more than 500 photos taken during flights. After testing several software Agisoft PhotoScan was used to create 3D point cloud and mesh about bog and its environment. Due to large number of photographs PhotoScan had to be configured for network processing to get

  8. Prognostics Applied to Electric Propulsion UAV

    Science.gov (United States)

    Goebel, Kai; Saha, Bhaskar

    2013-01-01

    Health management plays an important role in operations of UAV. If there is equipment malfunction on critical components, safe operation of the UAV might possibly be compromised. A technology with particular promise in this arena is equipment prognostics. This technology provides a state assessment of the health of components of interest and, if a degraded state has been found, it estimates how long it will take before the equipment will reach a failure threshold, conditional on assumptions about future operating conditions and future environmental conditions. This chapter explores the technical underpinnings of how to perform prognostics and shows an implementation on the propulsion of an electric UAV. A particle filter is shown as the method of choice in performing state assessment and predicting future degradation. The method is then applied to the batteries that provide power to the propeller motors. An accurate run-time battery life prediction algorithm is of critical importance to ensure the safe operation of the vehicle if one wants to maximize in-air time. Current reliability based techniques turn out to be insufficient to manage the use of such batteries where loads vary frequently in uncertain environments.

  9. Morphological and structural changes at the Merapi lava dome monitored in 2012-15 using unmanned aerial vehicles (UAVs)

    Science.gov (United States)

    Darmawan, Herlan; Walter, Thomas R.; Brotopuspito, Kirbani Sri; Subandriyo; I Gusti Made Agung Nandaka

    2018-01-01

    Dome-building volcanoes undergo rapid and profound topographic changes that are important to quantify for the purposes of hazard assessment. However, as hazardous lava domes often develop on high-altitude volcanoes that exhibit steep-sided topography, it is challenging to obtain direct field access and thus to analyze these morphological and structural changes. Merapi Volcano in Indonesia is a type example of such a volcano, as soon after its 2010 eruption, a new lava dome developed. This dome was partially destroyed during six distinct steam-driven explosions that occurred between 2012 and 2014. Here, we investigate the topographic and structural changes associated with these six steam-driven explosions by comparing close-range photogrammetric data obtained before and after these explosions. To accomplish this, we performed two UAV campaigns in 2012 and 2015. By applying the Structure from Motion (SfM) technique, we are able to construct three-dimensional point clouds, assess their quality by comparing them to a terrestrial laser scanning (TLS) dataset, and generate high-resolution Digital Elevation Models (DEMs) and photomosaics. The comparison of these two DEMs and photomosaics reveals changes in topography and the appearance of fractures. In the 2012 dataset, we find a dense fracture network striking to the NNW-SSE. In the post-eruptive 2015 dataset, we see that this NNW-SSE fracture trend is much more strongly expressed; we also detect the formation of aligned and elongated explosion craters, which are associated with the removal of over 200,000 m3 of dome material, most of which ( 70%) was deposited outside the crater region. Therefore, this study suggests that the locations of the steam-driven explosions at Merapi Volcano were controlled by the reactivation of preexisting structures. Moreover, some of the newly developed and reactivated fractures delineate a block on the southern slope of the dome, which could become structurally unstable and potentially

  10. Assessment of UAV and Ground-Based Structure from Motion with Multi-View Stereo Photogrammetry in a Gullied Savanna Catchment

    Directory of Open Access Journals (Sweden)

    Jack Koci

    2017-10-01

    Full Text Available Structure from Motion with Multi-View Stereo photogrammetry (SfM-MVS is increasingly used in geoscience investigations, but has not been thoroughly tested in gullied savanna systems. The aim of this study was to test the accuracy of topographic models derived from aerial (via Unmanned Aerial Vehicle, ‘UAV’ and ground-based (via handheld digital camera, ‘ground’ SfM-MVS in modelling hillslope gully systems in a dry-tropical savanna, and to assess the strengths and limitations of the approach at a hillslope scale and an individual gully scale. UAV surveys covered three separate hillslope gully systems (with areas of 0.412–0.715 km2, while ground surveys assessed individual gullies within the broader systems (with areas of 350–750 m2. SfM-MVS topographic models, including Digital Surface Models (DSM and dense point clouds, were compared against RTK-GPS point data and a pre-existing airborne LiDAR Digital Elevation Model (DEM. Results indicate that UAV SfM-MVS can deliver topographic models with a resolution and accuracy suitable to define gully systems at a hillslope scale (e.g., approximately 0.1 m resolution with 0.4–1.2 m elevation error, while ground-based SfM-MVS is more capable of quantifying gully morphology (e.g., approximately 0.01 m resolution with 0.04–0.1 m elevation error. Despite difficulties in reconstructing vegetated surfaces, uncertainty as to optimal survey and processing designs, and high computational demands, this study has demonstrated great potential for SfM-MVS to be used as a cost-effective tool to aid in the mapping, modelling and management of hillslope gully systems at different scales, in savanna landscapes and elsewhere.

  11. On the throughput of cognitive radio MIMO systems assisted with UAV relays

    KAUST Repository

    Sboui, Lokman; Ghazzai, Hakim; Rezki, Zouheir; Alouini, Mohamed-Slim

    2017-01-01

    We analyze the achievable rates of a cognitive radio MIMO system assisted by an unmanned aerial vehicle (UAV) relay. The primary user (PU) and the secondary user (SU) aim to communicate to the closest primary base station (BS) via a multi

  12. Using Natural Language to Enable Mission Managers to Control Multiple Heterogeneous UAVs

    Science.gov (United States)

    Trujillo, Anna C.; Puig-Navarro, Javier; Mehdi, S. Bilal; Mcquarry, A. Kyle

    2016-01-01

    The availability of highly capable, yet relatively cheap, unmanned aerial vehicles (UAVs) is opening up new areas of use for hobbyists and for commercial activities. This research is developing methods beyond classical control-stick pilot inputs, to allow operators to manage complex missions without in-depth vehicle expertise. These missions may entail several heterogeneous UAVs flying coordinated patterns or flying multiple trajectories deconflicted in time or space to predefined locations. This paper describes the functionality and preliminary usability measures of an interface that allows an operator to define a mission using speech inputs. With a defined and simple vocabulary, operators can input the vast majority of mission parameters using simple, intuitive voice commands. Although the operator interface is simple, it is based upon autonomous algorithms that allow the mission to proceed with minimal input from the operator. This paper also describes these underlying algorithms that allow an operator to manage several UAVs.

  13. Modelling and Analysis of Vibrations in a UAV Helicopter with a Vision System

    Directory of Open Access Journals (Sweden)

    G. Nicolás Marichal Plasencia

    2012-11-01

    Full Text Available The analysis of the nature and damping of unwanted vibrations on Unmanned Aerial Vehicle (UAV helicopters are important tasks when images from on-board vision systems are to be obtained. In this article, the authors model a UAV system, generate a range of vibrations originating in the main rotor and design a control methodology in order to damp these vibrations. The UAV is modelled using VehicleSim, the vibrations that appear on the fuselage are analysed to study their effects on the on-board vision system by using Simmechanics software. Following this, the authors present a control method based on an Adaptive Neuro-Fuzzy Inference System (ANFIS to achieve satisfactory damping results over the vision system on board.

  14. Towards a Biosynthetic UAV

    Science.gov (United States)

    Block, Eli; Byemerwa, Jovita; Dispenza, Ross; Doughty, Benjamin; Gillyard, KaNesha; Godbole, Poorwa; Gonzales-Wright, Jeanette; Hull, Ian; Kannappan, Jotthe; Levine, Alexander; hide

    2014-01-01

    We are currently working on a series of projects towards the construction of a fully biological unmanned aerial vehicle (UAV) for use in scientific and humanitarian missions. The prospect of a biologically-produced UAV presents numerous advantages over the current manufacturing paradigm. First, a foundational architecture built by cells allows for construction or repair in locations where it would be difficult to bring traditional tools of production. Second, a major limitation of current research with UAVs is the size and high power consumption of analytical instruments, which require bulky electrical components and large fuselages to support their weight. By moving these functions into cells with biosensing capabilities - for example, a series of cells engineered to report GFP, green fluorescent protein, when conditions exceed a certain threshold concentration of a compound of interest, enabling their detection post-flight - these problems of scale can be avoided. To this end, we are working to engineer cells to synthesize cellulose acetate as a novel bioplastic, characterize biological methods of waterproofing the material, and program this material's systemic biodegradation. In addition, we aim to use an "amberless" system to prevent horizontal gene transfer from live cells on the material to microorganisms in the flight environment.

  15. Modeling Multioperator Multi-UAV Operator Attention Allocation Problem Based on Maximizing the Global Reward

    Directory of Open Access Journals (Sweden)

    Yuhang Wu

    2016-01-01

    Full Text Available This paper focuses on the attention allocation problem (AAP in modeling multioperator multi-UAV (MOMU, with the operator model and task properties taken into consideration. The model of MOMU operator AAP based on maximizing the global reward is established and used to allocate tasks to all operators as well as set work time and rest time to each task simultaneously for operators. The proposed model is validated in Matlab simulation environment, using the immune algorithm and dynamic programming algorithm to evaluate the performance of the model in terms of the reward value with regard to the work time, rest time, and task allocation. The result shows that the total reward of the proposed model is larger than the one obtained from previously published methods using local maximization and the total reward of our method has an exponent-like relation with the task arrival rate. The proposed model can improve the operators’ task processing efficiency in the MOMU command and control scenarios.

  16. AERIAL SURVEYING UAV BASED ON OPEN-SOURCE HARDWARE AND SOFTWARE

    Directory of Open Access Journals (Sweden)

    J. Mészáros

    2012-09-01

    Full Text Available In the last years the functionality and type of UAV-systems increased fast, but unfortunately these systems are hardly available for researchers in some cases. A simple and low-cost solution was developed to build an autonomous aerial surveying airplane, which can fulfil the necessities (aerial photographs with very-high resolution of other departments at the university and very useful and practical for teaching photogrammetry.. The base was a commercial, remote controlled model airplane and an open-source GPS/IMU system (MatrixPilot was adapted to achieve the semi-automatic or automatic stabilization and navigation of the model airplane along predefined trajectory. The firmware is completely open-source and easily available on the website of the project. The first used camera system was a low-budget, low-quality video camera, which could provide only 1.2 megapixel photographs or low resolution video depending on the light conditions and the desired spatial resolution. A field measurement test was carried out with the described system: the aerial surveying of an undiscovered archaeological site, signed by a crop-mark in mountain Pilis (Hungary.

  17. Vision-based Vehicle Detection Survey

    Directory of Open Access Journals (Sweden)

    Alex David S

    2016-03-01

    Full Text Available Nowadays thousands of drivers and passengers were losing their lives every year on road accident, due to deadly crashes between more than one vehicle. There are number of many research focuses were dedicated to the development of intellectual driver assistance systems and autonomous vehicles over the past decade, which reduces the danger by monitoring the on-road environment. In particular, researchers attracted towards the on-road detection of vehicles in recent years. Different parameters have been analyzed in this paper which includes camera placement and the various applications of monocular vehicle detection, common features and common classification methods, motion- based approaches and nighttime vehicle detection and monocular pose estimation. Previous works on the vehicle detection listed based on camera poisons, feature based detection and motion based detection works and night time detection.

  18. MODELLING OF DECISION MAKING OF UNMANNED AERIAL VEHICLE'S OPERATOR IN EMERGENCY SITUATIONS

    Directory of Open Access Journals (Sweden)

    Volodymyr Kharchenko

    2017-03-01

    Full Text Available Purpose: lack of recommendation action algorithm of UAV operator in emergency situations; decomposition of the process of decision making (DM by UAV’s Operator in emergency situations; development of the structure of distributed decision support system (DDSS for remotely piloted aircraft; development of a database of local decision support system (DSS operators Remotely Piloted Aircraft Systems (RPAS; working-out of models DM by UAV’s Operator. Methods: Algoritm of actions of UAV operator by Wald criterion, Laplace criterion, Hurwitz criterion. Results: The program "UAV_AS" that gives to UAV operator recommendations on how to act in case of emergency. Discussion: The article deals with the problem of Unmanned Aerial Vehicles (UAV flights for decision of different tasks in emergency situation. Based on statistical data it was analyzing the types of emergencies for unmanned aircraft. Defined sequence of actions UAV operator and in case of emergencies.

  19. Are estimates of wind characteristics based on measurements with Pitot tubes and GNSS receivers mounted on consumer-grade unmanned aerial vehicles applicable in meteorological studies?

    Science.gov (United States)

    Niedzielski, Tomasz; Skjøth, Carsten; Werner, Małgorzata; Spallek, Waldemar; Witek, Matylda; Sawiński, Tymoteusz; Drzeniecka-Osiadacz, Anetta; Korzystka-Muskała, Magdalena; Muskała, Piotr; Modzel, Piotr; Guzikowski, Jakub; Kryza, Maciej

    2017-09-01

    The objective of this paper is to empirically show that estimates of wind speed and wind direction based on measurements carried out using the Pitot tubes and GNSS receivers, mounted on consumer-grade unmanned aerial vehicles (UAVs), may accurately approximate true wind parameters. The motivation for the study is that a growing number of commercial and scientific UAV operations may soon become a new source of data on wind speed and wind direction, with unprecedented spatial and temporal resolution. The feasibility study was carried out within an isolated mountain meadow of Polana Izerska located in the Izera Mountains (SW Poland) during an experiment which aimed to compare wind characteristics measured by several instruments: three UAVs (swinglet CAM, eBee, Maja) equipped with the Pitot tubes and GNSS receivers, wind speed and direction meters mounted at 2.5 and 10 m (mast), conventional weather station and vertical sodar. The three UAVs performed seven missions along spiral-like trajectories, most reaching 130 m above take-off location. The estimates of wind speed and wind direction were found to agree between UAVs. The time series of wind speed measured at 10 m were extrapolated to flight altitudes recorded at a given time so that a comparison was made feasible. It was found that the wind speed estimates provided by the UAVs on a basis of the Pitot tube/GNSS data are in agreement with measurements carried out using dedicated meteorological instruments. The discrepancies were recorded in the first and last phases of UAV flights.

  20. Detection and Segmentation of Vine Canopy in Ultra-High Spatial Resolution RGB Imagery Obtained from Unmanned Aerial Vehicle (UAV: A Case Study in a Commercial Vineyard

    Directory of Open Access Journals (Sweden)

    Carlos Poblete-Echeverría

    2017-03-01

    Full Text Available The use of Unmanned Aerial Vehicles (UAVs in viticulture permits the capture of aerial Red-Green-Blue (RGB images with an ultra-high spatial resolution. Recent studies have demonstrated that RGB images can be used to monitor spatial variability of vine biophysical parameters. However, for estimating these parameters, accurate and automated segmentation methods are required to extract relevant information from RGB images. Manual segmentation of aerial images is a laborious and time-consuming process. Traditional classification methods have shown satisfactory results in the segmentation of RGB images for diverse applications and surfaces, however, in the case of commercial vineyards, it is necessary to consider some particularities inherent to canopy size in the vertical trellis systems (VSP such as shadow effect and different soil conditions in inter-rows (mixed information of soil and weeds. Therefore, the objective of this study was to compare the performance of four classification methods (K-means, Artificial Neural Networks (ANN, Random Forest (RForest and Spectral Indices (SI to detect canopy in a vineyard trained on VSP. Six flights were carried out from post-flowering to harvest in a commercial vineyard cv. Carménère using a low-cost UAV equipped with a conventional RGB camera. The results show that the ANN and the simple SI method complemented with the Otsu method for thresholding presented the best performance for the detection of the vine canopy with high overall accuracy values for all study days. Spectral indices presented the best performance in the detection of Plant class (Vine canopy with an overall accuracy of around 0.99. However, considering the performance pixel by pixel, the Spectral indices are not able to discriminate between Soil and Shadow class. The best performance in the classification of three classes (Plant, Soil, and Shadow of vineyard RGB images, was obtained when the SI values were used as input data in trained

  1. Development of a bio-inspired UAV perching system

    Science.gov (United States)

    Xie, Pu

    Although technologies of unmanned aerial vehicles (UAVs) including micro air vehicles (MAVs) have been greatly advanced in the recent years, it is still very difficult for a UAV to perform some very challenging tasks such as perching to any desired spot reliably and agilely like a bird. Unlike the UAVs, the biological control mechanism of birds has been optimized through millions of year evolution and hence, they can perform many extremely maneuverability tasks, such as perching or grasping accurately and robustly. Therefore, we have good reason to learn from the nature in order to significantly improve the capabilities of UAVs. The development of a UAV perching system is becoming feasible, especially after a lot of research contributions in ornithology which involve the analysis of the bird's functionalities. Meanwhile, as technology advances in many engineering fields, such as airframes, propulsion, sensors, batteries, micro-electromechanical-system (MEMS), and UAV technology is also advancing rapidly. All of these research efforts in ornithology and the fast growing development technologies in UAV applications are motivating further interests and development in the area of UAV perching and grasping research. During the last decade, the research contributions about UAV perching and grasping were mainly based on fixed-wing, flapping-wing, and rotorcraft UAVs. However, most of the current researches in UAV systems with perching and grasping capability are focusing on either active (powered) grasping and perching or passive (unpowered) perching. Although birds do have both active and passive perching capabilities depending on their needs, there is no UAV perching system with both capabilities. In this project, we focused on filling this gap. Inspired by the anatomy analysis of bird legs and feet, a novel perching system has been developed to implement the bionics action for both active grasping and passive perching. In addition, for developing a robust and

  2. Vehicle positioning based on UWB technology

    Science.gov (United States)

    Hu, Siquan; Kang, Min; She, Chundong

    2017-08-01

    In recent years, with the rapid increase of the number of urban cars, the vehicle internet is becoming a trend of smart transportion. In such vehicle network, accurate location is very crucial in many new applications such as autopilot, semi-autopilot and Car-to-x communications. UWB technology has been used for indoor closed range positioning and ranging widely, while UWB outdoor positioning and ranging research is relatively less. This paper proposed UWB as the vehicle positioning technology and developed a method based on two-way-ranging (TWR) to solve the ranging problem between vehicles. At the same time, the improved TOA method was used to locate vehicles, which has higher precision compared with traditional GPS or LBS. A hardware module is introduced and the simulation results show that the modules are capable of precise positioning for vehicles in vehicle network.

  3. Cloud-Assisted UAV Data Collection for Multiple Emerging Events in Distributed WSNs.

    Science.gov (United States)

    Cao, Huiru; Liu, Yongxin; Yue, Xuejun; Zhu, Wenjian

    2017-08-07

    In recent years, UAVs (Unmanned Aerial Vehicles) have been widely applied for data collection and image capture. Specifically, UAVs have been integrated with wireless sensor networks (WSNs) to create data collection platforms with high flexibility. However, most studies in this domain focus on system architecture and UAVs' flight trajectory planning while event-related factors and other important issues are neglected. To address these challenges, we propose a cloud-assisted data gathering strategy for UAV-based WSN in the light of emerging events. We also provide a cloud-assisted approach for deriving UAV's optimal flying and data acquisition sequence of a WSN cluster. We validate our approach through simulations and experiments. It has been proved that our methodology outperforms conventional approaches in terms of flying time, energy consumption, and integrity of data acquisition. We also conducted a real-world experiment using a UAV to collect data wirelessly from multiple clusters of sensor nodes for monitoring an emerging event, which are deployed in a farm. Compared against the traditional method, this proposed approach requires less than half the flying time and achieves almost perfect data integrity.

  4. Assessment of the Possibility of Using Unmanned Aerial Vehicles (UAVs) for the Documentation of Hiking Trails in Alpine Areas.

