CHOSEN ASPECTS OF THE PRODUCTION OF THE BASIC MAP USING UAV IMAGERY

Directory of Open Access Journals (Sweden)

M. Kedzierski

2016-06-01

Full Text Available For several years there has been an increasing interest in the use of unmanned aerial vehicles in acquiring image data from a low altitude. Considering the cost-effectiveness of the flight time of UAVs vs. conventional airplanes, the use of the former is advantageous when generating large scale accurate ortophotos. Through the development of UAV imagery, we can update large-scale basic maps. These maps are cartographic products which are used for registration, economic, and strategic planning. On the basis of these maps other cartographic maps are produced, for example maps used building planning. The article presents an assessesment of the usefulness of orthophotos based on UAV imagery to upgrade the basic map. In the research a compact, non-metric camera, mounted on a fixed wing powered by an electric motor was used. The tested area covered flat, agricultural and woodland terrains. The processing and analysis of orthorectification were carried out with the INPHO UASMaster programme. Due to the effect of UAV instability on low-altitude imagery, the use of non-metric digital cameras and the low-accuracy GPS-INS sensors, the geometry of images is visibly lower were compared to conventional digital aerial photos (large values of phi and kappa angles. Therefore, typically, low-altitude images require large along- and across-track direction overlap – usually above 70 %. As a result of the research orthoimages were obtained with a resolution of 0.06 meters and a horizontal accuracy of 0.10m. Digitized basic maps were used as the reference data. The accuracy of orthoimages vs. basic maps was estimated based on the study and on the available reference sources. As a result, it was found that the geometric accuracy and interpretative advantages of the final orthoimages allow the updating of basic maps. It is estimated that such an update of basic maps based on UAV imagery reduces processing time by approx. 40%.

Experimental Methods for UAV Aerodynamic and Propulsion Performance Assessment

Directory of Open Access Journals (Sweden)

Stefan ANTON

2015-06-01

Full Text Available This paper presents an experimental method for assessing the performances and the propulsion power of a UAV in several points based on telemetry. The points in which we make the estimations are chosen based on several criteria and the fallowing parameters are measured: airspeed, time-to-climb, altitude and the horizontal distance. With the estimated propulsion power and knowing the shaft motor power, the propeller efficiency is determined at several speed values. The shaft motor power was measured in the lab using the propeller as a break. Many flights, using the same UAV configuration, were performed before extracting flight data, in order to reduce the instrumental or statistic errors. This paper highlights both the methodology of processing the data and the validation of theoretical results.

UAV magnetometry in mineral exploration and infrastructure detection

Science.gov (United States)

Braun, A.; Parvar, K.; Burns, M.

2015-12-01

Magnetic surveys are critical tools in mineral exploration and UAVs have the potential to carry magnetometers. UAV surveys can offer higher spatial resolution than traditional airborne surveys, and higher coverage than terrestrial surveys. However, the main advantage is their ability to sense the magnetic field in 3-D, while most airborne or terrestrial surveys are restricted to 2-D acquisition. This study compares UAV magnetic data from two different UAVs (JIB drone, DJI Phantom 2) and three different magnetometers (GEM GSPM35, Honeywell HMR2300, GEM GST-19). The first UAV survey was conducted using a JIB UAV with a GSPM35 flying at 10-15 m above ground. The survey's goal was to detect intrusive Rhyolite bodies for primary mineral exploration. The survey resulted in a better understanding of the validity/resolution of UAV data and led to improved knowledge about the geological structures in the area. The results further drove the design of a following terrestrial survey. Comparing the UAV data with an available airborne survey (upward continued to 250 m) reveals that the UAV data has superior spatial resolution, but exhibits a higher noise level. The magnetic anomalies related to the Rhyolite intrusions is about 109 nT and translates into an estimated depth of approximately 110 meters. The second survey was conducted using an in-house developed UAV magnetometer system equipped with a DJI Phantom 2 and a Honeywell HMR2300 fluxgate magnetometer. By flying the sensor in different altitudes, the vertical and horizontal gradients can be derived leading to full 3-D magnetic data volumes which can provide improved constraints for source depth/geometry characterization. We demonstrate that a buried steam pipeline was detectable with the UAV magnetometer system and compare the resulting data with a terrestrial survey using a GEM GST-19 Proton Precession Magnetometer.

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.

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...

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.

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.