    Science.gov (United States)

    Ćwiąkała, Paweł; Kocierz, Rafał; Puniach, Edyta; Nędzka, Michał; Mamczarz, Karolina; Niewiem, Witold; Wiącek, Paweł

    2017-12-29

    The research described in this paper deals with the documentation of hiking trails in alpine areas. The study presents a novel research topic, applying up-to-date survey techniques and top quality equipment with practical applications in nature conservation. The research presents the initial part of the process-capturing imagery, photogrammetric processing, quality checking, and a discussion on possibilities of the further data analysis. The research described in this article was conducted in the Tatra National Park (TNP) in Poland, which is considered as one of the most-visited national parks in Europe. The exceptional popularity of this place is responsible for intensification of morphogenetic processes, resulting in the development of numerous forms of erosion. This article presents the outcomes of research, whose purpose was to verify the usability of UAVs to check the condition of hiking trails in alpine areas. An octocopter equipped with a non-metric camera was used for measurements. Unlike traditional methods of measuring landscape features, such a solution facilitates acquisition of quasi-continuous data that has uniform resolution throughout the study area and high spatial accuracy. It is also a relatively cheap technology, which is its main advantage over equally popular laser scanning. The paper presents the complete methodology of data acquisition in harsh conditions and demanding locations of hiking trails on steep Tatra slopes. The paper also describes stages that lead to the elaboration of basic photogrammetric products relying on structure from motion (SfM) technology and evaluates the accuracy of the materials obtained. Finally, it shows the applicability of the prepared products to the evaluation of the spatial reach and intensity of erosion along hiking trails, and to the study of plant succession or tree stand condition in the area located next to hiking trails.

  5. Assessment of the Possibility of Using Unmanned Aerial Vehicles (UAVs for the Documentation of Hiking Trails in Alpine Areas

    Directory of Open Access Journals (Sweden)

    Paweł Ćwiąkała

    2017-12-01

    Full Text Available The research described in this paper deals with the documentation of hiking trails in alpine areas. The study presents a novel research topic, applying up-to-date survey techniques and top quality equipment with practical applications in nature conservation. The research presents the initial part of the process—capturing imagery, photogrammetric processing, quality checking, and a discussion on possibilities of the further data analysis. The research described in this article was conducted in the Tatra National Park (TNP in Poland, which is considered as one of the most-visited national parks in Europe. The exceptional popularity of this place is responsible for intensification of morphogenetic processes, resulting in the development of numerous forms of erosion. This article presents the outcomes of research, whose purpose was to verify the usability of UAVs to check the condition of hiking trails in alpine areas. An octocopter equipped with a non-metric camera was used for measurements. Unlike traditional methods of measuring landscape features, such a solution facilitates acquisition of quasi-continuous data that has uniform resolution throughout the study area and high spatial accuracy. It is also a relatively cheap technology, which is its main advantage over equally popular laser scanning. The paper presents the complete methodology of data acquisition in harsh conditions and demanding locations of hiking trails on steep Tatra slopes. The paper also describes stages that lead to the elaboration of basic photogrammetric products relying on structure from motion (SfM technology and evaluates the accuracy of the materials obtained. Finally, it shows the applicability of the prepared products to the evaluation of the spatial reach and intensity of erosion along hiking trails, and to the study of plant succession or tree stand condition in the area located next to hiking trails.

  6. UAV-based mapping, back analysis and trajectory modeling of a coseismic rockfall in Lefkada island, Greece

    Science.gov (United States)

    Saroglou, Charalampos; Asteriou, Pavlos; Zekkos, Dimitrios; Tsiambaos, George; Clark, Marin; Manousakis, John

    2018-01-01

    We present field evidence and a kinematic study of a rock block mobilized in the Ponti area by a Mw = 6.5 earthquake near the island of Lefkada on 17 November 2015. A detailed survey was conducted using an unmanned aerial vehicle (UAV) with an ultrahigh definition (UHD) camera, which produced a high-resolution orthophoto and a digital terrain model (DTM). The sequence of impact marks from the rock trajectory on the ground surface was identified from the orthophoto and field verified. Earthquake characteristics were used to estimate the acceleration of the rock slope and the initial condition of the detached block. Using the impact points from the measured rockfall trajectory, an analytical reconstruction of the trajectory was undertaken, which led to insights on the coefficients of restitution (CORs). The measured trajectory was compared with modeled rockfall trajectories using recommended parameters. However, the actual trajectory could not be accurately predicted, revealing limitations of existing rockfall analysis software used in engineering practice.

  7. Optimal multi-agent path planning for fast inverse modeling in UAV-based flood sensing applications

    KAUST Repository

    Abdelkader, Mohamed

    2014-05-01

    Floods are the most common natural disasters, causing thousands of casualties every year in the world. In particular, flash flood events are particularly deadly because of the short timescales on which they occur. Unmanned air vehicles equipped with mobile microsensors could be capable of sensing flash floods in real time, saving lives and greatly improving the efficiency of the emergency response. However, of the main issues arising with sensing floods is the difficulty of planning the path of the sensing agents in advance so as to obtain meaningful data as fast as possible. In this particle, we present a fast numerical scheme to quickly compute the trajectories of a set of UAVs in order to maximize the accuracy of model parameter estimation over a time horizon. Simulation results are presented, a preliminary testbed is briefly described, and future research directions and problems are discussed. © 2014 IEEE.

  8. Automatic Reverse Engineering of Private Flight Control Protocols of UAVs

    Directory of Open Access Journals (Sweden)

    Ran Ji

    2017-01-01

    Full Text Available The increasing use of civil unmanned aerial vehicles (UAVs has the potential to threaten public safety and privacy. Therefore, airspace administrators urgently need an effective method to regulate UAVs. Understanding the meaning and format of UAV flight control commands by automatic protocol reverse-engineering techniques is highly beneficial to UAV regulation. To improve our understanding of the meaning and format of UAV flight control commands, this paper proposes a method to automatically analyze the private flight control protocols of UAVs. First, we classify flight control commands collected from a binary network trace into clusters; then, we analyze the meaning of flight control commands by the accumulated error of each cluster; next, we extract the binary format of commands and infer field semantics in these commands; and finally, we infer the location of the check field in command and the generator polynomial matrix. The proposed approach is validated via experiments on a widely used consumer UAV.

  9. UAV MONITORING FOR ENVIROMENTAL MANAGEMENT IN GALAPAGOS ISLANDS

    Directory of Open Access Journals (Sweden)

    D. Ballaria

    2016-06-01

    Full Text Available In the Galapagos Islands, where 97% of the territory is protected and ecosystem dynamics are highly vulnerable, timely and accurate information is key for decision making. An appropriate monitoring system must meet two key features: on one hand, being able to capture information in a systematic and regular basis, and on the other hand, to quickly gather information on demand for specific purposes. The lack of such a system for geographic information limits the ability of Galapagos Islands’ institutions to evaluate and act upon environmental threats such as invasive species spread and vegetation degradation. In this context, the use of UAVs (unmanned aerial vehicles for capturing georeferenced images is a promising technology for environmental monitoring and management. This paper explores the potential of UAV images for monitoring degradation of littoral vegetation in Puerto Villamil (Isabela Island, Galapagos, Ecuador. Imagery was captured using two camera types: Red Green Blue (RGB and Infrarred Red Green (NIR. First, vegetation presence was identified through NDVI. Second, object-based classification was carried out for characterization of vegetation vigor. Results demonstrates the feasibility of UAV technology for base-line studies and monitoring on the amount and vigorousness of littoral vegetation in the Galapagos Islands. It is also showed that UAV images are not only useful for visual interpretation and object delineation, but also to timely produce useful thematic information for environmental management.

  10. Feasibility of Using Synthetic Aperture Radar to Aid UAV Navigation.

    Science.gov (United States)

    Nitti, Davide O; Bovenga, Fabio; Chiaradia, Maria T; Greco, Mario; Pinelli, Gianpaolo

    2015-07-28

    This study explores the potential of Synthetic Aperture Radar (SAR) to aid Unmanned Aerial Vehicle (UAV) navigation when Inertial Navigation System (INS) measurements are not accurate enough to eliminate drifts from a planned trajectory. This problem can affect medium-altitude long-endurance (MALE) UAV class, which permits heavy and wide payloads (as required by SAR) and flights for thousands of kilometres accumulating large drifts. The basic idea is to infer position and attitude of an aerial platform by inspecting both amplitude and phase of SAR images acquired onboard. For the amplitude-based approach, the system navigation corrections are obtained by matching the actual coordinates of ground landmarks with those automatically extracted from the SAR image. When the use of SAR amplitude is unfeasible, the phase content can be exploited through SAR interferometry by using a reference Digital Terrain Model (DTM). A feasibility analysis was carried out to derive system requirements by exploring both radiometric and geometric parameters of the acquisition setting. We showed that MALE UAV, specific commercial navigation sensors and SAR systems, typical landmark position accuracy and classes, and available DTMs lead to estimated UAV coordinates with errors bounded within ±12 m, thus making feasible the proposed SAR-based backup system.

  11. An automated 3D reconstruction method of UAV images

    Science.gov (United States)

    Liu, Jun; Wang, He; Liu, Xiaoyang; Li, Feng; Sun, Guangtong; Song, Ping

    2015-10-01

    In this paper a novel fully automated 3D reconstruction approach based on low-altitude unmanned aerial vehicle system (UAVs) images will be presented, which does not require previous camera calibration or any other external prior knowledge. Dense 3D point clouds are generated by integrating orderly feature extraction, image matching, structure from motion (SfM) and multi-view stereo (MVS) algorithms, overcoming many of the cost, time limitations of rigorous photogrammetry techniques. An image topology analysis strategy is introduced to speed up large scene reconstruction by taking advantage of the flight-control data acquired by UAV. Image topology map can significantly reduce the running time of feature matching by limiting the combination of images. A high-resolution digital surface model of the study area is produced base on UAV point clouds by constructing the triangular irregular network. Experimental results show that the proposed approach is robust and feasible for automatic 3D reconstruction of low-altitude UAV images, and has great potential for the acquisition of spatial information at large scales mapping, especially suitable for rapid response and precise modelling in disaster emergency.

  12. Feasibility of Using Synthetic Aperture Radar to Aid UAV Navigation

    Directory of Open Access Journals (Sweden)

    Davide O. Nitti

    2015-07-01

    Full Text Available This study explores the potential of Synthetic Aperture Radar (SAR to aid Unmanned Aerial Vehicle (UAV navigation when Inertial Navigation System (INS measurements are not accurate enough to eliminate drifts from a planned trajectory. This problem can affect medium-altitude long-endurance (MALE UAV class, which permits heavy and wide payloads (as required by SAR and flights for thousands of kilometres accumulating large drifts. The basic idea is to infer position and attitude of an aerial platform by inspecting both amplitude and phase of SAR images acquired onboard. For the amplitude-based approach, the system navigation corrections are obtained by matching the actual coordinates of ground landmarks with those automatically extracted from the SAR image. When the use of SAR amplitude is unfeasible, the phase content can be exploited through SAR interferometry by using a reference Digital Terrain Model (DTM. A feasibility analysis was carried out to derive system requirements by exploring both radiometric and geometric parameters of the acquisition setting. We showed that MALE UAV, specific commercial navigation sensors and SAR systems, typical landmark position accuracy and classes, and available DTMs lead to estimated UAV coordinates with errors bounded within ±12 m, thus making feasible the proposed SAR-based backup system.

  13. UAV Monitoring for Enviromental Management in Galapagos Islands

    Science.gov (United States)

    Ballari, D.; Orellana, D.; Acosta, E.; Espinoza, A.; Morocho, V.

    2016-06-01

    In the Galapagos Islands, where 97% of the territory is protected and ecosystem dynamics are highly vulnerable, timely and accurate information is key for decision making. An appropriate monitoring system must meet two key features: on one hand, being able to capture information in a systematic and regular basis, and on the other hand, to quickly gather information on demand for specific purposes. The lack of such a system for geographic information limits the ability of Galapagos Islands' institutions to evaluate and act upon environmental threats such as invasive species spread and vegetation degradation. In this context, the use of UAVs (unmanned aerial vehicles) for capturing georeferenced images is a promising technology for environmental monitoring and management. This paper explores the potential of UAV images for monitoring degradation of littoral vegetation in Puerto Villamil (Isabela Island, Galapagos, Ecuador). Imagery was captured using two camera types: Red Green Blue (RGB) and Infrarred Red Green (NIR). First, vegetation presence was identified through NDVI. Second, object-based classification was carried out for characterization of vegetation vigor. Results demonstrates the feasibility of UAV technology for base-line studies and monitoring on the amount and vigorousness of littoral vegetation in the Galapagos Islands. It is also showed that UAV images are not only useful for visual interpretation and object delineation, but also to timely produce useful thematic information for environmental management.

  14. WiP abstract: Optimal multi-agent path planning for fast inverse modeling in UAV-based flood sensing applications

    KAUST Repository

    Abdelkader, Mohamed; Shaqura, Mohammad; Ghommem, Mehdi; Collier, Nathan O.; Calo, Victor M.; Claudel, Christian G.

    2014-01-01

    Floods are one of the most commonly occurring natural disasters, and caused more than 120,000 fatalities in the world between 1991 and 2005. Most of these casualties are caused by the lack of a reliable real-time flash flood monitoring system. Given the area to monitor, unmanned aerial vehicles (UAVs) appear as the most promising solutions for this task. © 2014 IEEE.

  15. WiP abstract: Optimal multi-agent path planning for fast inverse modeling in UAV-based flood sensing applications

    KAUST Repository

    Abdelkader, Mohamed

    2014-04-01

    Floods are one of the most commonly occurring natural disasters, and caused more than 120,000 fatalities in the world between 1991 and 2005. Most of these casualties are caused by the lack of a reliable real-time flash flood monitoring system. Given the area to monitor, unmanned aerial vehicles (UAVs) appear as the most promising solutions for this task. © 2014 IEEE.

  16. Optical and acoustical UAV detection

    Science.gov (United States)

    Christnacher, Frank; Hengy, Sébastien; Laurenzis, Martin; Matwyschuk, Alexis; Naz, Pierre; Schertzer, Stéphane; Schmitt, Gwenael

    2016-10-01

    Recent world events have highlighted that the proliferation of UAVs is bringing with it a new and rapidly increasing threat for national defense and security agencies. Whilst many of the reported UAV incidents seem to indicate that there was no terrorist intent behind them, it is not unreasonable to assume that it may not be long before UAV platforms are regularly employed by terrorists or other criminal organizations. The flight characteristics of many of these mini- and micro-platforms present challenges for current systems which have been optimized over time to defend against the traditional air-breathing airborne platforms. A lot of programs to identify cost-effective measures for the detection, classification, tracking and neutralization have begun in the recent past. In this paper, lSL shows how the performance of a UAV detection and tracking concept based on acousto-optical technology can be powerfully increased through active imaging.

  17. Price Based Electric Vehicle Charging

    DEFF Research Database (Denmark)

    Mahat, Pukar; Handl, Martin; Kanstrup, Kenneth

    2012-01-01

    It is expected that a lot of the new light vehicles in the future will be electrical vehicles (EV). The storage capacity of these EVs has the potential to complement renewable energy resources and mitigate its intermittency. However, EV charging may have negative impact on the power grid. This pa......It is expected that a lot of the new light vehicles in the future will be electrical vehicles (EV). The storage capacity of these EVs has the potential to complement renewable energy resources and mitigate its intermittency. However, EV charging may have negative impact on the power grid...... method where distribution system operator (DSO) optimizes the cost of EV charging while taking substation transformer capacity into account....

  18. Commercial UAV operations in civil airspace

    Science.gov (United States)

    Newcome, Laurence R.

    2000-11-01

    The Federal Aviation Administration is often portrayed as the major impediment to unmanned aerial vehicle expansion into civil government and commercial markets. This paper describes one company's record for successfully negotiating the FAA regulations and obtaining authorizations for several types of UAVs to fly commercial reconnaissance missions in civil airspace. The process and criteria for obtaining such authorizations are described. The mishap records of the Pioneer, Predator and Hunter UAVs are examined in regard to their impact on FAA rule making. The paper concludes with a discussion of the true impediments to UAV penetration of commercial markets to date.

  19. UAV-Based Optical Granulometry as Tool for Detecting Changes in Structure of Flood Depositions

    Czech Academy of Sciences Publication Activity Database

    Langhammer, J.; Lendzioch, T.; Miřijovský, J.; Hartvich, Filip

    2017-01-01

    Roč. 9, č. 3 (2017), č. článku UNSP 240. ISSN 2072-4292 Institutional support: RVO:67985891 Keywords : granulometry * UAV * photogrammetry * fluvial geomorphology * alluvial sediment Subject RIV: DA - Hydrology ; Limnology OBOR OECD: Physical geography Impact factor: 3.244, year: 2016

  20. Enabling UAV Navigation with Sensor and Environmental Uncertainty in Cluttered and GPS-Denied Environments

    Directory of Open Access Journals (Sweden)

    Fernando Vanegas

    2016-05-01

    Full Text Available Unmanned Aerial Vehicles (UAV can navigate with low risk in obstacle-free environments using ground control stations that plan a series of GPS waypoints as a path to follow. This GPS waypoint navigation does however become dangerous in environments where the GPS signal is faulty or is only present in some places and when the airspace is filled with obstacles. UAV navigation then becomes challenging because the UAV uses other sensors, which in turn generate uncertainty about its localisation and motion systems, especially if the UAV is a low cost platform. Additional uncertainty affects the mission when the UAV goal location is only partially known and can only be discovered by exploring and detecting a target. This navigation problem is established in this research as a Partially-Observable Markov Decision Process (POMDP, so as to produce a policy that maps a set of motion commands to belief states and observations. The policy is calculated and updated on-line while flying with a newly-developed system for UAV Uncertainty-Based Navigation (UBNAV, to navigate in cluttered and GPS-denied environments using observations and executing motion commands instead of waypoints. Experimental results in both simulation and real flight tests show that the UAV finds a path on-line to a region where it can explore and detect a target without colliding with obstacles. UBNAV provides a new method and an enabling technology for scientists to implement and test UAV navigation missions with uncertainty where targets must be detected using on-line POMDP in real flight scenarios.

  1. Enabling UAV Navigation with Sensor and Environmental Uncertainty in Cluttered and GPS-Denied Environments.

    Science.gov (United States)

    Vanegas, Fernando; Gonzalez, Felipe

    2016-05-10

    Unmanned Aerial Vehicles (UAV) can navigate with low risk in obstacle-free environments using ground control stations that plan a series of GPS waypoints as a path to follow. This GPS waypoint navigation does however become dangerous in environments where the GPS signal is faulty or is only present in some places and when the airspace is filled with obstacles. UAV navigation then becomes challenging because the UAV uses other sensors, which in turn generate uncertainty about its localisation and motion systems, especially if the UAV is a low cost platform. Additional uncertainty affects the mission when the UAV goal location is only partially known and can only be discovered by exploring and detecting a target. This navigation problem is established in this research as a Partially-Observable Markov Decision Process (POMDP), so as to produce a policy that maps a set of motion commands to belief states and observations. The policy is calculated and updated on-line while flying with a newly-developed system for UAV Uncertainty-Based Navigation (UBNAV), to navigate in cluttered and GPS-denied environments using observations and executing motion commands instead of waypoints. Experimental results in both simulation and real flight tests show that the UAV finds a path on-line to a region where it can explore and detect a target without colliding with obstacles. UBNAV provides a new method and an enabling technology for scientists to implement and test UAV navigation missions with uncertainty where targets must be detected using on-line POMDP in real flight scenarios.

  2. Design of Autonomous Navigation Controllers for Unmanned Aerial Vehicles Using Multi-Objective Genetic Programming

    National Research Council Canada - National Science Library

    Barlow, Gregory J

    2004-01-01

    Unmanned aerial vehicles (UAVs) have become increasingly popular for many applications, including search and rescue, surveillance, and electronic warfare, but almost all UAVs are controlled remotely by humans...