UAV Low Altitude Photogrammetry for Power Line Inspection

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Yong Zhang

2017-01-01

Full Text Available When the distance between an obstacle and a power line is less than the discharge distance, a discharge arc can be generated, resulting in the interruption of power supplies. Therefore, regular safety inspections are necessary to ensure the safe operation of power grids. Tall vegetation and buildings are the key factors threatening the safe operation of extra high voltage transmission lines within a power line corridor. Manual or laser intensity direction and ranging (LiDAR based inspections are time consuming and expensive. To make safety inspections more efficient and flexible, a low-altitude unmanned aerial vehicle (UAV remote-sensing platform, equipped with an optical digital camera, was used to inspect power line corridors. We propose a semi-patch matching algorithm based on epipolar constraints, using both the correlation coefficient (CC and the shape of its curve to extract three dimensional (3D point clouds for a power line corridor. We use a stereo image pair from inter-strip to improve power line measurement accuracy by transforming the power line direction to an approximately perpendicular to epipolar line. The distance between the power lines and the 3D point cloud is taken as a criterion for locating obstacles within the power line corridor automatically. Experimental results show that our proposed method is a reliable, cost effective, and applicable way for practical power line inspection and can locate obstacles within the power line corridor with accuracy better than ±0.5 m.

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.

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.

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.

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.

Improving estimation of flight altitude in wildlife telemetry studies

Science.gov (United States)

Poessel, Sharon; Duerr, Adam E.; Hall, Jonathan C.; Braham, Melissa A.; Katzner, Todd

2018-01-01

Altitude measurements from wildlife tracking devices, combined with elevation data, are commonly used to estimate the flight altitude of volant animals. However, these data often include measurement error. Understanding this error may improve estimation of flight altitude and benefit applied ecology.There are a number of different approaches that have been used to address this measurement error. These include filtering based on GPS data, filtering based on behaviour of the study species, and use of state-space models to correct measurement error. The effectiveness of these approaches is highly variable.Recent studies have based inference of flight altitude on misunderstandings about avian natural history and technical or analytical tools. In this Commentary, we discuss these misunderstandings and suggest alternative strategies both to resolve some of these issues and to improve estimation of flight altitude. These strategies also can be applied to other measures derived from telemetry data.Synthesis and applications. Our Commentary is intended to clarify and improve upon some of the assumptions made when estimating flight altitude and, more broadly, when using GPS telemetry data. We also suggest best practices for identifying flight behaviour, addressing GPS error, and using flight altitudes to estimate collision risk with anthropogenic structures. Addressing the issues we describe would help improve estimates of flight altitude and advance understanding of the treatment of error in wildlife telemetry studies.

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

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.

A fast and mobile system for registration of low-altitude visual and thermal aerial images using multiple small-scale UAVs

Science.gov (United States)

Yahyanejad, Saeed; Rinner, Bernhard

2015-06-01

The use of multiple small-scale UAVs to support first responders in disaster management has become popular because of their speed and low deployment costs. We exploit such UAVs to perform real-time monitoring of target areas by fusing individual images captured from heterogeneous aerial sensors. Many approaches have already been presented to register images from homogeneous sensors. These methods have demonstrated robustness against scale, rotation and illumination variations and can also cope with limited overlap among individual images. In this paper we focus on thermal and visual image registration and propose different methods to improve the quality of interspectral registration for the purpose of real-time monitoring and mobile mapping. Images captured by low-altitude UAVs represent a very challenging scenario for interspectral registration due to the strong variations in overlap, scale, rotation, point of view and structure of such scenes. Furthermore, these small-scale UAVs have limited processing and communication power. The contributions of this paper include (i) the introduction of a feature descriptor for robustly identifying corresponding regions of images in different spectrums, (ii) the registration of image mosaics, and (iii) the registration of depth maps. We evaluated the first method using a test data set consisting of 84 image pairs. In all instances our approach combined with SIFT or SURF feature-based registration was superior to the standard versions. Although we focus mainly on aerial imagery, our evaluation shows that the presented approach would also be beneficial in other scenarios such as surveillance and human detection. Furthermore, we demonstrated the advantages of the other two methods in case of multiple image pairs.

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.

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.

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.

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

Comprehensive UAV agricultural remote-sensing research at Texas A M University

Science.gov (United States)

Thomasson, J. Alex; Shi, Yeyin; Olsenholler, Jeffrey; Valasek, John; Murray, Seth C.; Bishop, Michael P.