  3. Modeling and Inverse Controller Design for an Unmanned Aerial Vehicle Based on the Self-Organizing Map

    Science.gov (United States)

    Cho, Jeongho; Principe, Jose C.; Erdogmus, Deniz; Motter, Mark A.

    2005-01-01

    The next generation of aircraft will have dynamics that vary considerably over the operating regime. A single controller will have difficulty to meet the design specifications. In this paper, a SOM-based local linear modeling scheme of an unmanned aerial vehicle (UAV) is developed to design a set of inverse controllers. The SOM selects the operating regime depending only on the embedded output space information and avoids normalization of the input data. Each local linear model is associated with a linear controller, which is easy to design. Switching of the controllers is done synchronously with the active local linear model that tracks the different operating conditions. The proposed multiple modeling and control strategy has been successfully tested in a simulator that models the LoFLYTE UAV.

  4. Teleoperated Visual Inspection and Surveillance with Unmanned Ground and Aerial Vehicles

    Directory of Open Access Journals (Sweden)

    Viatcheslav Tretyakov

    2008-11-01

    Full Text Available This paper introduces our robotic system named UGAV (Unmanned Ground-Air Vehicle consisting of two semi-autonomous robot platforms, an Unmanned Ground Vehicle (UGV and an Unmanned Aerial Vehicles (UAV. The paper focuses on three topics of the inspection with the combined UGV and UAV: (A teleoperated control by means of cell or smart phones with a new concept of automatic configuration of the smart phone based on a RKI-XML description of the vehicles control capabilities, (B the camera and vision system with the focus to real time feature extraction e.g. for the tracking of the UAV and (C the architecture and hardware of the UAV

  5. SAR system development for UAV multicopter platforms

    OpenAIRE

    Escartin Martínez, Antonio

    2015-01-01

    SAR system development for UAV multicopter platforms This thesis describes the optimization of a synthetic aperture radar (SAR) at X-band and its integration into an unmanned aerial vehicle (UAV) of type octocopter. For such optimization the SAR system functionality was extended from singlepol to fulpol and it has been optimized at hardware level in order to improve its quality against noise figure. After its integration into the octocopter platform, its features has been used in order to ...

  6. Precise Positioning of Uavs - Dealing with Challenging Rtk-Gps Measurement Conditions during Automated Uav Flights

    Science.gov (United States)

    Zimmermann, F.; Eling, C.; Klingbeil, L.; Kuhlmann, H.

    2017-08-01

    For some years now, UAVs (unmanned aerial vehicles) are commonly used for different mobile mapping applications, such as in the fields of surveying, mining or archeology. To improve the efficiency of these applications an automation of the flight as well as the processing of the collected data is currently aimed at. One precondition for an automated mapping with UAVs is that the georeferencing is performed directly with cm-accuracies or better. Usually, a cm-accurate direct positioning of UAVs is based on an onboard multi-sensor system, which consists of an RTK-capable (real-time kinematic) GPS (global positioning system) receiver and additional sensors (e.g. inertial sensors). In this case, the absolute positioning accuracy essentially depends on the local GPS measurement conditions. Especially during mobile mapping applications in urban areas, these conditions can be very challenging, due to a satellite shadowing, non-line-of sight receptions, signal diffraction or multipath effects. In this paper, two straightforward and easy to implement strategies will be described and analyzed, which improve the direct positioning accuracies for UAV-based mapping and surveying applications under challenging GPS measurement conditions. Based on a 3D model of the surrounding buildings and vegetation in the area of interest, a GPS geometry map is determined, which can be integrated in the flight planning process, to avoid GPS challenging environments as far as possible. If these challenging environments cannot be avoided, the GPS positioning solution is improved by using obstruction adaptive elevation masks, to mitigate systematic GPS errors in the RTK-GPS positioning. Simulations and results of field tests demonstrate the profit of both strategies.

  7. Use of UAV-Borne Spectrometer for Land Cover Classification

    Directory of Open Access Journals (Sweden)

    Sowmya Natesan

    2018-04-01

    Full Text Available Unmanned aerial vehicles (UAV are being used for low altitude remote sensing for thematic land classification using visible light and multi-spectral sensors. The objective of this work was to investigate the use of UAV equipped with a compact spectrometer for land cover classification. The UAV platform used was a DJI Flamewheel F550 hexacopter equipped with GPS and Inertial Measurement Unit (IMU navigation sensors, and a Raspberry Pi processor and camera module. The spectrometer used was the FLAME-NIR, a near-infrared spectrometer for hyperspectral measurements. RGB images and spectrometer data were captured simultaneously. As spectrometer data do not provide continuous terrain coverage, the locations of their ground elliptical footprints were determined from the bundle adjustment solution of the captured images. For each of the spectrometer ground ellipses, the land cover signature at the footprint location was determined to enable the characterization, identification, and classification of land cover elements. To attain a continuous land cover classification map, spatial interpolation was carried out from the irregularly distributed labeled spectrometer points. The accuracy of the classification was assessed using spatial intersection with the object-based image classification performed using the RGB images. Results show that in homogeneous land cover, like water, the accuracy of classification is 78% and in mixed classes, like grass, trees and manmade features, the average accuracy is 50%, thus, indicating the contribution of hyperspectral measurements of low altitude UAV-borne spectrometers to improve land cover classification.

  8. Water stress index for alkaline fen habitat based on UAV and continuous tower measurements of canopy infrared temperature

    Science.gov (United States)

    Ciężkowski, Wojciech; Jóźwiak, Jacek; Chormański, Jarosław; Szporak-Wasilewska, Sylwia; Kleniewska, Małgorzata

    2017-04-01

    This study is focused on developing water stress index for alkaline fen, to evaluate water stress impact on habitat protected within Natura 2000 network: alkaline fens (habitat code:7230). It is calculated based on continuous measurements of air temperature, relative humidity and canopy temperature from meteorological tower and several UAV flights for canopy temperature registration. Measurements were taken during the growing season in 2016 in the Upper Biebrza Basin in north-east Poland. Firstly methodology of the crop water stress index (CWSI) determination was used to obtained non-water stress base line based on continuous measurements (NWSBtower). Parameters of NWSBtower were directly used to calculate spatial variability of CWSI for UAV thermal infrared (TIR) images. Then for each UAV flight day at least 3 acquisition were performed to define NWSBUAV. NWSBUAV was used to calculate canopy waters stress for whole image relative to the less stressed areas. The spatial distribution of developed index was verified using remotely sensed indices of vegetation health. Results showed that in analysed area covered by sedge-moss vegetation NWSB cannot be used directly. The proposed modification of CWSI allows identifying water stress in alkaline fen habitats and was called as Sedge-Moss Water Stress Index (SMWSI). The study shows possibility of usage remotely sensed canopy temperature data to detect areas exposed to the water stress on wetlands. This research has been carried out under the Biostrateg Programme of the Polish National Centre for Research and Development (NCBiR), project No.: DZP/BIOSTRATEG-II/390/2015: The innovative approach supporting monitoring of non-forest Natura 2000 habitats, using remote sensing methods (HabitARS).

  9. Radar sensing via a Micro-UAV-borne system

    Science.gov (United States)

    Catapano, Ilaria; Ludeno, Giovanni; Gennarelli, Gianluca; Soldovieri, Francesco; Rodi Vetrella, Amedeo; Fasano, Giancarmine

    2017-04-01

    -equipped drone. The system is made by a commercial radar system, whose mass, size, power and cost budgets is compatible with the installation on micro-UAV. The radar system has been mounted on a DJI 550 UAV, a flexible hexacopter allowing both complex flight operations and static flight, and has been equipped with small size log-periodic antennas, having a 6 dB gain over the frequency range from 2 GHz to 11 GHz. An ad-hoc signal processing chain has been adopted to process the collected raw data and obtain an image of the investigated scenario providing an accurate target detection and localization. This chain involves a SVD-based noise filter procedure and an advanced data processing approach, which assumes a linear model of the underlying scattering phenomenon. REFERENCES [1] K. Whitehead, C. H. Hugenholtz, "Remote sensing of the environment with small unmanned aircraft systems (UASs), part 1: a review of progress and challenges", J. Unmanned Vehicle Systems, vol.2, pp. 69-85, 2014. [2] K. Ouchi, Recent trend and advance of synthetic aperture radar with selected topics, Remote Sens, vol.5, pp.716-807, 2013. [3] D. Altdor et al., UAV-borne electromagnetic induction and ground-penetrating radar measurements: a feasibility test, 74th Annual Meeting of the Deutsche Geophysikalische Gesellschaft in Karlsruhe, Germany, March 9 - 13, 2014.

  10. Multimodel Predictive Control Approach for UAV Formation Flight

    Directory of Open Access Journals (Sweden)

    Chang-jian Ru

    2014-01-01

    Full Text Available Formation flight problem is the most important and interesting problem of multiple UAVs (unmanned aerial vehicles cooperative control. In this paper, a novel approach for UAV formation flight based on multimodel predictive control is designed. Firstly, the state equation of relative motion is obtained and then discretized. By the geometrical method, the characteristic points of state are determined. Afterwards, based on the linearization technique, the standard linear discrete model is obtained at each characteristic state point. Then, weighted model set is proposed using the idea of T-S (Takagi-Sugeno fuzzy control and the predictive control is carried out based on the multimodel method. Finally, to verify the performance of the proposed method, two different simulation scenarios are performed.

  11. Estimation and Extrapolation of Tree Parameters Using Spectral Correlation between UAV and Pléiades Data

    Directory of Open Access Journals (Sweden)

    Azadeh Abdollahnejad

    2018-02-01

    Full Text Available The latest technological advances in space-borne imagery have significantly enhanced the acquisition of high-quality data. With the availability of very high-resolution satellites, such as Pléiades, it is now possible to estimate tree parameters at the individual level with high fidelity. Despite innovative advantages on high-precision satellites, data acquisition is not yet available to the public at a reasonable cost. Unmanned aerial vehicles (UAVs have the practical advantage of data acquisition at a higher spatial resolution than that of satellites. This study is divided into two main parts: (1 we describe the estimation of basic tree attributes, such as tree height, crown diameter, diameter at breast height (DBH, and stem volume derived from UAV data based on structure from motion (SfM algorithms; and (2 we consider the extrapolation of the UAV data to a larger area, using correlation between satellite and UAV observations as an economically viable approach. Results have shown that UAVs can be used to predict tree characteristics with high accuracy (i.e., crown projection, stem volume, cross-sectional area (CSA, and height. We observed a significant relation between extracted data from UAV and ground data with R2 = 0.71 for stem volume, R2 = 0.87 for height, and R2 = 0.60 for CSA. In addition, our results showed a high linear relation between spectral data from the UAV and the satellite (R2 = 0.94. Overall, the accuracy of the results between UAV and Pléiades was reasonable and showed that the used methods are feasible for extrapolation of extracted data from UAV to larger areas.

  12. UAV-based remote sensing surveys of lava flow fields: a case study from Etna's 1974 channel-fed lava flows

    Science.gov (United States)

    Favalli, Massimiliano; Fornaciai, Alessandro; Nannipieri, Luca; Harris, Andrew; Calvari, Sonia; Lormand, Charline

    2018-03-01

    During an eruption, time scales of topographic change are fast and involve vertical and planimetric evolution of millimeters to meters as the event progresses. Repeat production of high spatial resolution terrain models of lava flow fields over time scales of a few hours is thus a high-value capability in tracking the buildup of the deposit. Among the wide range of terrestrial and aerial methods available to collect such topographic data, the use of an unmanned aerial vehicle (UAV) as an acquisition platform, together with structure from motion (SfM) photogrammetry, has become especially useful. This approach allows high-frequency production of centimeter-scale terrain models over kilometer-scale areas, including dangerous and inaccessible zones, with low cost and minimal hazard to personnel. This study presents the application of such an integrated UAV-SfM method to generate a high spatial resolution digital terrain model and orthomosaic of Mount Etna's January-February 1974 lava flow field. The SfM method, applied to images acquired using a UAV platform, enabled the extraction of a very high spatial resolution (20 cm) digital elevation model and the generation of a 3-cm orthomosaic covering an area of 1.35 km2. This spatial resolution enabled us to analyze the morphology of sub-meter-scale features, such as folds, blocks, and cracks, over kilometer-scale areas. The 3-cm orthomosaic allowed us to further push the analysis to centimeter-scale grain size distribution of the lava surface. Using these data, we define three types of crust structure and relate them to positions within a channel-fed ´áā flow system. These crust structures are (i) flow parallel shear lines, (ii) raft zones, and (iii) folded zones. Flow parallel shear lines are found at the channel edges, and are 2-m-wide and 0.25-m-deep zones running along the levee base and in which cracking is intense. They result from intense shearing between the moving channel lava and the static levee lava. In

  13. Radical advancement in multi-spectral imaging for autonomous vehicles (UAVs, UGVs, and UUVs) using active compensation.

    Energy Technology Data Exchange (ETDEWEB)

    Clark, Brian F.; Bagwell, Brett E.; Wick, David Victor

    2007-01-01

    The purpose of this LDRD was to demonstrate a compact, multi-spectral, refractive imaging systems using active optical compensation. Compared to a comparable, conventional lens system, our system has an increased operational bandwidth, provides for spectral selectivity and, non-mechanically corrects aberrations induced by the wavelength dependent properties of a passive refractive optical element (i.e. lens). The compact nature and low power requirements of the system lends itself to small platforms such as autonomous vehicles. In addition, the broad spectral bandwidth of our system would allow optimized performance for both day/night use, and the multi-spectral capability allows for spectral discrimination and signature identification.

  14. UAV Trajectory Modeling Using Neural Networks

    Science.gov (United States)

    Xue, Min

    2017-01-01

    Large amount of small Unmanned Aerial Vehicles (sUAVs) are projected to operate in the near future. Potential sUAV applications include, but not limited to, search and rescue, inspection and surveillance, aerial photography and video, precision agriculture, and parcel delivery. sUAVs are expected to operate in the uncontrolled Class G airspace, which is at or below 500 feet above ground level (AGL), where many static and dynamic constraints exist, such as ground properties and terrains, restricted areas, various winds, manned helicopters, and conflict avoidance among sUAVs. How to enable safe, efficient, and massive sUAV operations at the low altitude airspace remains a great challenge. NASA's Unmanned aircraft system Traffic Management (UTM) research initiative works on establishing infrastructure and developing policies, requirement, and rules to enable safe and efficient sUAVs' operations. To achieve this goal, it is important to gain insights of future UTM traffic operations through simulations, where the accurate trajectory model plays an extremely important role. On the other hand, like what happens in current aviation development, trajectory modeling should also serve as the foundation for any advanced concepts and tools in UTM. Accurate models of sUAV dynamics and control systems are very important considering the requirement of the meter level precision in UTM operations. The vehicle dynamics are relatively easy to derive and model, however, vehicle control systems remain unknown as they are usually kept by manufactures as a part of intellectual properties. That brings challenges to trajectory modeling for sUAVs. How to model the vehicle's trajectories with unknown control system? This work proposes to use a neural network to model a vehicle's trajectory. The neural network is first trained to learn the vehicle's responses at numerous conditions. Once being fully trained, given current vehicle states, winds, and desired future trajectory, the neural

  15. UAV Research, Operations, and Flight Test at the NASA Dryden Flight Research Center

    Science.gov (United States)

    Cosentino, Gary B.

    2009-01-01

    This slide presentation reviews some of the projects that have extended NASA Dryden's capabilities in designing, testing, and using Unmanned Aerial Vehicles (UAV's). Some of the UAV's have been for Science and experimental applications, some have been for flight research and demonstration purposes, and some have been small UAV's for other customers.

  16. A Stereo Dual-Channel Dynamic Programming Algorithm for UAV Image Stitching.

    Science.gov (United States)

    Li, Ming; Chen, Ruizhi; Zhang, Weilong; Li, Deren; Liao, Xuan; Wang, Lei; Pan, Yuanjin; Zhang, Peng

    2017-09-08

    Dislocation is one of the major challenges in unmanned aerial vehicle (UAV) image stitching. In this paper, we propose a new algorithm for seamlessly stitching UAV images based on a dynamic programming approach. Our solution consists of two steps: Firstly, an image matching algorithm is used to correct the images so that they are in the same coordinate system. Secondly, a new dynamic programming algorithm is developed based on the concept of a stereo dual-channel energy accumulation. A new energy aggregation and traversal strategy is adopted in our solution, which can find a more optimal seam line for image stitching. Our algorithm overcomes the theoretical limitation of the classical Duplaquet algorithm. Experiments show that the algorithm can effectively solve the dislocation problem in UAV image stitching, especially for the cases in dense urban areas. Our solution is also direction-independent, which has better adaptability and robustness for stitching images.

  17. Modeling and Flocking Consensus Analysis for Large-Scale UAV Swarms

    Directory of Open Access Journals (Sweden)

    Li Bing

    2013-01-01

    Full Text Available Recently, distributed coordination control of the unmanned aerial vehicle (UAV swarms has been a particularly active topic in intelligent system field. In this paper, through understanding the emergent mechanism of the complex system, further research on the flocking and the dynamic characteristic of UAV swarms will be given. Firstly, this paper analyzes the current researches and existent problems of UAV swarms. Afterwards, by the theory of stochastic process and supplemented variables, a differential-integral model is established, converting the system model into Volterra integral equation. The existence and uniqueness of the solution of the system are discussed. Then the flocking control law is given based on artificial potential with system consensus. At last, we analyze the stability of the proposed flocking control algorithm based on the Lyapunov approach and prove that the system in a limited time can converge to the consensus direction of the velocity. Simulation results are provided to verify the conclusion.

  18. Route constraints model based on polychromatic sets

    Science.gov (United States)

    Yin, Xianjun; Cai, Chao; Wang, Houjun; Li, Dongwu

    2018-03-01

    With the development of unmanned aerial vehicle (UAV) technology, the fields of its application are constantly expanding. The mission planning of UAV is especially important, and the planning result directly influences whether the UAV can accomplish the task. In order to make the results of mission planning for unmanned aerial vehicle more realistic, it is necessary to consider not only the physical properties of the aircraft, but also the constraints among the various equipment on the UAV. However, constraints among the equipment of UAV are complex, and the equipment has strong diversity and variability, which makes these constraints difficult to be described. In order to solve the above problem, this paper, referring to the polychromatic sets theory used in the advanced manufacturing field to describe complex systems, presents a mission constraint model of UAV based on polychromatic sets.

  19. Design of Power Cable UAV Intelligent Patrol System Based on Adaptive Kalman Filter Fuzzy PID Control

    Directory of Open Access Journals (Sweden)

    Chen Siyu

    2017-01-01

    Full Text Available Patrol UAV has poor aerial posture stability and is largely affected by anthropic factors, which lead to some shortages such as low power cable tracking precision, captured image loss and inconvenient temperature measurement, etc. In order to solve these disadvantages, this article puts forward a power cable intelligent patrol system. The core innovation of the system is a 360° platform. This collects the position information of power cables by using far infrared sensors and carries out real-time all-direction adjustment of UAV lifting platform through the adaptive Kalman filter fuzzy PID control algorithm, so that the precise tracking of power cables is achieved. An intelligent patrol system is established to detect the faults more accurately, so that a high intelligence degree of power cable patrol system is realized.

  20. Airborne gamma spectrometric survey in the Chernobyl exclusion zone based on oktokopter UAV type

    International Nuclear Information System (INIS)

    Zabulonov, Yu.L.; Burtnyak, V.M.; Zolkin, I.O.