2016-05-01

Unmanned aerial vehicles (UAVs) have advantages over manned vehicles for agricultural remote sensing. Flying UAVs is less expensive, is more flexible in scheduling, enables lower altitudes, uses lower speeds, and provides better spatial resolution for imaging. The main disadvantage is that, at lower altitudes and speeds, only small areas can be imaged. However, on large farms with contiguous fields, high-quality images can be collected regularly by using UAVs with appropriate sensing technologies that enable high-quality image mosaics to be created with sufficient metadata and ground-control points. In the United States, rules governing the use of aircraft are promulgated and enforced by the Federal Aviation Administration (FAA), and rules governing UAVs are currently in flux. Operators must apply for appropriate permissions to fly UAVs. In the summer of 2015 Texas A&M University's agricultural research agency, Texas A&M AgriLife Research, embarked on a comprehensive program of remote sensing with UAVs at its 568-ha Brazos Bottom Research Farm. This farm is made up of numerous fields where various crops are grown in plots or complete fields. The crops include cotton, corn, sorghum, and wheat. After gaining FAA permission to fly at the farm, the research team used multiple fixed-wing and rotary-wing UAVs along with various sensors to collect images over all parts of the farm at least once per week. This article reports on details of flight operations and sensing and analysis protocols, and it includes some lessons learned in the process of developing a UAV remote-sensing effort of this sort.

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.

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.

The fusion of satellite and UAV data: simulation of high spatial resolution band

Science.gov (United States)

Jenerowicz, Agnieszka; Siok, Katarzyna; Woroszkiewicz, Malgorzata; Orych, Agata

2017-10-01

Remote sensing techniques used in the precision agriculture and farming that apply imagery data obtained with sensors mounted on UAV platforms became more popular in the last few years due to the availability of low- cost UAV platforms and low- cost sensors. Data obtained from low altitudes with low- cost sensors can be characterised by high spatial and radiometric resolution but quite low spectral resolution, therefore the application of imagery data obtained with such technology is quite limited and can be used only for the basic land cover classification. To enrich the spectral resolution of imagery data acquired with low- cost sensors from low altitudes, the authors proposed the fusion of RGB data obtained with UAV platform with multispectral satellite imagery. The fusion is based on the pansharpening process, that aims to integrate the spatial details of the high-resolution panchromatic image with the spectral information of lower resolution multispectral or hyperspectral imagery to obtain multispectral or hyperspectral images with high spatial resolution. The key of pansharpening is to properly estimate the missing spatial details of multispectral images while preserving their spectral properties. In the research, the authors presented the fusion of RGB images (with high spatial resolution) obtained with sensors mounted on low- cost UAV platforms and multispectral satellite imagery with satellite sensors, i.e. Landsat 8 OLI. To perform the fusion of UAV data with satellite imagery, the simulation of the panchromatic bands from RGB data based on the spectral channels linear combination, was conducted. Next, for simulated bands and multispectral satellite images, the Gram-Schmidt pansharpening method was applied. As a result of the fusion, the authors obtained several multispectral images with very high spatial resolution and then analysed the spatial and spectral accuracies of processed images.

Designing and Testing a UAV Mapping System for Agricultural Field Surveying

Directory of Open Access Journals (Sweden)

Martin Peter Christiansen

2017-11-01

Full Text Available A Light Detection and Ranging (LiDAR sensor mounted on an Unmanned Aerial Vehicle (UAV can map the overflown environment in point clouds. Mapped canopy heights allow for the estimation of crop biomass in agriculture. The work presented in this paper contributes to sensory UAV setup design for mapping and textual analysis of agricultural fields. LiDAR data are combined with data from Global Navigation Satellite System (GNSS and Inertial Measurement Unit (IMU sensors to conduct environment mapping for point clouds. The proposed method facilitates LiDAR recordings in an experimental winter wheat field. Crop height estimates ranging from 0.35–0.58 m are correlated to the applied nitrogen treatments of 0–300 kg N ha . The LiDAR point clouds are recorded, mapped, and analysed using the functionalities of the Robot Operating System (ROS and the Point Cloud Library (PCL. Crop volume estimation is based on a voxel grid with a spatial resolution of 0.04 × 0.04 × 0.001 m. Two different flight patterns are evaluated at an altitude of 6 m to determine the impacts of the mapped LiDAR measurements on crop volume estimations.

Designing and Testing a UAV Mapping System for Agricultural Field Surveying.

Science.gov (United States)

Christiansen, Martin Peter; Laursen, Morten Stigaard; Jørgensen, Rasmus Nyholm; Skovsen, Søren; Gislum, René

2017-11-23

A Light Detection and Ranging (LiDAR) sensor mounted on an Unmanned Aerial Vehicle (UAV) can map the overflown environment in point clouds. Mapped canopy heights allow for the estimation of crop biomass in agriculture. The work presented in this paper contributes to sensory UAV setup design for mapping and textual analysis of agricultural fields. LiDAR data are combined with data from Global Navigation Satellite System (GNSS) and Inertial Measurement Unit (IMU) sensors to conduct environment mapping for point clouds. The proposed method facilitates LiDAR recordings in an experimental winter wheat field. Crop height estimates ranging from 0.35-0.58 m are correlated to the applied nitrogen treatments of 0-300 kg N ha . The LiDAR point clouds are recorded, mapped, and analysed using the functionalities of the Robot Operating System (ROS) and the Point Cloud Library (PCL). Crop volume estimation is based on a voxel grid with a spatial resolution of 0.04 × 0.04 × 0.001 m. Two different flight patterns are evaluated at an altitude of 6 m to determine the impacts of the mapped LiDAR measurements on crop volume estimations.

UAV low-altitude remote sensing for precision weed management

Science.gov (United States)

Precision weed management, an application of precision agriculture, accounts for within-field variability of weed infestation and herbicide damage. Unmanned aerial vehicles (UAVs) provide a unique platform for remote sensing of field crops. They are more efficient and flexible than manned agricultur...

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.

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).

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.

Baseline and Multimodal UAV GCS Interface Design

Science.gov (United States)

2013-07-01

complete a computerized version of the NASA - TLX assessment of perceived mental workload. 2.3 Results The baseline condition ran smoothly and with...System MALE Medium-altitude, Long-endurance NASA - TLX NASA Task Load Index SA Situation Awareness TDT Tucker Davis Technologies UAV Uninhabited Aerial

Recording animal vocalizations from a UAV: bat echolocation during roost re-entry.

Science.gov (United States)

Kloepper, Laura N; Kinniry, Morgan

2018-05-17

Unmanned aerial vehicles (UAVs) are rising in popularity for wildlife monitoring, but direct recordings of animal vocalizations have not yet been accomplished, likely due to the noise generated by the UAV. Echolocating bats, especially Tadarida brasiliensis, are good candidates for UAV recording due to their high-speed, high-altitude flight. Here, we use a UAV to record the signals of bats during morning roost re-entry. We designed a UAV to block the noise of the propellers from the receiving microphone, and report on the characteristics of bioacoustic recordings from a UAV. We report the first published characteristics of echolocation signals from bats during group flight and cave re-entry. We found changes in inter-individual time-frequency shape, suggesting that bats may use differences in call design when sensing in complex groups. Furthermore, our first documented successful recordings of animals in their natural habitat demonstrate that UAVs can be important tools for bioacoustic monitoring, and we discuss the ethical considerations for such monitoring.

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.

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.

Development Of Linear Quadratic Regulator Design For Small UAV System

Directory of Open Access Journals (Sweden)

Cho Zin Myint

2015-08-01

Full Text Available The aim of this paper is to know the importance role of stability analysis for both unmanned aircraft system and for all control system. The objective of paper is to develop a method for dynamic stability analysis of the design process. These are categorized intoTo design model and stability analysis of UAV based on the forces and moment equations of aircraft dynamic model To choose the suitable controller for desired altitude of a particular UAV model To analyze the stability condition for aircraft using mathematical modeling and MATLAB. In this paper the analytical model of the longitudinal dynamic of flying wing UAV has been developed using aerodynamic data. The stability characteristics of UAV can be achieved from the system transfer function with LQR controller.