    2015-01-01

    The results of field studies of radioactive contamination condition of RWTSP ''Red Forest'' and ''Neftebaza'' in the Chernobyl zone, obtained by the authors in June 2015 are represented. The technique of detection of local inhomogeneities on the soil surface without contrasting borders by airborne gamma spectrometry from the board of oktokopter UAV type is worked through. The technique of searching and contouring of hidden burial of radioactive waste is practiced

  1. Detection, Location and Grasping Objects Using a Stereo Sensor on UAV in Outdoor Environments

    Directory of Open Access Journals (Sweden)

    Pablo Ramon Soria

    2017-01-01

    Full Text Available The article presents a vision system for the autonomous grasping of objects with Unmanned Aerial Vehicles (UAVs in real time. Giving UAVs the capability to manipulate objects vastly extends their applications, as they are capable of accessing places that are difficult to reach or even unreachable for human beings. This work is focused on the grasping of known objects based on feature models. The system runs in an on-board computer on a UAV equipped with a stereo camera and a robotic arm. The algorithm learns a feature-based model in an offline stage, then it is used online for detection of the targeted object and estimation of its position. This feature-based model was proved to be robust to both occlusions and the presence of outliers. The use of stereo cameras improves the learning stage, providing 3D information and helping to filter features in the online stage. An experimental system was derived using a rotary-wing UAV and a small manipulator for final proof of concept. The robotic arm is designed with three degrees of freedom and is lightweight due to payload limitations of the UAV. The system has been validated with different objects, both indoors and outdoors.

  2. Evolving Self-Organized Behavior for Homogeneous and Heterogeneous UAV or UCAV Swarms

    National Research Council Canada - National Science Library

    Price, Ian C

    2006-01-01

    This investigation uses a self-organization (SO) approach to enable cooperative search and destruction of retaliating targets with swarms of homogeneous and heterogeneous unmanned aerial vehicles (UAVs...

  3. A Multi-Disciplinary Approach to Remote Sensing through Low-Cost UAVs.

    Science.gov (United States)

    Calvario, Gabriela; Sierra, Basilio; Alarcón, Teresa E; Hernandez, Carmen; Dalmau, Oscar

    2017-06-16

    The use of Unmanned Aerial Vehicles (UAVs) based on remote sensing has generated low cost monitoring, since the data can be acquired quickly and easily. This paper reports the experience related to agave crop analysis with a low cost UAV. The data were processed by traditional photogrammetric flow and data extraction techniques were applied to extract new layers and separate the agave plants from weeds and other elements of the environment. Our proposal combines elements of photogrammetry, computer vision, data mining, geomatics and computer science. This fusion leads to very interesting results in agave control. This paper aims to demonstrate the potential of UAV monitoring in agave crops and the importance of information processing with reliable data flow.

  4. Automatic Hotspot and Sun Glint Detection in UAV Multispectral Images.

    Science.gov (United States)

    Ortega-Terol, Damian; Hernandez-Lopez, David; Ballesteros, Rocio; Gonzalez-Aguilera, Diego

    2017-10-15

    Last advances in sensors, photogrammetry and computer vision have led to high-automation levels of 3D reconstruction processes for generating dense models and multispectral orthoimages from Unmanned Aerial Vehicle (UAV) images. However, these cartographic products are sometimes blurred and degraded due to sun reflection effects which reduce the image contrast and colour fidelity in photogrammetry and the quality of radiometric values in remote sensing applications. This paper proposes an automatic approach for detecting sun reflections problems (hotspot and sun glint) in multispectral images acquired with an Unmanned Aerial Vehicle (UAV), based on a photogrammetric strategy included in a flight planning and control software developed by the authors. In particular, two main consequences are derived from the approach developed: (i) different areas of the images can be excluded since they contain sun reflection problems; (ii) the cartographic products obtained (e.g., digital terrain model, orthoimages) and the agronomical parameters computed (e.g., normalized vegetation index-NVDI) are improved since radiometric defects in pixels are not considered. Finally, an accuracy assessment was performed in order to analyse the error in the detection process, getting errors around 10 pixels for a ground sample distance (GSD) of 5 cm which is perfectly valid for agricultural applications. This error confirms that the precision in the detection of sun reflections can be guaranteed using this approach and the current low-cost UAV technology.

  5. High-Fidelity Solar Power Income Modeling for Solar-Electric UAVs: Development and Flight Test Based Verification

    OpenAIRE

    Oettershagen, Philipp

    2017-01-01

    Solar power models are a crucial element of solar-powered UAV design and performance analysis. During the conceptual design phase, their accuracy directly relates to the accuracy of the predicted performance metrics and thus the final design characteristics of the solar-powered UAV. Likewise, during the operations phase of a solar-powered UAV accurate solar power income models are required to predict and assess the solar power system performance. However, the existing literature on solar-powe...

  6. Video change detection for fixed wing UAVs

    Science.gov (United States)

    Bartelsen, Jan; Müller, Thomas; Ring, Jochen; Mück, Klaus; Brüstle, Stefan; Erdnüß, Bastian; Lutz, Bastian; Herbst, Theresa

    2017-10-01

    In this paper we proceed the work of Bartelsen et al.1 We present the draft of a process chain for an image based change detection which is designed for videos acquired by fixed wing unmanned aerial vehicles (UAVs). From our point of view, automatic video change detection for aerial images can be useful to recognize functional activities which are typically caused by the deployment of improvised explosive devices (IEDs), e.g. excavations, skid marks, footprints, left-behind tooling equipment, and marker stones. Furthermore, in case of natural disasters, like flooding, imminent danger can be recognized quickly. Due to the necessary flight range, we concentrate on fixed wing UAVs. Automatic change detection can be reduced to a comparatively simple photogrammetric problem when the perspective change between the "before" and "after" image sets is kept as small as possible. Therefore, the aerial image acquisition demands a mission planning with a clear purpose including flight path and sensor configuration. While the latter can be enabled simply by a fixed and meaningful adjustment of the camera, ensuring a small perspective change for "before" and "after" videos acquired by fixed wing UAVs is a challenging problem. Concerning this matter, we have performed tests with an advanced commercial off the shelf (COTS) system which comprises a differential GPS and autopilot system estimating the repetition accuracy of its trajectory. Although several similar approaches have been presented,23 as far as we are able to judge, the limits for this important issue are not estimated so far. Furthermore, we design a process chain to enable the practical utilization of video change detection. It consists of a front-end of a database to handle large amounts of video data, an image processing and change detection implementation, and the visualization of the results. We apply our process chain on the real video data acquired by the advanced COTS fixed wing UAV and synthetic data. For the

  7. Analysis of Vehicle-Based Security Operations

    Energy Technology Data Exchange (ETDEWEB)

    Carter, Jason M [ORNL; Paul, Nate R [ORNL

    2015-01-01

    Vehicle-to-vehicle (V2V) communications promises to increase roadway safety by providing each vehicle with 360 degree situational awareness of other vehicles in proximity, and by complementing onboard sensors such as radar or camera in detecting imminent crash scenarios. In the United States, approximately three hundred million automobiles could participate in a fully deployed V2V system if Dedicated Short-Range Communication (DSRC) device use becomes mandatory. The system s reliance on continuous communication, however, provides a potential means for unscrupulous persons to transmit false data in an attempt to cause crashes, create traffic congestion, or simply render the system useless. V2V communications must be highly scalable while retaining robust security and privacy preserving features to meet the intra-vehicle and vehicle-to-infrastructure communication requirements for a growing vehicle population. Oakridge National Research Laboratory is investigating a Vehicle-Based Security System (VBSS) to provide security and privacy for a fully deployed V2V and V2I system. In the VBSS an On-board Unit (OBU) generates short-term certificates and signs Basic Safety Messages (BSM) to preserve privacy and enhance security. This work outlines a potential VBSS structure and its operational concepts; it examines how a vehicle-based system might feasibly provide security and privacy, highlights remaining challenges, and explores potential mitigations to address those challenges. Certificate management alternatives that attempt to meet V2V security and privacy requirements have been examined previously by the research community including privacy-preserving group certificates, shared certificates, and functional encryption. Due to real-world operational constraints, adopting one of these approaches for VBSS V2V communication is difficult. Timely misbehavior detection and revocation are still open problems for any V2V system. We explore the alternative approaches that may be

  8. Spurious RF signals emitted by mini-UAVs

    Science.gov (United States)

    Schleijpen, Ric (H. M. A.); Voogt, Vincent; Zwamborn, Peter; van den Oever, Jaap

    2016-10-01

    This paper presents experimental work on the detection of spurious RF emissions of mini Unmanned Aerial Vehicles (mini-UAV). Many recent events have shown that mini-UAVs can be considered as a potential threat for civil security. For this reason the detection of mini-UAVs has become of interest to the sensor community. The detection, classification and identification chain can take advantage of different sensor technologies. Apart from the signatures used by radar and electro-optical sensor systems, the UAV also emits RF signals. These RF signatures can be split in intentional signals for communication with the operator and un-intentional RF signals emitted by the UAV. These unintentional or spurious RF emissions are very weak but could be used to discriminate potential UAV detections from false alarms. The goal of this research was to assess the potential of exploiting spurious emissions in the classification and identification chain of mini-UAVs. It was already known that spurious signals are very weak, but the focus was on the question whether the emission pattern could be correlated to the behaviour of the UAV. In this paper experimental examples of spurious RF emission for different types of mini-UAVs and their correlation with the electronic circuits in the UAVs will be shown

  9. Passivity-Based Control for a Micro Air Vehicle Using Unit Quaternions

    Directory of Open Access Journals (Sweden)

    Maria Eusebia Guerrero-Sanchez

    2016-12-01

    Full Text Available In this paper the development and practical implementation of a Passivity-Based Control (PBC algorithm to stabilize an Unmanned Aerial Vehicle (UAV described with unit quaternions are presented. First, a mathematical model based on Euler-Lagrange formulation using a logarithmic mapping in the quaternion space is introduced. Then, a new methodology: a quaternion-passivity-based control is derived, which does not compute excessive and complex Partial Differential Equations (PDEs for synthesizing the control law, making a significant advantage in comparison with other methodologies. Therefore, the control design to a system as the quad-rotor is easily solved by the proposed methodology. Another advantage is the possibility to stabilize quad-rotor full dynamics which may not be possible with classical PBC techniques. Experimental results and numerical simulations to validate our proposed scheme are presented.

  10. Teaching UAVs to Race Using UE4Sim

    KAUST Repository

    Mueller, Matthias

    2017-08-19

    Automating the navigation of unmanned aerial vehicles (UAVs) in diverse scenarios has gained much attention in the recent years. However, teaching UAVs to fly in challenging environments remains an unsolved problem, mainly due to the lack of data for training. In this paper, we develop a photo-realistic simulator that can afford the generation of large amounts of training data (both images rendered from the UAV camera and its controls) to teach a UAV to autonomously race through challenging tracks. We train a deep neural network to predict UAV controls from raw image data for the task of autonomous UAV racing. Training is done through imitation learning enabled by data augmentation to allow for the correction of navigation mistakes. Extensive experiments demonstrate that our trained network (when sufficient data augmentation is used) outperforms state-of-the-art methods and flies more consistently than many human pilots.

  11. Teaching UAVs to Race Using UE4Sim

    KAUST Repository

    Mueller, Matthias; Casser, Vincent; Smith, Neil; Michels, Dominik L.; Ghanem, Bernard

    2017-01-01

    Automating the navigation of unmanned aerial vehicles (UAVs) in diverse scenarios has gained much attention in the recent years. However, teaching UAVs to fly in challenging environments remains an unsolved problem, mainly due to the lack of data for training. In this paper, we develop a photo-realistic simulator that can afford the generation of large amounts of training data (both images rendered from the UAV camera and its controls) to teach a UAV to autonomously race through challenging tracks. We train a deep neural network to predict UAV controls from raw image data for the task of autonomous UAV racing. Training is done through imitation learning enabled by data augmentation to allow for the correction of navigation mistakes. Extensive experiments demonstrate that our trained network (when sufficient data augmentation is used) outperforms state-of-the-art methods and flies more consistently than many human pilots.

  12. Vehicle security encryption based on unlicensed encryption

    Science.gov (United States)

    Huang, Haomin; Song, Jing; Xu, Zhijia; Ding, Xiaoke; Deng, Wei

    2018-03-01

    The current vehicle key is easy to be destroyed and damage, proposing the use of elliptical encryption algorithm is improving the reliability of vehicle security system. Based on the encryption rules of elliptic curve, the chip's framework and hardware structure are designed, then the chip calculation process simulation has been analyzed by software. The simulation has been achieved the expected target. Finally, some issues pointed out in the data calculation about the chip's storage control and other modules.

  13. Simulation to Flight Test for a UAV Controls Testbed

    Science.gov (United States)

    Motter, Mark A.; Logan, Michael J.; French, Michael L.; Guerreiro, Nelson M.

    2006-01-01

    The NASA Flying Controls Testbed (FLiC) is a relatively small and inexpensive unmanned aerial vehicle developed specifically to test highly experimental flight control approaches. The most recent version of the FLiC is configured with 16 independent aileron segments, supports the implementation of C-coded experimental controllers, and is capable of fully autonomous flight from takeoff roll to landing, including flight test maneuvers. The test vehicle is basically a modified Army target drone, AN/FQM-117B, developed as part of a collaboration between the Aviation Applied Technology Directorate (AATD) at Fort Eustis, Virginia and NASA Langley Research Center. Several vehicles have been constructed and collectively have flown over 600 successful test flights, including a fully autonomous demonstration at the Association of Unmanned Vehicle Systems International (AUVSI) UAV Demo 2005. Simulations based on wind tunnel data are being used to further develop advanced controllers for implementation and flight test.

  14. Automated Snow Extent Mapping Based on Orthophoto Images from Unmanned Aerial Vehicles

    Science.gov (United States)

    Niedzielski, Tomasz; Spallek, Waldemar; Witek-Kasprzak, Matylda

    2018-04-01

    The paper presents the application of the k-means clustering in the process of automated snow extent mapping using orthophoto images generated using the Structure-from-Motion (SfM) algorithm from oblique aerial photographs taken by unmanned aerial vehicle (UAV). A simple classification approach has been implemented to discriminate between snow-free and snow-covered terrain. The procedure uses the k-means clustering and classifies orthophoto images based on the three-dimensional space of red-green-blue (RGB) or near-infrared-red-green (NIRRG) or near-infrared-green-blue (NIRGB) bands. To test the method, several field experiments have been carried out, both in situations when snow cover was continuous and when it was patchy. The experiments have been conducted using three fixed-wing UAVs (swinglet CAM by senseFly, eBee by senseFly, and Birdie by FlyTech UAV) on 10/04/2015, 23/03/2016, and 16/03/2017 within three test sites in the Izerskie Mountains in southwestern Poland. The resulting snow extent maps, produced automatically using the classification method, have been validated against real snow extents delineated through a visual analysis and interpretation offered by human analysts. For the simplest classification setup, which assumes two classes in the k-means clustering, the extent of snow patches was estimated accurately, with areal underestimation of 4.6% (RGB) and overestimation of 5.5% (NIRGB). For continuous snow cover with sparse discontinuities at places where trees or bushes protruded from snow, the agreement between automatically produced snow extent maps and observations was better, i.e. 1.5% (underestimation with RGB) and 0.7-0.9% (overestimation, either with RGB or with NIRRG). Shadows on snow were found to be mainly responsible for the misclassification.

  15. Evaluating the effectiveness of low cost UAV generated topography for geomorphic change detection

    Science.gov (United States)

    Cook, K. L.

    2014-12-01

    With the recent explosion in the use and availability of unmanned aerial vehicle platforms and development of easy to use structure from motion software, UAV based photogrammetry is increasingly being adopted to produce high resolution topography for the study of surface processes. UAV systems can vary substantially in price and complexity, but the tradeoffs between these and the quality of the resulting data are not well constrained. We look at one end of this spectrum and evaluate the effectiveness of a simple low cost UAV setup for obtaining high resolution topography in a challenging field setting. Our study site is the Daan River gorge in western Taiwan, a rapidly eroding bedrock gorge that we have monitored with terrestrial Lidar since 2009. The site presents challenges for the generation and analysis of high resolution topography, including vertical gorge walls, vegetation, wide variation in surface roughness, and a complicated 3D morphology. In order to evaluate the accuracy of the UAV-derived topography, we compare it with terrestrial Lidar data collected during the same survey period. Our UAV setup combines a DJI Phantom 2 quadcopter with a 16 megapixel Canon Powershot camera for a total platform cost of less than $850. The quadcopter is flown manually, and the camera is programmed to take a photograph every 5 seconds, yielding 200-250 pictures per flight. We measured ground control points and targets for both the Lidar scans and the aerial surveys using a Leica RTK GPS with 1-2 cm accuracy. UAV derived point clouds were obtained using Agisoft Photoscan software. We conducted both Lidar and UAV surveys before and after a summer typhoon season, allowing us to evaluate the reliability of the UAV survey to detect geomorphic changes in the range of one to several meters. We find that this simple UAV setup can yield point clouds with an average accuracy on the order of 10 cm compared to the Lidar point clouds. Well-distributed and accurately located ground

  16. A Space-Time Network-Based Modeling Framework for Dynamic Unmanned Aerial Vehicle Routing in Traffic Incident Monitoring Applications

    Directory of Open Access Journals (Sweden)

    Jisheng Zhang

    2015-06-01

    Full Text Available It is essential for transportation management centers to equip and manage a network of fixed and mobile sensors in order to quickly detect traffic incidents and further monitor the related impact areas, especially for high-impact accidents with dramatic traffic congestion propagation. As emerging small Unmanned Aerial Vehicles (UAVs start to have a more flexible regulation environment, it is critically important to fully explore the potential for of using UAVs for monitoring recurring and non-recurring traffic conditions and special events on transportation networks. This paper presents a space-time network- based modeling framework for integrated fixed and mobile sensor networks, in order to provide a rapid and systematic road traffic monitoring mechanism. By constructing a discretized space-time network to characterize not only the speed for UAVs but also the time-sensitive impact areas of traffic congestion, we formulate the problem as a linear integer programming model to minimize the detection delay cost and operational cost, subject to feasible flying route constraints. A Lagrangian relaxation solution framework is developed to decompose the original complex problem into a series of computationally efficient time-dependent and least cost path finding sub-problems. Several examples are used to demonstrate the results of proposed models in UAVs’ route planning for small and medium-scale networks.

  17. Improved Seam-Line Searching Algorithm for UAV Image Mosaic with Optical Flow.

    Science.gov (United States)

    Zhang, Weilong; Guo, Bingxuan; Li, Ming; Liao, Xuan; Li, Wenzhuo

    2018-04-16

    Ghosting and seams are two major challenges in creating unmanned aerial vehicle (UAV) image mosaic. In response to these problems, this paper proposes an improved method for UAV image seam-line searching. First, an image matching algorithm is used to extract and match the features of adjacent images, so that they can be transformed into the same coordinate system. Then, the gray scale difference, the gradient minimum, and the optical flow value of pixels in adjacent image overlapped area in a neighborhood are calculated, which can be applied to creating an energy function for seam-line searching. Based on that, an improved dynamic programming algorithm is proposed to search the optimal seam-lines to complete the UAV image mosaic. This algorithm adopts a more adaptive energy aggregation and traversal strategy, which can find a more ideal splicing path for adjacent UAV images and avoid the ground objects better. The experimental results show that the proposed method can effectively solve the problems of ghosting and seams in the panoramic UAV images.

  18. Control system design for UAV trajectory tracking

    Science.gov (United States)

    Wang, Haitao; Gao, Jinyuan

    2006-11-01

    In recent years, because of the emerging requirements for increasing autonomy, the controller of uninhabited air vehicles must be augmented with a very sophisticated autopilot design which is capable of tracking complex and agile maneuvering trajectory. This paper provides a simplified control system framework to solve UAV maneuvering trajectory tracking problem. The flight control system is divided into three subsystems including command generation, transformation and allocation. According to the kinematics equations of the aircraft, flight path angle commands can be generated by desired 3D position from path planning. These commands are transformed to body angular rates through direct nonlinear mapping, which is simpler than common multi-loop method based on time scale separation assumption. Then, by using weighted pseudo-inverse method, the control surface deflections are allocated to follow body angular rates from the previous step. In order to improve the robustness, a nonlinear disturbance observer-based approach is used to compensate the uncertainty of system. A 6DOF nonlinear UAV model is controlled to demonstrate the performance of the trajectory tracking control system. Simulation results show that the control strategy is easy to be realized and the precision of tracking is satisfying.

  19. Small VTOL UAV Acoustics Measurement and Prediction, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Interest in civilian use of small Unmanned Aerial Vehicles (UAVs) with Vertical Takeoff and Landing (VTOL) capability has increased greatly in recent years, and is...

  20. A Synthetic Teammate for UAV Applications: A Prospective Look

    National Research Council Canada - National Science Library

    Gluck, Kevin A; Ball, Jerry T; Gunzelmann, Glenn; Krusmark, Michael A; Lyon, Don R; Cooke, Nancy J

    2006-01-01

    This report describes current progress and future plans for research and development in synthetic teammates for applications in training, analysis, and system design for Uninhabited Aerial Vehicle (UAV) operations...

  1. Unmanned Aerial Vehicle Based Wireless Sensor Network for Marine-Coastal Environment Monitoring.

    Science.gov (United States)

    Trasviña-Moreno, Carlos A; Blasco, Rubén; Marco, Álvaro; Casas, Roberto; Trasviña-Castro, Armando

    2017-02-24

    Marine environments are delicate ecosystems which directly influence local climates, flora, fauna, and human activities. Their monitorization plays a key role in their preservation, which is most commonly done through the use of environmental sensing buoy networks. These devices transmit data by means of satellite communications or close-range base stations, which present several limitations and elevated infrastructure costs. Unmanned Aerial Vehicles (UAV) are another alternative for remote environmental monitoring which provide new types of data and ease of use. These aircraft are mainly used in video capture related applications, in its various light spectrums, and do not provide the same data as sensing buoys, nor can they be used for such extended periods of time. The aim of this research is to provide a flexible, easy to deploy and cost-effective Wireless Sensor Network (WSN) for monitoring marine environments. This proposal uses a UAV as a mobile data collector, low-power long-range communications and sensing buoys as part of a single WSN. A complete description of the design, development, and implementation of the various parts of this system is presented, as well as its validation in a real-world scenario.

  2. Towards Remote Estimation of Radiation Use Efficiency in Maize Using UAV-Based Low-Cost Camera Imagery

    Directory of Open Access Journals (Sweden)

    Andreas Tewes

    2018-02-01

    Full Text Available Radiation Use Efficiency (RUE defines the productivity with which absorbed photosynthetically active radiation (APAR is converted to plant biomass. Readily used in crop growth models to predict dry matter accumulation, RUE is commonly determined by elaborate static sensor measurements in the field. Different definitions are used, based on total absorbed PAR (RUEtotal or PAR absorbed by the photosynthetically active leaf tissue only (RUEgreen. Previous studies have shown that the fraction of PAR absorbed (fAPAR, which supports the assessment of RUE, can be reliably estimated via remote sensing (RS, but unfortunately at spatial resolutions too coarse for experimental agriculture. UAV-based RS offers the possibility to cover plant reflectance at very high spatial and temporal resolution, possibly covering several experimental plots in little time. We investigated if (a UAV-based low-cost camera imagery allowed estimating RUEs in different experimental plots where maize was cultivated in the growing season of 2016, (b those values were different from the ones previously reported in literature and (c there was a difference between RUEtotal and RUEgreen. We determined fractional cover and canopy reflectance based on the RS imagery. Our study found that RUEtotal ranges between 4.05 and 4.59, and RUEgreen between 4.11 and 4.65. These values are higher than those published in other research articles, but not outside the range of plausibility. The difference between RUEtotal and RUEgreen was minimal, possibly due to prolonged canopy greenness induced by the stay-green trait of the cultivar grown. The procedure presented here makes time-consuming APAR measurements for determining RUE especially in large experiments superfluous.

  3. An evaluation of a UAV guidance system with consumer grade GPS receivers

    Science.gov (United States)

    Rosenberg, Abigail Stella

    Remote sensing has been demonstrated an important tool in agricultural and natural resource management and research applications, however there are limitations that exist with traditional platforms (i.e., hand held sensors, linear moves, vehicle mounted, airplanes, remotely piloted vehicles (RPVs), unmanned aerial vehicles (UAVs) and satellites). Rapid technological advances in electronics, computers, software applications, and the aerospace industry have dramatically reduced the cost and increased the availability of remote sensing technologies. Remote sensing imagery vary in spectral, spatial, and temporal resolutions and are available from numerous providers. Appendix A presented results of a test project that acquired high-resolution aerial photography with a RPV to map the boundary of a 0.42 km2 fire area. The project mapped the boundaries of the fire area from a mosaic of the aerial images collected and compared this with ground-based measurements. The project achieved a 92.4% correlation between the aerial assessment and the ground truth data. Appendix B used multi-objective analysis to quantitatively assess the tradeoffs between different sensor platform attributes to identify the best overall technology. Experts were surveyed to identify the best overall technology at three different pixel sizes. Appendix C evaluated the positional accuracy of a relatively low cost UAV designed for high resolution remote sensing of small areas in order to determine the positional accuracy of sensor readings. The study evaluated the accuracy and uncertainty of a UAV flight route with respect to the programmed waypoints and of the UAV's GPS position, respectively. In addition, the potential displacement of sensor data was evaluated based on (1) GPS measurements on board the aircraft and (2) the autopilot's circuit board with 3-axis gyros and accelerometers (i.e., roll, pitch, and yaw). The accuracies were estimated based on a 95% confidence interval or similar methods. The

  4. Low-cost Cognitive Electronics Technology for Enhanced Communications and Situational Awareness for Networks of Small Unmanned Aerial Vehicles (UAV)

    Science.gov (United States)

    2013-03-01

    series of checkpoints in a complex route network,” while observing standard traffic etiquette and regulations [17]. The rules for the 2012 RoboCup...structure or protocols above the PHY. To support AVEP operation, we developed a packet structure based on the transmission control protocol (TCP...Control Protocol .” 1981. [37] F. Ge, Q. Chen, Y. Wang, C. W. Bostian, T. W. Rondeau, and B. Le, “Cognitive radio: from spectrum sharing to adaptive

  5. Dynamic UAV-based traffic monitoring under uncertainty as a stochastic arc-inventory routing policy

    Directory of Open Access Journals (Sweden)

    Joseph Y.J. Chow

    2016-10-01

    Full Text Available Given the rapid advances in unmanned aerial vehicles, or drones, and increasing need to monitor at a city level, one of the current research gaps is how to systematically deploy drones over multiple periods. We propose a real-time data-driven approach: we formulate the first deterministic arc-inventory routing problem and derive its stochastic dynamic policy. The policy is expected to be of greatest value in scenarios where uncertainty is highest and costliest, such as city monitoring during major events. The Bellman equation for an approximation of the proposed inventory routing policy is formulated as a selective vehicle routing problem. We propose an approximate dynamic programming algorithm based on Least Squares Monte Carlo simulation to find that policy. The algorithm has been modified so that the least squares dependent variable is defined to be the “expected stock out cost upon the next replenishment”. The new algorithm is tested on 30 simulated instances of real time trajectories over 5 time periods of the selective vehicle routing problem to evaluate the proposed policy and algorithm. Computational results on the selected instances show that the algorithm on average outperforms the myopic policy by 23–28%, depending on the parametric design. Further tests are conducted on classic benchmark arc routing problem instances. The 11-link instance gdb19 (Golden et al., 1983 is expanded into a sequential 15-period stochastic dynamic example and used to demonstrate why a naïve static multi-period deployment plan would not be effective in real networks.

  6. Rapid Extraction of Landslide and Spatial Distribution Analysis after Jiuzhaigou Ms7.0 Earthquake Based on Uav Images

    Science.gov (United States)

    Jiao, Q. S.; Luo, Y.; Shen, W. H.; Li, Q.; Wang, X.

    2018-04-01

    Jiuzhaigou earthquake led to the collapse of the mountains and formed lots of landslides in Jiuzhaigou scenic spot and surrounding roads which caused road blockage and serious ecological damage. Due to the urgency of the rescue, the authors carried unmanned aerial vehicle (UAV) and entered the disaster area as early as August 9 to obtain the aerial images near the epicenter. On the basis of summarizing the earthquake landslides characteristics in aerial images, by using the object-oriented analysis method, landslides image objects were obtained by multi-scale segmentation, and the feature rule set of each level was automatically built by SEaTH (Separability and Thresholds) algorithm to realize the rapid landslide extraction. Compared with visual interpretation, object-oriented automatic landslides extraction method achieved an accuracy of 94.3 %. The spatial distribution of the earthquake landslide had a significant positive correlation with slope and relief and had a negative correlation with the roughness, but no obvious correlation with the aspect. The relationship between the landslide and the aspect was not found and the probable reason may be that the distance between the study area and the seismogenic fault was too far away. This work provided technical support for the earthquake field emergency, earthquake landslide prediction and disaster loss assessment.

  7. RAPID EXTRACTION OF LANDSLIDE AND SPATIAL DISTRIBUTION ANALYSIS AFTER JIUZHAIGOU Ms7.0 EARTHQUAKE BASED ON UAV IMAGES

    Directory of Open Access Journals (Sweden)

    Q. S. Jiao

    2018-04-01

    Full Text Available Jiuzhaigou earthquake led to the collapse of the mountains and formed lots of landslides in Jiuzhaigou scenic spot and surrounding roads which caused road blockage and serious ecological damage. Due to the urgency of the rescue, the authors carried unmanned aerial vehicle (UAV and entered the disaster area as early as August 9 to obtain the aerial images near the epicenter. On the basis of summarizing the earthquake landslides characteristics in aerial images, by using the object-oriented analysis method, landslides image objects were obtained by multi-scale segmentation, and the feature rule set of each level was automatically built by SEaTH (Separability and Thresholds algorithm to realize the rapid landslide extraction. Compared with visual interpretation, object-oriented automatic landslides extraction method achieved an accuracy of 94.3 %. The spatial distribution of the earthquake landslide had a significant positive correlation with slope and relief and had a negative correlation with the roughness, but no obvious correlation with the aspect. The relationship between the landslide and the aspect was not found and the probable reason may be that the distance between the study area and the seismogenic fault was too far away. This work provided technical support for the earthquake field emergency, earthquake landslide prediction and disaster loss assessment.

  8. 3-D model-based vehicle tracking.

    Science.gov (United States)

    Lou, Jianguang; Tan, Tieniu; Hu, Weiming; Yang, Hao; Maybank, Steven J

    2005-10-01

    This paper aims at tracking vehicles from monocular intensity image sequences and presents an efficient and robust approach to three-dimensional (3-D) model-based vehicle tracking. Under the weak perspective assumption and the ground-plane constraint, the movements of model projection in the two-dimensional image plane can be decomposed into two motions: translation and rotation. They are the results of the corresponding movements of 3-D translation on the ground plane (GP) and rotation around the normal of the GP, which can be determined separately. A new metric based on point-to-line segment distance is proposed to evaluate the similarity between an image region and an instantiation of a 3-D vehicle model under a given pose. Based on this, we provide an efficient pose refinement method to refine the vehicle's pose parameters. An improved EKF is also proposed to track and to predict vehicle motion with a precise kinematics model. Experimental results with both indoor and outdoor data show that the algorithm obtains desirable performance even under severe occlusion and clutter.

  9. The prospects for Unmanned Aerial Vehicles

    OpenAIRE

    Brookes, Andrew

    2000-01-01

    In this study Andrew Brookes argues that Unmanned Aerial Vehicles (UAV) is the military fashion of the moment. Since the end of the 1990s many nations have added UAVs to their military inventories, and in 1999 half a dozen nations used UAVs over Kosovo. In the light of operational experience in Kosovo, Brookes re-evaluates the potential of this vehicle, and examines the roles, capabilities and future challenges of UAV.

  10. Extended observer based on adaptive second order sliding mode control for a fixed wing UAV.

    Science.gov (United States)

    Castañeda, Herman; Salas-Peña, Oscar S; León-Morales, Jesús de

    2017-01-01

    This paper addresses the design of attitude and airspeed controllers for a fixed wing unmanned aerial vehicle. An adaptive second order sliding mode control is proposed for improving performance under different operating conditions and is robust in presence of external disturbances. Moreover, this control does not require the knowledge of disturbance bounds and avoids overestimation of the control gains. Furthermore, in order to implement this controller, an extended observer is designed to estimate unmeasurable states as well as external disturbances. Additionally, sufficient conditions are given to guarantee the closed-loop stability of the observer based control. Finally, using a full 6 degree of freedom model, simulation results are obtained where the performance of the proposed method is compared against active disturbance rejection based on sliding mode control. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  11. UAV-BASED PHOTOGRAMMETRIC POINT CLOUDS – TREE STEM MAPPING IN OPEN STANDS IN COMPARISON TO TERRESTRIAL LASER SCANNER POINT CLOUDS

    Directory of Open Access Journals (Sweden)

    A. Fritz

    2013-08-01

    Full Text Available In both ecology and forestry, there is a high demand for structural information of forest stands. Forest structures, due to their heterogeneity and density, are often difficult to assess. Hence, a variety of technologies are being applied to account for this "difficult to come by" information. Common techniques are aerial images or ground- and airborne-Lidar. In the present study we evaluate the potential use of unmanned aerial vehicles (UAVs as a platform for tree stem detection in open stands. A flight campaign over a test site near Freiburg, Germany covering a target area of 120 × 75 [m2] was conducted. The dominant tree species of the site is oak (quercus robur with almost no understory growth. Over 1000 images with a tilt angle of 45° were shot. The flight pattern applied consisted of two antipodal staggered flight routes at a height of 55 [m] above the ground. We used a Panasonic G3 consumer camera equipped with a 14–42 [mm] standard lens and a 16.6 megapixel sensor. The data collection took place in leaf-off state in April 2013. The area was prepared with artificial ground control points for transformation of the structure-from-motion (SFM point cloud into real world coordinates. After processing, the results were compared with a terrestrial laser scanner (TLS point cloud of the same area. In the 0.9 [ha] test area, 102 individual trees above 7 [cm] diameter at breast height were located on in the TLS-cloud. We chose the software CMVS/PMVS-2 since its algorithms are developed with focus on dense reconstruction. The processing chain for the UAV-acquired images consists of six steps: a. cleaning the data: removing of blurry, under- or over exposed and off-site images; b. applying the SIFT operator [Lowe, 2004]; c. image matching; d. bundle adjustment; e. clustering; and f. dense reconstruction. In total, 73 stems were considered as reconstructed and located within one meter of the reference trees. In general stems were far less accurate

  12. ANALYSIS OF COMBINED UAV-BASED RGB AND THERMAL REMOTE SENSING DATA: A NEW APPROACH TO CROWD MONITORING

    Directory of Open Access Journals (Sweden)

    S. Schulte

    2017-08-01

    Full Text Available Collecting vast amount of data does not solely help to fulfil information needs related to crowd monitoring, it is rather important to collect data that is suitable to meet specific information requirements. In order to address this issue, a prototype is developed to facilitate the combination of UAV-based RGB and thermal remote sensing datasets. In an experimental approach, image sensors were mounted on a remotely piloted aircraft and captured two video datasets over a crowd. A group of volunteers performed diverse movements that depict real world scenarios. The prototype is deriving the movement on the ground and is programmed in MATLAB. This novel detection approach using combined data is afterwards evaluated against detection algorithms that only use a single data source. Our tests show that the combination of RGB and thermal remote sensing data is beneficial for the field of crowd monitoring regarding the detection of crowd movement.

  13. Vision-Based Detection and Distance Estimation of Micro Unmanned Aerial Vehicles

    Directory of Open Access Journals (Sweden)

    Fatih Gökçe

    2015-09-01

    Full Text Available Detection and distance estimation of micro unmanned aerial vehicles (mUAVs is crucial for (i the detection of intruder mUAVs in protected environments; (ii sense and avoid purposes on mUAVs or on other aerial vehicles and (iii multi-mUAV control scenarios, such as environmental monitoring, surveillance and exploration. In this article, we evaluate vision algorithms as alternatives for detection and distance estimation of mUAVs, since other sensing modalities entail certain limitations on the environment or on the distance. For this purpose, we test Haar-like features, histogram of gradients (HOG and local binary patterns (LBP using cascades of boosted classifiers. Cascaded boosted classifiers allow fast processing by performing detection tests at multiple stages, where only candidates passing earlier simple stages are processed at the preceding more complex stages. We also integrate a distance estimation method with our system utilizing geometric cues with support vector regressors. We evaluated each method on indoor and outdoor videos that are collected in a systematic way and also on videos having motion blur. Our experiments show that, using boosted cascaded classifiers with LBP, near real-time detection and distance estimation of mUAVs are possible in about 60 ms indoors (1032 × 778 resolution and 150 ms outdoors (1280 × 720 resolution per frame, with a detection rate of 0.96 F-score. However, the cascaded classifiers using Haar-like features lead to better distance estimation since they can position the bounding boxes on mUAVs more accurately. On the other hand, our time analysis yields that the cascaded classifiers using HOG train and run faster than the other algorithms.

  14. Hybrid Power Management-Based Vehicle Architecture

    Science.gov (United States)

    Eichenberg, Dennis J.

    2011-01-01

    Hybrid Power Management (HPM) is the integration of diverse, state-of-the-art power devices in an optimal configuration for space and terrestrial applications (s ee figure). The appropriate application and control of the various power devices significantly improves overall system performance and efficiency. The basic vehicle architecture consists of a primary power source, and possibly other power sources, that provides all power to a common energy storage system that is used to power the drive motors and vehicle accessory systems. This architecture also provides power as an emergency power system. Each component is independent, permitting it to be optimized for its intended purpose. The key element of HPM is the energy storage system. All generated power is sent to the energy storage system, and all loads derive their power from that system. This can significantly reduce the power requirement of the primary power source, while increasing the vehicle reliability. Ultracapacitors are ideal for an HPM-based energy storage system due to their exceptionally long cycle life, high reliability, high efficiency, high power density, and excellent low-temperature performance. Multiple power sources and multiple loads are easily incorporated into an HPM-based vehicle. A gas turbine is a good primary power source because of its high efficiency, high power density, long life, high reliability, and ability to operate on a wide range of fuels. An HPM controller maintains optimal control over each vehicle component. This flexible operating system can be applied to all vehicles to considerably improve vehicle efficiency, reliability, safety, security, and performance. The HPM-based vehicle architecture has many advantages over conventional vehicle architectures. Ultracapacitors have a much longer cycle life than batteries, which greatly improves system reliability, reduces life-of-system costs, and reduces environmental impact as ultracapacitors will probably never need to be

  15. AirSTAR: A UAV Platform for Flight Dynamics and Control System Testing

    Science.gov (United States)

    Jordan, Thomas L.; Foster, John V.; Bailey, Roger M.; Belcastro, Christine M.

    2006-01-01

    As part of the NASA Aviation Safety Program at Langley Research Center, a dynamically scaled unmanned aerial vehicle (UAV) and associated ground based control system are being developed to investigate dynamics modeling and control of large transport vehicles in upset conditions. The UAV is a 5.5% (seven foot wingspan), twin turbine, generic transport aircraft with a sophisticated instrumentation and telemetry package. A ground based, real-time control system is located inside an operations vehicle for the research pilot and associated support personnel. The telemetry system supports over 70 channels of data plus video for the downlink and 30 channels for the control uplink. Data rates are in excess of 200 Hz. Dynamic scaling of the UAV, which includes dimensional, weight, inertial, actuation, and control system scaling, is required so that the sub-scale vehicle will realistically simulate the flight characteristics of the full-scale aircraft. This testbed will be utilized to validate modeling methods, flight dynamics characteristics, and control system designs for large transport aircraft, with the end goal being the development of technologies to reduce the fatal accident rate due to loss-of-control.