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

Estimation of Vegetable Crop Parameter by Multi-temporal UAV-Borne Images

Directory of Open Access Journals (Sweden)

Thomas Moeckel

2018-05-01

Full Text Available 3D point cloud analysis of imagery collected by unmanned aerial vehicles (UAV has been shown to be a valuable tool for estimation of crop phenotypic traits, such as plant height, in several species. Spatial information about these phenotypic traits can be used to derive information about other important crop characteristics, like fresh biomass yield, which could not be derived directly from the point clouds. Previous approaches have often only considered single date measurements using a single point cloud derived metric for the respective trait. Furthermore, most of the studies focused on plant species with a homogenous canopy surface. The aim of this study was to assess the applicability of UAV imagery for capturing crop height information of three vegetables (crops eggplant, tomato, and cabbage with a complex vegetation canopy surface during a complete crop growth cycle to infer biomass. Additionally, the effect of crop development stage on the relationship between estimated crop height and field measured crop height was examined. Our study was conducted in an experimental layout at the University of Agricultural Science in Bengaluru, India. For all the crops, the crop height and the biomass was measured at five dates during one crop growth cycle between February and May 2017 (average crop height was 42.5, 35.5, and 16.0 cm for eggplant, tomato, and cabbage. Using a structure from motion approach, a 3D point cloud was created for each crop and sampling date. In total, 14 crop height metrics were extracted from the point clouds. Machine learning methods were used to create prediction models for vegetable crop height. The study demonstrates that the monitoring of crop height using an UAV during an entire growing period results in detailed and precise estimates of crop height and biomass for all three crops (R2 ranging from 0.87 to 0.97, bias ranging from −0.66 to 0.45 cm. The effect of crop development stage on the predicted crop height was

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.

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.

Feasibility Study for an Autonomous UAV -Magnetometer System -- Final Report on SERDP SEED 1509:2206

Energy Technology Data Exchange (ETDEWEB)

Roelof Versteeg; Mark McKay; Matt Anderson; Ross Johnson; Bob Selfridge; Jay Bennett

2007-09-01

Large areas across the United States are potentially contaminated with UXO, with some ranges encompassing tens to hundreds of thousands of acres. Technologies are needed which will allow for cost effective wide area scanning with 1) near 100 % coverage and 2) near 100 % detection of subsurface ordnance or features indicative of subsurface ordnance. The current approach to wide area scanning is a multi-level one, in which medium altitude fixed wing optical imaging is used for an initial site assessment. This assessment is followed with low altitude manned helicopter based magnetometry followed by surface investigations using either towed geophysical sensor arrays or man portable sensors. In order to be effective for small UXO detection, the sensing altitude for magnetic site investigations needs to be on the order of 1 – 3 meters. These altitude requirements means that manned helicopter surveys will generally only be feasible in large, open and relatively flat terrains. While such surveys are effective in mapping large areas relatively fast there are substantial mobilization/demobilization, staffing and equipment costs associated with these surveys (resulting in costs of approximately $100-$150/acre). Surface towed arrays provide high resolution maps but have other limitations, e.g. in their ability to navigate rough terrain effectively. Thus, other systems are needed allowing for effective data collection. An UAV (Unmanned Aerial Vehicle) magnetometer platform is an obvious alternative. The motivation behind such a system is that it would be safer for the operators, cheaper in initial and O&M costs, and more effective in terms of site characterization. However, while UAV data acquisition from fixed wing platforms for large (> 200 feet) stand off distances is relatively straight forward, a host of challenges exist for low stand-off distance (~ 6 feet) UAV geophysical data acquisition. The objective of SERDP SEED 1509:2006 was to identify the primary challenges

Geohazard reconnaissance mapping for potential rock boulder fall using low altitude UAV photogrammetry

Science.gov (United States)

Sharan Kumar, N.; Ashraf Mohamad Ismail, Mohd; Sukor, Nur Sabahiah Abdul; Cheang, William

2018-05-01

This paper discusses potential applications of unmanned aerial vehicles (UAVs) for evaluation of risk immediately with photos and 3-dimensional digital element. Aerial photography using UAV ready to give a powerful technique for potential rock boulder fall recognition. High-resolution outputs from this method give the chance to evaluate the site for potential rock boulder falls spatially. The utilization of UAV to capture the aerial photos is a quick, reliable, and cost-effective technique contrasted with terrestrial laser scanning method. Reconnaissance of potential rock boulder susceptible to fall is very crucial during the geotechnical investigation. This process is essential in the view of the rock fall hazards nearby site before the beginning of any preliminary work. Photogrammetric applications have empowered the automated way to deal with identification of rock boulder susceptible to fall by recognizing the location, size, and position. A developing examination of the utilization of digital photogrammetry gives numerous many benefits for civil engineering application. These advancements have made important contributions to our capabilities to create the geohazard map on potential rock boulder fall.