  16. Bio-inspired UAV routing, source localization, and acoustic signature classification for persistent surveillance

    Science.gov (United States)

    Burman, Jerry; Hespanha, Joao; Madhow, Upamanyu; Pham, Tien

    2011-06-01

    A team consisting of Teledyne Scientific Company, the University of California at Santa Barbara and the Army Research Laboratory* is developing technologies in support of automated data exfiltration from heterogeneous battlefield sensor networks to enhance situational awareness for dismounts and command echelons. Unmanned aerial vehicles (UAV) provide an effective means to autonomously collect data from a sparse network of unattended ground sensors (UGSs) that cannot communicate with each other. UAVs are used to reduce the system reaction time by generating autonomous collection routes that are data-driven. Bio-inspired techniques for search provide a novel strategy to detect, capture and fuse data. A fast and accurate method has been developed to localize an event by fusing data from a sparse number of UGSs. This technique uses a bio-inspired algorithm based on chemotaxis or the motion of bacteria seeking nutrients in their environment. A unique acoustic event classification algorithm was also developed based on using swarm optimization. Additional studies addressed the problem of routing multiple UAVs, optimally placing sensors in the field and locating the source of gunfire at helicopters. A field test was conducted in November of 2009 at Camp Roberts, CA. The field test results showed that a system controlled by bio-inspired software algorithms can autonomously detect and locate the source of an acoustic event with very high accuracy and visually verify the event. In nine independent test runs of a UAV, the system autonomously located the position of an explosion nine times with an average accuracy of 3 meters. The time required to perform source localization using the UAV was on the order of a few minutes based on UAV flight times. In June 2011, additional field tests of the system will be performed and will include multiple acoustic events, optimal sensor placement based on acoustic phenomenology and the use of the International Technology Alliance (ITA

  17. A system of UAV application in indoor environment

    DEFF Research Database (Denmark)

    Khosiawan, Yohanes; Nielsen, Izabela Ewa

    2016-01-01

    In recent years, there has been an increased demand in the use of multiple unmanned aerial vehicles (UAVs) in indoor environments such as material handling task in a manufacturing environment and plant/environment monitoring task in a greenhouse. However, there is a lack of work reported on this ......In recent years, there has been an increased demand in the use of multiple unmanned aerial vehicles (UAVs) in indoor environments such as material handling task in a manufacturing environment and plant/environment monitoring task in a greenhouse. However, there is a lack of work reported...... on this topic. This paper presents a detailed study on several UAV systems and UAV scheduling systems. It is followed by a proposed system of UAV application in indoor environment, which comprises components of UAV system addressed in detail; focused on scheduler as the heart of operations. Consequently, system...... architecture of UAV scheduling system is presented and the framework of scheduler component is included. Scheduler component works in a phased manner to provide a systematic abstraction and achieve an efficient computation time. This study serves as a reference guide for UAV application in indoor environment....

  18. Urban forest topographical mapping using UAV LIDAR

    Science.gov (United States)

    Putut Ash Shidiq, Iqbal; Wibowo, Adi; Kusratmoko, Eko; Indratmoko, Satria; Ardhianto, Ronni; Prasetyo Nugroho, Budi

    2017-12-01

    Topographical data is highly needed by many parties, such as government institution, mining companies and agricultural sectors. It is not just about the precision, the acquisition time and data processing are also carefully considered. In relation with forest management, a high accuracy topographic map is necessary for planning, close monitoring and evaluating forest changes. One of the solution to quickly and precisely mapped topography is using remote sensing system. In this study, we test high-resolution data using Light Detection and Ranging (LiDAR) collected from unmanned aerial vehicles (UAV) to map topography and differentiate vegetation classes based on height in urban forest area of University of Indonesia (UI). The semi-automatic and manual classifications were applied to divide point clouds into two main classes, namely ground and vegetation. There were 15,806,380 point clouds obtained during the post-process, in which 2.39% of it were detected as ground.

  19. A method of intentional movement estimation of oblique small-UAV videos stabilized based on homography model

    Science.gov (United States)

    Guo, Shiyi; Mai, Ying; Zhao, Hongying; Gao, Pengqi

    2013-05-01

    The airborne video streams of small-UAVs are commonly plagued with distractive jittery and shaking motions, disorienting rotations, noisy and distorted images and other unwanted movements. These problems collectively make it very difficult for observers to obtain useful information from the video. Due to the small payload of small-UAVs, it is a priority to improve the image quality by means of electronic image stabilization. But when small-UAV makes a turn, affected by the flight characteristics of it, the video is easy to become oblique. This brings a lot of difficulties to electronic image stabilization technology. Homography model performed well in the oblique image motion estimation, while bringing great challenges to intentional motion estimation. Therefore, in this paper, we focus on solve the problem of the video stabilized when small-UAVs banking and turning. We attend to the small-UAVs fly along with an arc of a fixed turning radius. For this reason, after a series of experimental analysis on the flight characteristics and the path how small-UAVs turned, we presented a new method to estimate the intentional motion in which the path of the frame center was used to fit the video moving track. Meanwhile, the image sequences dynamic mosaic was done to make up for the limited field of view. At last, the proposed algorithm was carried out and validated by actual airborne videos. The results show that the proposed method is effective to stabilize the oblique video of small-UAVs.

  20. Development of an innovative uav-mountd screening tool for landfill gas emisiions

    DEFF Research Database (Denmark)

    Fjelsted, L.; Thomasen, T. B.; Valbjørn, I. L.

    2015-01-01

    Identification of landfill gas emission hot spots are potentially a very time consuming process, and the use of an Unmanned Aerial Vehicle (UAV) based screening tool could be an effective investigation strategy. In this study, the potential use of a long-wave thermal infrared camera was investiga......Identification of landfill gas emission hot spots are potentially a very time consuming process, and the use of an Unmanned Aerial Vehicle (UAV) based screening tool could be an effective investigation strategy. In this study, the potential use of a long-wave thermal infrared camera...... was investigated. The correlation between surface soil temperatures and landfill gas emissions was examined in a field study conducted at Hedeland Landfill near Roskilde, Denmark. The surface temperatures were both measured with a soil thermometer and a long-wave infrared camera and compared to detected methane...

  1. Light vehicle crash avoidance needs and countermeasure profiles for safety applications based on vehicle-to-vehicle communications

    Science.gov (United States)

    2013-04-30

    This report discusses light-vehicle crash countermeasure profiles and functions for five target pre-crash scenario groups based on vehicle-to-vehicle (V2V) communications. Target pre-crash scenario groups include rear-end, lane change, opposite direc...

  2. Aerosol and Cloud Properties during the Cloud Cheju ABC Plume -Asian Monsoon Experiment (CAPMEX) 2008: Linking between Ground-based and UAV Measurements

    Science.gov (United States)

    Kim, S.; Yoon, S.; Venkata Ramana, M.; Ramanathan, V.; Nguyen, H.; Park, S.; Kim, M.

    2009-12-01

    Cheju Atmospheric Brown Cloud (ABC) Plume-Monsoon Experiment (CAPMEX), comprehsensive ground-based measurements and a series of data-gathering flights by specially equipped autonomous unmanned aerial vehicles (AUAVs) for aerosol and cloud, had conducted at Jeju (formerly, Cheju), South Korea during August-September 2008, to improve our understanding of how the reduction of anthropogenic emissions in China (so-called “great shutdown” ) during and after the Summer Beijing Olympic Games 2008 effcts on the air quliaty and radiation budgets and how atmospheric brown clouds (ABCs) influences solar radiation budget off Asian continent. Large numbers of in-situ and remote sensing instruments at the Gosan ABC observatory and miniaturized instruments on the aircraft measure a range of properties such as the quantity of soot, size-segregated aerosol particle numbers, total particle numbers, size-segregated cloud droplet numbers (only AUAV), aerosol scattering properties (only ground), aerosol vertical distribution, column-integrated aerosol properties, and meteorological variables. By integrating ground-level and high-elevation AUAV measurements with NASA-satellite observations (e.g., MODIS, CALIPSO), we investigate the long range transport of aerosols, the impact of ABCs on clouds, and the role of biogenic and anthropogenic aerosols on cloud condensation nuclei (CCN). In this talk, we will present the results from CAPMEX focusing on: (1) the characteristics of aerosol optical, physical and chemical properties at Gosan observatory, (2) aerosol solar heating calculated from the ground-based micro-pulse lidar and AERONET sun/sky radiometer synergy, and comparison with direct measurements from UAV, and (3) aerosol-cloud interactions in conjunction with measurements by satellites and Gosan observatory.

  3. Vision-based vehicle detection and tracking algorithm design

    Science.gov (United States)

    Hwang, Junyeon; Huh, Kunsoo; Lee, Donghwi

    2009-12-01

    The vision-based vehicle detection in front of an ego-vehicle is regarded as promising for driver assistance as well as for autonomous vehicle guidance. The feasibility of vehicle detection in a passenger car requires accurate and robust sensing performance. A multivehicle detection system based on stereo vision has been developed for better accuracy and robustness. This system utilizes morphological filter, feature detector, template matching, and epipolar constraint techniques in order to detect the corresponding pairs of vehicles. After the initial detection, the system executes the tracking algorithm for the vehicles. The proposed system can detect front vehicles such as the leading vehicle and side-lane vehicles. The position parameters of the vehicles located in front are obtained based on the detection information. The proposed vehicle detection system is implemented on a passenger car, and its performance is verified experimentally.

  4. U.S. Unmanned Aerial Vehicles (UAVs) and Network Centric Warfare (NCW): Impacts on Combat Aviation Tactics from Gulf War I Through 2007 Iraq

    Science.gov (United States)

    2008-03-01

    early warning AIM Air-intercept missile AJCN Adaptive, joint, C4ISR node AOR Area of responsibility ARM Anti-radiation missile ATARS Advanced...and economic considerations are offered, including relevant technological advancements. UAV impacts on these four conflicts are examined in the next...Tactical Airborne Reconnaissance System ( ATARS ) on F-16 and F/A-18 aircraft, and satellites. Manned platforms were adapted to multiple mission scenarios

  5. Automatic UAV Image Geo-Registration by Matching UAV Images to Georeferenced Image Data

    Directory of Open Access Journals (Sweden)

    Xiangyu Zhuo

    2017-04-01

    Full Text Available Recent years have witnessed the fast development of UAVs (unmanned aerial vehicles. As an alternative to traditional image acquisition methods, UAVs bridge the gap between terrestrial and airborne photogrammetry and enable flexible acquisition of high resolution images. However, the georeferencing accuracy of UAVs is still limited by the low-performance on-board GNSS and INS. This paper investigates automatic geo-registration of an individual UAV image or UAV image blocks by matching the UAV image(s with a previously taken georeferenced image, such as an individual aerial or satellite image with a height map attached or an aerial orthophoto with a DSM (digital surface model attached. As the biggest challenge for matching UAV and aerial images is in the large differences in scale and rotation, we propose a novel feature matching method for nadir or slightly tilted images. The method is comprised of a dense feature detection scheme, a one-to-many matching strategy and a global geometric verification scheme. The proposed method is able to find thousands of valid matches in cases where SIFT and ASIFT fail. Those matches can be used to geo-register the whole UAV image block towards the reference image data. When the reference images offer high georeferencing accuracy, the UAV images can also be geolocalized in a global coordinate system. A series of experiments involving different scenarios was conducted to validate the proposed method. The results demonstrate that our approach achieves not only decimeter-level registration accuracy, but also comparable global accuracy as the reference images.

  6. Spectral broadening of acoustic tones generated by unmanned aerial vehicles in a turbulent atmosphere

    DEFF Research Database (Denmark)

    Ostashev, Vladimir E.; Wilson, D. K.; Finn, Anthony

    2016-01-01

    The acoustic spectrum emitted by unmanned aerial vehicles (UAVs) and other aircraft can be distorted by propagation through atmospheric turbulence. Since most UAVs are propeller-based, they generate a series of acoustic tones and harmonics. In this paper, spectral broadening of these tones due......, spectral broadening is calculated and analyzed for typical meteorological regimes of the atmospheric boundary layer and different flight trajectories of UAVs. Experimental results are presented and compared with theoretical predictions. Spectral broadening might also provide a means for remotely sensing...

  7. Time Series UAV Image-Based Point Clouds for Landslide Progression Evaluation Applications.

    Science.gov (United States)

    Al-Rawabdeh, Abdulla; Moussa, Adel; Foroutan, Marzieh; El-Sheimy, Naser; Habib, Ayman

    2017-10-18

    Landslides are major and constantly changing threats to urban landscapes and infrastructure. It is essential to detect and capture landslide changes regularly. Traditional methods for monitoring landslides are time-consuming, costly, dangerous, and the quality and quantity of the data is sometimes unable to meet the necessary requirements of geotechnical projects. This motivates the development of more automatic and efficient remote sensing approaches for landslide progression evaluation. Automatic change detection involving low-altitude unmanned aerial vehicle image-based point clouds, although proven, is relatively unexplored, and little research has been done in terms of accounting for volumetric changes. In this study, a methodology for automatically deriving change displacement rates, in a horizontal direction based on comparisons between extracted landslide scarps from multiple time periods, has been developed. Compared with the iterative closest projected point (ICPP) registration method, the developed method takes full advantage of automated geometric measuring, leading to fast processing. The proposed approach easily processes a large number of images from different epochs and enables the creation of registered image-based point clouds without the use of extensive ground control point information or further processing such as interpretation and image correlation. The produced results are promising for use in the field of landslide research.

  8. Optimizing Multiple Kernel Learning for the Classification of UAV Data

    Directory of Open Access Journals (Sweden)

    Caroline M. Gevaert

    2016-12-01

    Full Text Available Unmanned Aerial Vehicles (UAVs are capable of providing high-quality orthoimagery and 3D information in the form of point clouds at a relatively low cost. Their increasing popularity stresses the necessity of understanding which algorithms are especially suited for processing the data obtained from UAVs. The features that are extracted from the point cloud and imagery have different statistical characteristics and can be considered as heterogeneous, which motivates the use of Multiple Kernel Learning (MKL for classification problems. In this paper, we illustrate the utility of applying MKL for the classification of heterogeneous features obtained from UAV data through a case study of an informal settlement in Kigali, Rwanda. Results indicate that MKL can achieve a classification accuracy of 90.6%, a 5.2% increase over a standard single-kernel Support Vector Machine (SVM. A comparison of seven MKL methods indicates that linearly-weighted kernel combinations based on simple heuristics are competitive with respect to computationally-complex, non-linear kernel combination methods. We further underline the importance of utilizing appropriate feature grouping strategies for MKL, which has not been directly addressed in the literature, and we propose a novel, automated feature grouping method that achieves a high classification accuracy for various MKL methods.

  9. Concrete Crack Identification Using a UAV Incorporating Hybrid Image Processing.

    Science.gov (United States)

    Kim, Hyunjun; Lee, Junhwa; Ahn, Eunjong; Cho, Soojin; Shin, Myoungsu; Sim, Sung-Han

    2017-09-07

    Crack assessment is an essential process in the maintenance of concrete structures. In general, concrete cracks are inspected by manual visual observation of the surface, which is intrinsically subjective as it depends on the experience of inspectors. Further, it is time-consuming, expensive, and often unsafe when inaccessible structural members are to be assessed. Unmanned aerial vehicle (UAV) technologies combined with digital image processing have recently been applied to crack assessment to overcome the drawbacks of manual visual inspection. However, identification of crack information in terms of width and length has not been fully explored in the UAV-based applications, because of the absence of distance measurement and tailored image processing. This paper presents a crack identification strategy that combines hybrid image processing with UAV technology. Equipped with a camera, an ultrasonic displacement sensor, and a WiFi module, the system provides the image of cracks and the associated working distance from a target structure on demand. The obtained information is subsequently processed by hybrid image binarization to estimate the crack width accurately while minimizing the loss of the crack length information. The proposed system has shown to successfully measure cracks thicker than 0.1 mm with the maximum length estimation error of 7.3%.

  10. PRECISE POSITIONING OF UAVS – DEALING WITH CHALLENGING RTK-GPS MEASUREMENT CONDITIONS DURING AUTOMATED UAV FLIGHTS

    Directory of Open Access Journals (Sweden)

    F. Zimmermann

    2017-08-01

    Full Text Available For some years now, UAVs (unmanned aerial vehicles are commonly used for different mobile mapping applications, such as in the fields of surveying, mining or archeology. To improve the efficiency of these applications an automation of the flight as well as the processing of the collected data is currently aimed at. One precondition for an automated mapping with UAVs is that the georeferencing is performed directly with cm-accuracies or better. Usually, a cm-accurate direct positioning of UAVs is based on an onboard multi-sensor system, which consists of an RTK-capable (real-time kinematic GPS (global positioning system receiver and additional sensors (e.g. inertial sensors. In this case, the absolute positioning accuracy essentially depends on the local GPS measurement conditions. Especially during mobile mapping applications in urban areas, these conditions can be very challenging, due to a satellite shadowing, non-line-of sight receptions, signal diffraction or multipath effects. In this paper, two straightforward and easy to implement strategies will be described and analyzed, which improve the direct positioning accuracies for UAV-based mapping and surveying applications under challenging GPS measurement conditions. Based on a 3D model of the surrounding buildings and vegetation in the area of interest, a GPS geometry map is determined, which can be integrated in the flight planning process, to avoid GPS challenging environments as far as possible. If these challenging environments cannot be avoided, the GPS positioning solution is improved by using obstruction adaptive elevation masks, to mitigate systematic GPS errors in the RTK-GPS positioning. Simulations and results of field tests demonstrate the profit of both strategies.

  11. A Novel Online Data-Driven Algorithm for Detecting UAV Navigation Sensor Faults

    OpenAIRE

    Rui Sun; Qi Cheng; Guanyu Wang; Washington Yotto Ochieng

    2017-01-01

    The use of Unmanned Aerial Vehicles (UAVs) has increased significantly in recent years. On-board integrated navigation sensors are a key component of UAVs’ flight control systems and are essential for flight safety. In order to ensure flight safety, timely and effective navigation sensor fault detection capability is required. In this paper, a novel data-driven Adaptive Neuron Fuzzy Inference System (ANFIS)-based approach is presented for the detection of on-board navigation sensor faults in ...

  12. Detection of Nuclear Sources by UAV Teleoperation Using a Visuo-Haptic Augmented Reality Interface

    OpenAIRE

    Jacopo Aleotti; Giorgio Micconi; Stefano Caselli; Giacomo Benassi; Nicola Zambelli; Manuele Bettelli; Andrea Zappettini

    2017-01-01

    A visuo-haptic augmented reality (VHAR) interface is presented enabling an operator to teleoperate an unmanned aerial vehicle (UAV) equipped with a custom CdZnTe-based spectroscopic gamma-ray detector in outdoor environments. The task is to localize nuclear radiation sources, whose location is unknown to the user, without the close exposure of the operator. The developed detector also enables identification of the localized nuclear sources. The aim of the VHAR interface is to increase the sit...

  13. Fluxgate vector magnetometers: A multisensor device for ground, UAV, and airborne magnetic surveys

    OpenAIRE

    Gavazzi , Bruno; Le Maire , Pauline; Munschy , Marc; Dechamp , Aline

    2016-01-01

    International audience; Fluxgate magnetometers are quite uncommon in geophysics. Recent advances in calibration of the devices and their magnetic compensation ability led Institut de Physique du Globe de Stras-bourg to develop instruments for magnetic measurements at different scales for a wide range of applications — from submetric measurements on the ground to aircraft-conducted acquisition by unmanned aerial vehicles (UAVs). A case study on the aerial military base BA112 shows the usefulne...

  14. USAGE OF UNMANNED AERIAL VEHICLES IN GENERAL AVIATION: CURRENT SITUATION AND PROSPECTS

    Directory of Open Access Journals (Sweden)

    2016-01-01

    Full Text Available The article aims at analyzing the current and future trends in usage of Unmanned Aerial Vehicles (UAV in gen- eral aviation (branches of economy. The main goal of the analysis is to determine the branches of economy, in which the usage of UAVs would be the most beneficial in the near- to mid-term future. The main requirements and restrictions of usage of the aircraft in general aviation were used as a basis for determining the types of operations, in which the usage of UAVs will be the most rational and effective. The effectiveness evaluation was based on the developed method, involving evaluation of the following factors such as: advantages of usage of manned aircraft, advantages of usage of unmanned air- craft, problems associated with the usage of manned aircraft, problems associated with the usage of unmanned aircraft. After evaluation of the mentioned aspects above the safety, operational productivity and ecological indicators were evaluat- ed. These qualitative assessments allowed identifying the branches of economy, where the usage of UAVs could potentially be the most advantageous. The article also discusses the possible strategies of UAVs development for general aviation. The so-called “mixed” strategy of UAV development is identified as the best in the current situation. This strategy combines the conversion of the existing military UAVs with the purpose of fitting them in to civilian use with the parallel development of brand new UAVs, which would be designed for operation in branches of economy right from the beginning (from scratch.

  15. Characterization Test Procedures for Intersection Collision Avoidance Systems Based on Vehicle-to-Vehicle Communications

    Science.gov (United States)

    2015-12-01

    Characterization test procedures have been developed to quantify the performance of intersection collision avoidance (ICA) systems based on vehicle-to-vehicle communications. These systems warn the driver of an imminent crossing-path collision at a r...

  16. Integrated vehicle-based safety systems light-vehicle field operational test key findings report.

    Science.gov (United States)

    2011-01-01

    "This document presents key findings from the light-vehicle field operational test conducted as part of the Integrated Vehicle-Based Safety Systems program. These findings are the result of analyses performed by the University of Michigan Transportat...

  17. Integrated vehicle-based safety systems light-vehicle field operational test, methodology and results report.

    Science.gov (United States)

    2010-12-01

    "This document presents the methodology and results from the light-vehicle field operational test conducted as part of the Integrated Vehicle-Based Safety Systems program. These findings are the result of analyses performed by the University of Michi...

  18. Integrated vehicle-based safety systems (IVBSS) : light vehicle platform field operational test data analysis plan.

    Science.gov (United States)

    2009-12-22

    This document presents the University of Michigan Transportation Research Institutes plan to : perform analysis of data collected from the light vehicle platform field operational test of the : Integrated Vehicle-Based Safety Systems (IVBSS) progr...

  19. Development of an Experimental Platform for Testing Autonomous UAV Guidance and Control Algorithms

    National Research Council Canada - National Science Library

    Rufa, Justin R

    2007-01-01

    With the United States? push towards using unmanned aerial vehicles (UAVs) for more military missions, wide area search theory is being researched to determine the viability of multiple vehicle autonomous searches over the battle area...

  20. Gaze-Based Controlling a Vehicle

    DEFF Research Database (Denmark)

    Mardanbeigi, Diako; Witzner Hansen, Dan

    ) as an example of a complex gaze-based task in environment. This paper discusses the possibilities and limitations of how gaze interaction can be performed for controlling vehicles not only using a remote gaze tracker but also in general challenging situations where the user and robot are mobile...... modality if gaze trackers are embedded into the head- mounted devices. The domain of gaze-based interactive applications increases dramatically as interaction is no longer constrained to 2D displays. This paper proposes a general framework for gaze-based controlling a non- stationary robot (vehicle...... and the movements may be governed by several degrees of freedom (e.g. flying). A case study is also introduced where the mobile gaze tracker is used for controlling a Roomba vacuum cleaner....

  1. Transmission Tower Environment Monitoring Using UAV

    International Nuclear Information System (INIS)

    Redzuwan, Redia Mohd; Din, Norashidah Md; Baharuddin, Mohd Zafri; Mustafa, Intan Shafinaz; Omar, Rohayu Che'

    2013-01-01

    Power utility engineers used to conduct ground survey to collect topographic data. Therefore, they can get detailed and accurate information, but these techniques take a lot of labors and expenses, and spending times for the surveying. An attractive solution to the ground survey is using images taken using Unmanned Aerial Vehicle (UAV). Images captured from UAV can be collected quickly and efficiently over the same area covered in the land survey, in a fraction of the time. The purpose of this research is to mosaic the large numbers of spectral images together into a region wide panoramic image which allows experts to analyze the data for transmission tower monitoring purposes.

  2. Common Operating Picture: UAV Security Study

    Science.gov (United States)

    2004-01-01

    This initial communication security study is a top-level assessment of basic security issues related to the operation of Unmanned Aerial Vehicles (UAVs) in the National Airspace System (NAS). Security considerations will include information relating to the use of International Civil Aviation Organization (ICAO) Aeronautical Telecommunications Network (ATN) protocols and applications identifying their maturity, as well as the use of IPV4 and a version of mobile IPV6. The purpose of this assessment is to provide an initial analysis of the security implications of introducing UAVs into the NAS.

  3. Magnetic profiling of the San Andreas Fault using a dual magnetometer UAV aerial survey system.

    Science.gov (United States)

    Abbate, J. A.; Angelopoulos, V.; Masongsong, E. V.; Yang, J.; Medina, H. R.; Moon, S.; Davis, P. M.

    2017-12-01

    Aeromagnetic survey methods using planes are more time-effective than hand-held methods, but can be far more expensive per unit area unless large areas are covered. The availability of low cost UAVs and low cost, lightweight fluxgate magnetometers (FGMs) allows, with proper offset determination and stray fields correction, for low-cost magnetic surveys. Towards that end, we have developed a custom multicopter UAV for magnetic mapping using a dual 3-axis fluxgate magnetometer system: the GEOphysical Drone Enhanced Survey Instrument (GEODESI). A high precision sensor measures the UAV's position and attitude (roll, pitch, and yaw) and is recorded using a custom Arduino data processing system. The two FGMs (in-board and out-board) are placed on two ends of a vertical 1m boom attached to the base of the UAV. The in-board FGM is most sensitive to stray fields from the UAV and its signal is used, after scaling, to clean the signal of the out-board FGM from the vehicle noise. The FGMs record three orthogonal components of the magnetic field in the UAV body coordinates which are then transformed into a north-east-down coordinate system using a rotation matrix determined from the roll-pitch-yaw attitude data. This ensures knowledge of the direction of all three field components enabling us to perform inverse modeling of magnetic anomalies with greater accuracy than total or vertical field measurements used in the past. Field tests were performed at Dragon's Back Pressure Ridge in the Carrizo Plain of California, where there is a known crossing of the San Andreas Fault. Our data and models were compared to previously acquired LiDAR and hand-held magnetometer measurements. Further tests will be carried out to solidify our results and streamline our processing for educational use in the classroom and student field training.

  4. Mini-UAV based sensory system for measuring environmental variables in greenhouses.

    Science.gov (United States)

    Roldán, Juan Jesús; Joossen, Guillaume; Sanz, David; del Cerro, Jaime; Barrientos, Antonio

    2015-02-02

    This paper describes the design, construction and validation of a mobile sensory platform for greenhouse monitoring. The complete system consists of a sensory system on board a small quadrotor (i.e., a four rotor mini-UAV). The goals of this system include taking measures of temperature, humidity, luminosity and CO2 concentration and plotting maps of these variables. These features could potentially allow for climate control, crop monitoring or failure detection (e.g., a break in a plastic cover). The sensors have been selected by considering the climate and plant growth models and the requirements for their integration onboard the quadrotor. The sensors layout and placement have been determined through a study of quadrotor aerodynamics and the influence of the airflows from its rotors. All components of the system have been developed, integrated and tested through a set of field experiments in a real greenhouse. The primary contributions of this paper are the validation of the quadrotor as a platform for measuring environmental variables and the determination of the optimal location of sensors on a quadrotor.

  5. Mini-UAV Based Sensory System for Measuring Environmental Variables in Greenhouses

    Directory of Open Access Journals (Sweden)

    Juan Jesús Roldán

    2015-02-01

    Full Text Available This paper describes the design, construction and validation of a mobile sensory platform for greenhouse monitoring. The complete system consists of a sensory system on board a small quadrotor (i.e., a four rotor mini-UAV. The goals of this system include taking measures of temperature, humidity, luminosity and CO2 concentration and plotting maps of these variables. These features could potentially allow for climate control, crop monitoring or failure detection (e.g., a break in a plastic cover. The sensors have been selected by considering the climate and plant growth models and the requirements for their integration onboard the quadrotor. The sensors layout and placement have been determined through a study of quadrotor aerodynamics and the influence of the airflows from its rotors. All components of the system have been developed, integrated and tested through a set of field experiments in a real greenhouse. The primary contributions of this paper are the validation of the quadrotor as a platform for measuring environmental variables and the determination of the optimal location of sensors on a quadrotor.

  6. AUTOMATED INSPECTION OF POWER LINE CORRIDORS TO MEASURE VEGETATION UNDERCUT USING UAV-BASED IMAGES

    Directory of Open Access Journals (Sweden)

    M. Maurer

    2017-08-01

    Full Text Available Power line corridor inspection is a time consuming task that is performed mostly manually. As the development of UAVs made huge progress in recent years, and photogrammetric computer vision systems became well established, it is time to further automate inspection tasks. In this paper we present an automated processing pipeline to inspect vegetation undercuts of power line corridors. For this, the area of inspection is reconstructed, geo-referenced, semantically segmented and inter class distance measurements are calculated. The presented pipeline performs an automated selection of the proper 3D reconstruction method for on the one hand wiry (power line, and on the other hand solid objects (surrounding. The automated selection is realized by performing pixel-wise semantic segmentation of the input images using a Fully Convolutional Neural Network. Due to the geo-referenced semantic 3D reconstructions a documentation of areas where maintenance work has to be performed is inherently included in the distance measurements and can be extracted easily. We evaluate the influence of the semantic segmentation according to the 3D reconstruction and show that the automated semantic separation in wiry and dense objects of the 3D reconstruction routine improves the quality of the vegetation undercut inspection. We show the generalization of the semantic segmentation to datasets acquired using different acquisition routines and to varied seasons in time.

  7. Automated Inspection of Power Line Corridors to Measure Vegetation Undercut Using Uav-Based Images

    Science.gov (United States)

    Maurer, M.; Hofer, M.; Fraundorfer, F.; Bischof, H.

    2017-08-01

    Power line corridor inspection is a time consuming task that is performed mostly manually. As the development of UAVs made huge progress in recent years, and photogrammetric computer vision systems became well established, it is time to further automate inspection tasks. In this paper we present an automated processing pipeline to inspect vegetation undercuts of power line corridors. For this, the area of inspection is reconstructed, geo-referenced, semantically segmented and inter class distance measurements are calculated. The presented pipeline performs an automated selection of the proper 3D reconstruction method for on the one hand wiry (power line), and on the other hand solid objects (surrounding). The automated selection is realized by performing pixel-wise semantic segmentation of the input images using a Fully Convolutional Neural Network. Due to the geo-referenced semantic 3D reconstructions a documentation of areas where maintenance work has to be performed is inherently included in the distance measurements and can be extracted easily. We evaluate the influence of the semantic segmentation according to the 3D reconstruction and show that the automated semantic separation in wiry and dense objects of the 3D reconstruction routine improves the quality of the vegetation undercut inspection. We show the generalization of the semantic segmentation to datasets acquired using different acquisition routines and to varied seasons in time.

  8. USING A MICRO-UAV FOR ULTRA-HIGH RESOLUTION MULTI-SENSOR OBSERVATIONS OF ANTARCTIC MOSS BEDS

    Directory of Open Access Journals (Sweden)

    A. Lucieer

    2012-07-01

    Full Text Available This study is the first to use an Unmanned Aerial Vehicle (UAV for mapping moss beds in Antarctica. Mosses can be used as indicators for the regional effects of climate change. Mapping and monitoring their extent and health is therefore important. UAV aerial photography provides ultra-high resolution spatial data for this purpose. We developed a technique to extract an extremely dense 3D point cloud from overlapping UAV aerial photography based on structure from motion (SfM algorithms. The combination of SfM and patch-based multi-view stereo image vision algorithms resulted in a 2 cm resolution digital terrain model (DTM. This detailed topographic information combined with vegetation indices derived from a 6-band multispectral sensor enabled the assessment of moss bed health. This novel UAV system has allowed us to map different environmental characteristics of the moss beds at ultra-high resolution providing us with a better understanding of these fragile Antarctic ecosystems. The paper provides details on the different UAV instruments and the image processing framework resulting in DEMs, vegetation indices, and terrain derivatives.

  9. UAV measurements of aerosol properties at the Cyprus institute

    Science.gov (United States)

    Neitola, Kimmo; Sciare, Jean; Keleshis, Christos; Pikridas, Michael; Argyrides, Marios; Vouterakos, Panagiotis; Antoniou, Panyiota; Apostolou, Apostolos; Savvides, Constantinos; Vrekoussis, Mihalis; Mihalopoulos, Nikos; Biskos, George; Gao, Ru-Shan; Murphy, Daniel; Schrod, Jann; Weber, Daniel; Bingemer, Heinz; Mocnik, Grisa

    2017-04-01

    Unmanned Aerial Vehicles (UAVs) provide a cost-effective and easy-to-use method to document the vertical profiles of aerosol particles and their physical and optical properties, within and above the boundary layer. These observations combined with satellite and ground data together can provide important information and model constrains regarding the impact of aerosols on the air quality and regional climate. Cyprus is a unique place to observe long-range transported pollution and dust originating from different areas (Europe, Africa, Turkey, and Middle East) and perform such aerosol profiling. The USRL team at the Cyprus Institute has recently started weekly routine flights with a newly developed UAV fleet to build a unique dataset of vertical profile observations. Instrumentation on the UAVs includes miniature Scanning Aerosol Sun Photometer (miniSASP, Murphy et al., 2015), Printed Optical Particle Spectrometer (POPS, Gao et al., 2016), Ice nuclei sampler (IN) and Dual Wavelength absorption Prototype (DWP) together with the measured meteorological parameters (P, T and RH). The UAV fleet is still expanding, as well as the instrumentation, and preliminary test flights have led to very promising results. The UAV ascend up to approximately the middle of the boundary layer, defined by LIDAR measurements at Limassol, where the UAV will fly on one altitude for several minutes ensuring stable data collection. After flying on one altitude, the UAV will continue ascending above the boundary layer, where another level flight will take place for data gathering, before descending for safe landing. The miniSASP measures the sun irradiance and sky radiance at four wavelengths (460, 550, 670 and 680nm) by doing continuous almucantar scans every 30 s. The instrument installation compensates for the pitch and roll of the UAV with 4 Hz frequency. For this reason, the flights are designed to maintain level flight conditions, to ensure proper data acquisition, and to obtain data from

  10. Beach Volume Change Using Uav Photogrammetry Songjung Beach, Korea

    Science.gov (United States)

    Yoo, C. I.; Oh, T. S.

    2016-06-01

    Natural beach is controlled by many factors related to wave and tidal forces, wind, sediment, and initial topography. For this reason, if numerous topographic data of beach is accurately collected, coastal erosion/acceleration is able to be assessed and clarified. Generally, however, many studies on coastal erosion have limitation to analyse the whole beach, carried out of partial area as like shoreline (horizontal 2D) and beach profile (vertical 2D) on account of limitation of numerical simulation. This is an important application for prevention of coastal erosion, and UAV photogrammetry is also used to 3D topographic data. This paper analyses the use of unmanned aerial vehicles (UAV) to 3D map and beach volume change. UAV (Quadcopter) equipped with a non-metric camera was used to acquire images in Songjung beach which is located south-east Korea peninsula. The dynamics of beach topography, its geometric properties and estimates of eroded and deposited sand volumes were determined by combining elevation data with quarterly RTK-VRS measurements. To explore the new possibilities for assessment of coastal change we have developed a methodology for 3D analysis of coastal topography evolution based on existing high resolution elevation data combined with low coast, UAV and on-ground RTK-VRS surveys. DSMs were obtained by stereo-matching using Agisoft Photoscan. Using GCPs the vertical accuracy of the DSMs was found to be 10 cm or better. The resulting datasets were integrated in a local coordinates and the method proved to be a very useful fool for the detection of areas where coastal erosion occurs and for the quantification of beach change. The value of such analysis is illustrated by applications to coastal of South Korea sites that face significant management challenges.

  11. BEACH VOLUME CHANGE USING UAV PHOTOGRAMMETRY SONGJUNG BEACH, KOREA

    Directory of Open Access Journals (Sweden)

    C. I. Yoo

    2016-06-01

    Full Text Available Natural beach is controlled by many factors related to wave and tidal forces, wind, sediment, and initial topography. For this reason, if numerous topographic data of beach is accurately collected, coastal erosion/acceleration is able to be assessed and clarified. Generally, however, many studies on coastal erosion have limitation to analyse the whole beach, carried out of partial area as like shoreline (horizontal 2D and beach profile (vertical 2D on account of limitation of numerical simulation. This is an important application for prevention of coastal erosion, and UAV photogrammetry is also used to 3D topographic data. This paper analyses the use of unmanned aerial vehicles (UAV to 3D map and beach volume change. UAV (Quadcopter equipped with a non-metric camera was used to acquire images in Songjung beach which is located south-east Korea peninsula. The dynamics of beach topography, its geometric properties and estimates of eroded and deposited sand volumes were determined by combining elevation data with quarterly RTK-VRS measurements. To explore the new possibilities for assessment of coastal change we have developed a methodology for 3D analysis of coastal topography evolution based on existing high resolution elevation data combined with low coast, UAV and on-ground RTK-VRS surveys. DSMs were obtained by stereo-matching using Agisoft Photoscan. Using GCPs the vertical accuracy of the DSMs was found to be 10 cm or better. The resulting datasets were integrated in a local coordinates and the method proved to be a very useful fool for the detection of areas where coastal erosion occurs and for the quantification of beach change. The value of such analysis is illustrated by applications to coastal of South Korea sites that face significant management challenges.

  12. A Novel Online Data-Driven Algorithm for Detecting UAV Navigation Sensor Faults.

    Science.gov (United States)

    Sun, Rui; Cheng, Qi; Wang, Guanyu; Ochieng, Washington Yotto

    2017-09-29

    The use of Unmanned Aerial Vehicles (UAVs) has increased significantly in recent years. On-board integrated navigation sensors are a key component of UAVs' flight control systems and are essential for flight safety. In order to ensure flight safety, timely and effective navigation sensor fault detection capability is required. In this paper, a novel data-driven Adaptive Neuron Fuzzy Inference System (ANFIS)-based approach is presented for the detection of on-board navigation sensor faults in UAVs. Contrary to the classic UAV sensor fault detection algorithms, based on predefined or modelled faults, the proposed algorithm combines an online data training mechanism with the ANFIS-based decision system. The main advantages of this algorithm are that it allows real-time model-free residual analysis from Kalman Filter (KF) estimates and the ANFIS to build a reliable fault detection system. In addition, it allows fast and accurate detection of faults, which makes it suitable for real-time applications. Experimental results have demonstrated the effectiveness of the proposed fault detection method in terms of accuracy and misdetection rate.