Development of the Main Wing Structure of a High Altitude Long Endurance UAV

Science.gov (United States)

Park, Sang Wook; Shin, Jeong Woo; Kim, Tae-Uk

2018-04-01

To enhance the flight endurance of a HALE UAV, the main wing of the UAV should have a high aspect ratio and low structural weight. Since a main wing constructed with the thin walled and slender components needed for low structural weight can suffer catastrophic failure during flight, it is important to develop a light-weight airframe without sacrificing structural integrity. In this paper, the design of the main wing of the HALE UAV was conducted using spars which were composed of a carbon-epoxy cylindrical tube and bulkheads to achieve both the weight reduction and structural integrity. The spars were sized using numerical analysis considering non-linear deformation under bending moment. Static strength testing of the wing was conducted under the most critical load condition. Then, the experimental results obtained for the wing were compared to the analytical result from the non-linear finite-element analysis. It was found that the developed main wing reduced its structural weight without any failure under the ultimate load condition of the static strength testing.

Development of a Compact High Altitude Imager and Sounding Radiometer (CHAISR)

Science.gov (United States)

Choi, R. K. Y.; Min, S.; Cho, Y. J.; Kim, K. H.; Ha, J. C.; Joo, S. W.

2017-12-01

Joint Civilian-Military Committee, under Advisory Council on Science and Technology, Korea, has approved a technology demonstration project for developing a lightweight HALE UAV (High-Altitude, Long Endurance). It aims to operate at lower stratosphere, i.e. altitude of 16 20 km, offering unique observational platform to atmospheric research community as pseudo-satellite. NIMS (National Institute of Meteorological Sciences, Korea) is responsible for a payload for atmospheric science, a Compact High Altitude Imager and Sounding Radiometer (CHAISR) to demonstrate scientific observations at lower stratosphere in the interest of improving numerical weather prediction model. CHAISR consists of three microwave radiometers (MWR) with 16 channel, and medium resolution cameras operating in a visible and infrared spectrum. One of the technological challenges for CHAISR is to accommodate those instruments within 50 W of power consumption. CHAISR will experience temperature up to -75°C, while pressure as low as 50 hPa at operational altitude. It requires passive thermal control of the payload to keep electronic subsystems warm enough for instrument operation with minimal power available. Safety features, such as payload power management and thermal control, are considered with minimal user input. Three radiometers measure atmospheric brightness temperature at frequency at around 20, 40, and 50 GHz. Retrieval process yields temperature and humidity profiles with cross track scan along the flight line. Estimated total weight of all radiometer hardware, from the antennas to data acquisition system, is less than 0.8 kg and a maximum power consumption is 15.2 W. With not enough power for blackbody calibration target, radiometers use zenith sky view at lower stratosphere as an excellent calibration target for a conventional tipping-curve calibration. Spatial distributions of clouds from visible and surface temperature from thermal cameras are used as additional information for

Fatalities in high altitude mountaineering: a review of quantitative risk estimates.

Science.gov (United States)

Weinbruch, Stephan; Nordby, Karl-Christian

2013-12-01

Quantitative estimates for mortality in high altitude mountaineering are reviewed. Special emphasis is placed on the heterogeneity of the risk estimates and on confounding. Crude estimates for mortality are on the order of 1/1000 to 40/1000 persons above base camp, for both expedition members and high altitude porters. High altitude porters have mostly a lower risk than expedition members (risk ratio for all Nepalese peaks requiring an expedition permit: 0.73; 95 % confidence interval 0.59-0.89). The summit bid is generally the most dangerous part of an expedition for members, whereas most high altitude porters die during route preparation. On 8000 m peaks, the mortality during descent from summit varies between 4/1000 and 134/1000 summiteers (members plus porters). The risk estimates are confounded by human and environmental factors. Information on confounding by gender and age is contradictory and requires further work. There are indications for safety segregation of men and women, with women being more risk averse than men. Citizenship appears to be a significant confounder. Prior high altitude mountaineering experience in Nepal has no protective effect. Commercial expeditions in the Nepalese Himalayas have a lower mortality than traditional expeditions, though after controlling for confounding, the difference is not statistically significant. The overall mortality is increasing with increasing peak altitude for expedition members but not for high altitude porters. In the Nepalese Himalayas and in Alaska, a significant decrease of mortality with calendar year was observed. A few suggestions for further work are made at the end of the article.