  13. Reproducibility of UAV-based earth surface topography based on structure-from-motion algorithms.

    Science.gov (United States)

    Clapuyt, François; Vanacker, Veerle; Van Oost, Kristof

    2014-05-01

    A representation of the earth surface at very high spatial resolution is crucial to accurately map small geomorphic landforms with high precision. Very high resolution digital surface models (DSM) can then be used to quantify changes in earth surface topography over time, based on differencing of DSMs taken at various moments in time. However, it is compulsory to have both high accuracy for each topographic representation and consistency between measurements over time, as DSM differencing automatically leads to error propagation. This study investigates the reproducibility of reconstructions of earth surface topography based on structure-from-motion (SFM) algorithms. To this end, we equipped an eight-propeller drone with a standard reflex camera. This equipment can easily be deployed in the field, as it is a lightweight, low-cost system in comparison with classic aerial photo surveys and terrestrial or airborne LiDAR scanning. Four sets of aerial photographs were created for one test field. The sets of airphotos differ in focal length, and viewing angles, i.e. nadir view and ground-level view. In addition, the importance of the accuracy of ground control points for the construction of a georeferenced point cloud was assessed using two different GPS devices with horizontal accuracy at resp. the sub-meter and sub-decimeter level. Airphoto datasets were processed with SFM algorithm and the resulting point clouds were georeferenced. Then, the surface representations were compared with each other to assess the reproducibility of the earth surface topography. Finally, consistency between independent datasets is discussed.

  14. Health monitoring of unmanned aerial vehicle based on optical fiber sensor array

    Science.gov (United States)

    Luo, Yuxiang; Shen, Jingshi; Shao, Fei; Guo, Chunhui; Yang, Ning; Zhang, Jiande

    2017-10-01

    The unmanned aerial vehicle (UAV) in flight needs to face the complicated environment, especially to withstand harsh weather conditions, such as the temperature and pressure. Compared with conventional sensors, fiber Bragg grating (FBG) sensor has the advantages of small size, light weight, high reliability, high precision, anti-electromagnetic interference, long lift-span, moistureproof and good resistance to causticity. It's easy to be embedded in composite structural components of UAVs. In the paper, over 1000 FBG sensors distribute regularly on a wide range of UAVs body, combining wavelength division multiplexing (WDM), time division multiplexing (TDM) and multichannel parallel architecture. WDM has the advantage of high spatial resolution. TDM has the advantage of large capacity and wide range. It is worthful to constitute a sensor network by different technologies. For the signal demodulation of FBG sensor array, WDM works by means of wavelength scanning light sources and F-P etalon. TDM adopts the technology of optical time-domain reflectometry. In order to demodulate efficiently, the most proper sensor multiplex number with some reflectivity is given by the curves fitting. Due to the regular array arrangement of FBG sensors on the UAVs, we can acquire the health state of UAVs in the form of 3D visualization. It is helpful to master the information of health status rapidly and give a real-time health evaluation.

  15. Cross-Correlation-Based Structural System Identification Using Unmanned Aerial Vehicles

    Directory of Open Access Journals (Sweden)

    Hyungchul Yoon

    2017-09-01

    Full Text Available Computer vision techniques have been employed to characterize dynamic properties of structures, as well as to capture structural motion for system identification purposes. All of these methods leverage image-processing techniques using a stationary camera. This requirement makes finding an effective location for camera installation difficult, because civil infrastructure (i.e., bridges, buildings, etc. are often difficult to access, being constructed over rivers, roads, or other obstacles. This paper seeks to use video from Unmanned Aerial Vehicles (UAVs to address this problem. As opposed to the traditional way of using stationary cameras, the use of UAVs brings the issue of the camera itself moving; thus, the displacements of the structure obtained by processing UAV video are relative to the UAV camera. Some efforts have been reported to compensate for the camera motion, but they require certain assumptions that may be difficult to satisfy. This paper proposes a new method for structural system identification using the UAV video directly. Several challenges are addressed, including: (1 estimation of an appropriate scale factor; and (2 compensation for the rolling shutter effect. Experimental validation is carried out to validate the proposed approach. The experimental results demonstrate the efficacy and significant potential of the proposed approach.

  16. Feasibility of Turing-Style Tests for Autonomous Aerial Vehicle "Intelligence"

    Science.gov (United States)

    Young, Larry A.

    2007-01-01

    A new approach is suggested to define and evaluate key metrics as to autonomous aerial vehicle performance. This approach entails the conceptual definition of a "Turing Test" for UAVs. Such a "UAV Turing test" would be conducted by means of mission simulations and/or tailored flight demonstrations of vehicles under the guidance of their autonomous system software. These autonomous vehicle mission simulations and flight demonstrations would also have to be benchmarked against missions "flown" with pilots/human-operators in the loop. In turn, scoring criteria for such testing could be based upon both quantitative mission success metrics (unique to each mission) and by turning to analog "handling quality" metrics similar to the well-known Cooper-Harper pilot ratings used for manned aircraft. Autonomous aerial vehicles would be considered to have successfully passed this "UAV Turing Test" if the aggregate mission success metrics and handling qualities for the autonomous aerial vehicle matched or exceeded the equivalent metrics for missions conducted with pilots/human-operators in the loop. Alternatively, an independent, knowledgeable observer could provide the "UAV Turing Test" ratings of whether a vehicle is autonomous or "piloted." This observer ideally would, in the more sophisticated mission simulations, also have the enhanced capability of being able to override the scripted mission scenario and instigate failure modes and change of flight profile/plans. If a majority of mission tasks are rated as "piloted" by the observer, when in reality the vehicle/simulation is fully- or semi- autonomously controlled, then the vehicle/simulation "passes" the "UAV Turing Test." In this regards, this second "UAV Turing Test" approach is more consistent with Turing s original "imitation game" proposal. The overall feasibility, and important considerations and limitations, of such an approach for judging/evaluating autonomous aerial vehicle "intelligence" will be discussed from a

  17. Targeted Applications of Unmanned Aerial Vehicles (Drones) in Telemedicine.

    Science.gov (United States)

    Bhatt, Kunj; Pourmand, Ali; Sikka, Neal

    2018-02-28

    Advances in technology have revolutionized the medical field and changed the way healthcare is delivered. Unmanned aerial vehicles (UAVs) are the next wave of technological advancements that have the potential to make a huge splash in clinical medicine. UAVs, originally developed for military use, are making their way into the public and private sector. Because they can be flown autonomously and can reach almost any geographical location, the significance of UAVs are becoming increasingly apparent in the medical field. We conducted a comprehensive review of the English language literature via the PubMed and Google Scholar databases using search terms "unmanned aerial vehicles," "UAVs," and "drone." Preference was given to clinical trials and review articles that addressed the keywords and clinical medicine. Potential applications of UAVs in medicine are broad. Based on articles identified, we grouped UAV application in medicine into three categories: (1) Prehospital Emergency Care; (2) Expediting Laboratory Diagnostic Testing; and (3) Surveillance. Currently, UAVs have been shown to deliver vaccines, automated external defibrillators, and hematological products. In addition, they are also being studied in the identification of mosquito habitats as well as drowning victims at beaches as a public health surveillance modality. These preliminary studies shine light on the possibility that UAVs may help to increase access to healthcare for patients who may be otherwise restricted from proper care due to cost, distance, or infrastructure. As with any emerging technology and due to the highly regulated healthcare environment, the safety and effectiveness of this technology need to be thoroughly discussed. Despite the many questions that need to be answered, the application of drones in medicine appears to be promising and can both increase the quality and accessibility of healthcare.

  18. Intification and modelling of flight characteristics for self-build shock flyer type UAV

    Science.gov (United States)

    Rashid., Z. A.; Dardin, A. S. F. Syed.; Azid, A. A.; Ahmad, K. A.

    2018-02-01

    The development of an autonomous Unmanned Aerial Vehicle (UAV) requires a fundamentals studies of the UAV's flight characteristic. The aim of this study is to identify and model the flight characteristic of a conventional fixed-wing type UAV. Subsequence to this, the mode of flight of the UAV can be investigated. One technique to identify the characteristic of a UAV is a flight test where it required specific maneuvering to be executed while measuring the attitude sensor. In this study, a simple shock flyer type UAV was used as the aircraft. The result shows that the modeled flight characteristic has a significant relation with actual values but the fitting value is rather small. It is suggested that the future study is conducted with an improvement of the physical UAV, data filtering and better system identification methods.

  19. Combination of UAV and terrestrial photogrammetry to assess rapid glacier evolution and map glacier hazards

    Science.gov (United States)

    Fugazza, Davide; Scaioni, Marco; Corti, Manuel; D'Agata, Carlo; Azzoni, Roberto Sergio; Cernuschi, Massimo; Smiraglia, Claudio; Diolaiuti, Guglielmina Adele

    2018-04-01

    Tourists and hikers visiting glaciers all year round face hazards such as sudden terminus collapses, typical of such a dynamically evolving environment. In this study, we analyzed the potential of different survey techniques to analyze hazards of the Forni Glacier, an important geosite located in Stelvio Park (Italian Alps). We carried out surveys in the 2016 ablation season and compared point clouds generated from an unmanned aerial vehicle (UAV) survey, close-range photogrammetry and terrestrial laser scanning (TLS). To investigate the evolution of glacier hazards and evaluate the glacier thinning rate, we also used UAV data collected in 2014 and a digital elevation model (DEM) created from an aerial photogrammetric survey of 2007. We found that the integration between terrestrial and UAV photogrammetry is ideal for mapping hazards related to the glacier collapse, while TLS is affected by occlusions and is logistically complex in glacial terrain. Photogrammetric techniques can therefore replace TLS for glacier studies and UAV-based DEMs hold potential for becoming a standard tool in the investigation of glacier thickness changes. Based on our data sets, an increase in the size of collapses was found over the study period, and the glacier thinning rates went from 4.55 ± 0.24 m a-1 between 2007 and 2014 to 5.20 ± 1.11 m a-1 between 2014 and 2016.

  20. Automated UAV-based mapping for airborne reconnaissance and video exploitation

    Science.gov (United States)

    Se, Stephen; Firoozfam, Pezhman; Goldstein, Norman; Wu, Linda; Dutkiewicz, Melanie; Pace, Paul; Naud, J. L. Pierre

    2009-05-01

    Airborne surveillance and reconnaissance are essential for successful military missions. Such capabilities are critical for force protection, situational awareness, mission planning, damage assessment and others. UAVs gather huge amount of video data but it is extremely labour-intensive for operators to analyse hours and hours of received data. At MDA, we have developed a suite of tools towards automated video exploitation including calibration, visualization, change detection and 3D reconstruction. The on-going work is to improve the robustness of these tools and automate the process as much as possible. Our calibration tool extracts and matches tie-points in the video frames incrementally to recover the camera calibration and poses, which are then refined by bundle adjustment. Our visualization tool stabilizes the video, expands its field-of-view and creates a geo-referenced mosaic from the video frames. It is important to identify anomalies in a scene, which may include detecting any improvised explosive devices (IED). However, it is tedious and difficult to compare video clips to look for differences manually. Our change detection tool allows the user to load two video clips taken from two passes at different times and flags any changes between them. 3D models are useful for situational awareness, as it is easier to understand the scene by visualizing it in 3D. Our 3D reconstruction tool creates calibrated photo-realistic 3D models from video clips taken from different viewpoints, using both semi-automated and automated approaches. The resulting 3D models also allow distance measurements and line-of- sight analysis.

  1. Aerial photogrammetry procedure optimized for micro uav

    Directory of Open Access Journals (Sweden)

    T. Anai

    2014-06-01

    Full Text Available This paper proposes the automatic aerial photogrammetry procedure optimized for Micro UAV that has ability of autonomous flight. The most important goal of our proposed method is the reducing the processing cost for fully automatic reconstruction of DSM from a large amount of image obtained from Micro UAV. For this goal, we have developed automatic corresponding point generation procedure using feature point tracking algorithm considering position and attitude information, which obtained from onboard GPS-IMU integrated on Micro UAV. In addition, we have developed the automatic exterior orientation and registration procedure from the automatic generated corresponding points on each image and position and attitude information from Micro UAV. Moreover, in order to reconstruct precise DSM, we have developed the area base matching process which considering edge information. In this paper, we describe processing flow of our automatic aerial photogrammetry. Moreover, the accuracy assessment is also described. Furthermore, some application of automatic reconstruction of DSM will be desired.

  2. a Mobile Multi-Sensor Platform for Building Reconstruction Integrating Terrestrial and Autonomous Uav-Based Close Range Data Acquisition

    Science.gov (United States)

    Cefalu, A.; Haala, N.; Schmohl, S.; Neumann, I.; Genz, T.

    2017-08-01

    Photogrammetric data capture of complex 3D objects using UAV imagery has become commonplace. Software tools based on algorithms like Structure-from-Motion and multi-view stereo image matching enable the fully automatic generation of densely meshed 3D point clouds. In contrast, the planning of a suitable image network usually requires considerable effort of a human expert, since this step directly influences the precision and completeness of the resulting point cloud. Planning of suitable camera stations can be rather complex, in particular for objects like buildings, bridges and monuments, which frequently feature strong depth variations to be acquired by high resolution images at a short distance. Within the paper, we present an automatic flight mission planning tool, which generates flight lines while aiming at camera configurations, which maintain a roughly constant object distance, provide sufficient image overlap and avoid unnecessary stations. Planning is based on a coarse Digital Surface Model and an approximate building outline. As a proof of concept, we use the tool within our research project MoVEQuaD, which aims at the reconstruction of building geometry at sub-centimetre accuracy.

  3. Using LTE Networks for UAV Command and Control Link

    DEFF Research Database (Denmark)

    Nguyen, Huan Cong; Amorim, Rafhael Medeiros de; Wigard, Jeroen

    2017-01-01

    In this paper we investigate the ability of Long-Term Evolution (LTE) network to provide coverage for Unmanned Aerial Vehicles (UAVs) in a rural area, in particular for the Command and Control (C2) downlink. The study takes into consideration the dependency of the large-scale path loss on the hei......In this paper we investigate the ability of Long-Term Evolution (LTE) network to provide coverage for Unmanned Aerial Vehicles (UAVs) in a rural area, in particular for the Command and Control (C2) downlink. The study takes into consideration the dependency of the large-scale path loss...... on the height of the UAV, which is derived from actual measurements, and a real-world cellular network layout and configuration. The results indicate that interference is the dominant factor limiting the cellular coverage for UAVs in the downlink: outage level increases from 4.2% at 1.5 m height to 51.7% at 120...

  4. Current development of UAV sense and avoid system

    Science.gov (United States)

    Zhahir, A.; Razali, A.; Mohd Ajir, M. R.

    2016-10-01

    As unmanned aerial vehicles (UAVs) are now gaining high interests from civil and commercialised market, the automatic sense and avoid (SAA) system is currently one of the essential features in research spotlight of UAV. Several sensor types employed in current SAA research and technology of sensor fusion that offers a great opportunity in improving detection and tracking system are presented here. The purpose of this paper is to provide an overview of SAA system development in general, as well as the current challenges facing UAV researchers and designers.

  5. Dynamic Data-Driven UAV Network for Plume Characterization

    Science.gov (United States)

    2016-05-23

    AFRL-AFOSR-VA-TR-2016-0203 Dynamic Data-Driven UAV Network for Plume Characterization Kamran Mohseni UNIVERSITY OF FLORIDA Final Report 05/23/2016...AND SUBTITLE Dynamic Data-Driven UAV Network for Plume Characterization 5a.  CONTRACT NUMBER 5b.  GRANT NUMBER FA9550-13-1-0090 5c.  PROGRAM ELEMENT...studied a dynamic data driven (DDD) approach to operation of a heterogeneous team of unmanned aerial vehicles ( UAVs ) or micro/miniature aerial

  6. Automatic detection of blurred images in UAV image sets

    Science.gov (United States)

    Sieberth, Till; Wackrow, Rene; Chandler, Jim H.

    2016-12-01

    Unmanned aerial vehicles (UAV) have become an interesting and active research topic for photogrammetry. Current research is based on images acquired by an UAV, which have a high ground resolution and good spectral and radiometrical resolution, due to the low flight altitudes combined with a high resolution camera. UAV image flights are also cost effective and have become attractive for many applications including, change detection in small scale areas. One of the main problems preventing full automation of data processing of UAV imagery is the degradation effect of blur caused by camera movement during image acquisition. This can be caused by the normal flight movement of the UAV as well as strong winds, turbulence or sudden operator inputs. This blur disturbs the visual analysis and interpretation of the data, causes errors and can degrade the accuracy in automatic photogrammetric processing algorithms. The detection and removal of these images is currently achieved manually, which is both time consuming and prone to error, particularly for large image-sets. To increase the quality of data processing an automated process is necessary, which must be both reliable and quick. This paper describes the development of an automatic filtering process, which is based upon the quantification of blur in an image. Images with known blur are processed digitally to determine a quantifiable measure of image blur. The algorithm is required to process UAV images fast and reliably to relieve the operator from detecting blurred images manually. The newly developed method makes it possible to detect blur caused by linear camera displacement and is based on human detection of blur. Humans detect blurred images best by comparing it to other images in order to establish whether an image is blurred or not. The developed algorithm simulates this procedure by creating an image for comparison using image processing. Creating internally a comparable image makes the method independent of

  7. Optimum Route Planning and Scheduling for Unmanned Aerial Vehicles

    National Research Council Canada - National Science Library

    Sonmezocak, Erkan; Kurt, Senol

    2008-01-01

    .... The route planning of UAVs is the most critical and challenging problem of wartime. This thesis will develop three algorithms to solve a model that produces executable routings in order to dispatch three Unmanned Aerial Vehicles (UAV...

  8. Vehicle State Estimator based regenerative braking implementation on an electric vehicle to improve lateral vehicle stability

    NARCIS (Netherlands)

    Jansen, S.T.H.; van Boekel, J.J.P.; Iersel, van S.S.; Besselink, I.J.M.; Nijmeijer, H.

    2013-01-01

    The driving range of electric vehicles can be extended using regenerative braking. Regenerative braking uses the electric drive system, and therefore only the driven wheels, for decelerating the vehicle. Braking on one axle affects the stability of the vehicle, especially for road conditions with

  9. Vehicle state estimator based regenerative braking implementation on an electric vehicle to improve lateral vehicle stability

    NARCIS (Netherlands)

    Jansen, S.T.H.; Boekel, J.J.P. van; Iersel, S.S. van; Besselink, I.J.M.; Nijmeijer, H.

    2013-01-01

    The driving range of electric vehicles can be extended using regenerative braking. Regenerative braking uses the elctric drive system, and therefore only the driven wheels, for decelerating the vehicle. Braking on one axle affects the stability of the vehicle, especially for road conditions with

  10. Detection of Nuclear Sources by UAV Teleoperation Using a Visuo-Haptic Augmented Reality Interface

    Directory of Open Access Journals (Sweden)

    Jacopo Aleotti

    2017-09-01

    Full Text Available A visuo-haptic augmented reality (VHAR interface is presented enabling an operator to teleoperate an unmanned aerial vehicle (UAV equipped with a custom CdZnTe-based spectroscopic gamma-ray detector in outdoor environments. The task is to localize nuclear radiation sources, whose location is unknown to the user, without the close exposure of the operator. The developed detector also enables identification of the localized nuclear sources. The aim of the VHAR interface is to increase the situation awareness of the operator. The user teleoperates the UAV using a 3DOF haptic device that provides an attractive force feedback around the location of the most intense detected radiation source. Moreover, a fixed camera on the ground observes the environment where the UAV is flying. A 3D augmented reality scene is displayed on a computer screen accessible to the operator. Multiple types of graphical overlays are shown, including sensor data acquired by the nuclear radiation detector, a virtual cursor that tracks the UAV and geographical information, such as buildings. Experiments performed in a real environment are reported using an intense nuclear source.