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

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.

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.

Determination of Shift/Bias in Digital Aerial Triangulation of UAV Imagery Sequences

Science.gov (United States)

Wierzbicki, Damian

2017-12-01

Currently UAV Photogrammetry is characterized a largely automated and efficient data processing. Depicting from the low altitude more often gains on the meaning in the uses of applications as: cities mapping, corridor mapping, road and pipeline inspections or mapping of large areas e.g. forests. Additionally, high-resolution video image (HD and bigger) is more often use for depicting from the low altitude from one side it lets deliver a lot of details and characteristics of ground surfaces features, and from the other side is presenting new challenges in the data processing. Therefore, determination of elements of external orientation plays a substantial role the detail of Digital Terrain Models and artefact-free ortophoto generation. Parallel a research on the quality of acquired images from UAV and above the quality of products e.g. orthophotos are conducted. Despite so fast development UAV photogrammetry still exists the necessity of accomplishment Automatic Aerial Triangulation (AAT) on the basis of the observations GPS/INS and via ground control points. During low altitude photogrammetric flight, the approximate elements of external orientation registered by UAV are burdened with the influence of some shift/bias errors. In this article, methods of determination shift/bias error are presented. In the process of the digital aerial triangulation two solutions are applied. In the first method shift/bias error was determined together with the drift/bias error, elements of external orientation and coordinates of ground control points. In the second method shift/bias error was determined together with the elements of external orientation, coordinates of ground control points and drift/bias error equals 0. When two methods were compared the difference for shift/bias error is more than ±0.01 m for all terrain coordinates XYZ.

Adaptive UAV Attitude Estimation Employing Unscented Kalman Filter, FOAM and Low-Cost MEMS Sensors

NARCIS (Netherlands)

Garcia de Marina Peinado, Hector; Espinosa, Felipe; Santos, Carlos

2012-01-01

Navigation employing low cost MicroElectroMechanical Systems (MEMS) sensors in Unmanned Aerial Vehicles (UAVs) is an uprising challenge. One important part of this navigation is the right estimation of the attitude angles. Most of the existent algorithms handle the sensor readings in a fixed way,

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.

Comparative Study of Wing Lift Distribution Analysis for High Altitude Long Endurance (HALE) Unmaned Aerial Vehicle

Science.gov (United States)

Silitonga, Faber Y.; Agoes Moelyadi, M.

2018-04-01

The development of High Altitude Long Endurance (HALE) Unmanned Aerial Vehicle (UAV) has been emerged for both civil and military purposes. Its ability of operating in high altitude with long endurance is important in supporting maritime applications.Preliminary analysis of HALE UAV lift distribution of the wing presented to give decisive consideration for its early development. Ensuring that the generated lift is enough to compensate its own weight. Therotical approach using Pradtl’s non-linear lifting line theory will be compared with modern numerical approach using Computational Fluid Dynamics (CFD). Results of wing lift distribution calculated from both methods will be compared to study the reliability of it. HALE UAV ITB has high aspect ratio wing and will be analyze at cruise flight condition. The result indicates difference between Non-linear Lifting Line and CFD method.

Unmanned Aerial Vehicles: Progress Toward Meeting High Altitude Endurance Aircraft Price Goals

National Research Council Canada - National Science Library

1998-01-01

...) High Altitude Endurance (HAE) Unmanned Aerial Vehicle (UAV) program to determine whether the average flyaway cost for the Global Hawk and DarkStar HAE alr vehicles will be within DOD's cost goal...

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....

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.

Augmented Reality Tool for the Situational Awareness Improvement of UAV Operators

Science.gov (United States)

Ruano, Susana; Cuevas, Carlos; Gallego, Guillermo; García, Narciso

2017-01-01

Unmanned Aerial Vehicles (UAVs) are being extensively used nowadays. Therefore, pilots of traditional aerial platforms should adapt their skills to operate them from a Ground Control Station (GCS). Common GCSs provide information in separate screens: one presents the video stream while the other displays information about the mission plan and information coming from other sensors. To avoid the burden of fusing information displayed in the two screens, an Augmented Reality (AR) tool is proposed in this paper. The AR system has two functionalities for Medium-Altitude Long-Endurance (MALE) UAVs: route orientation and target identification. Route orientation allows the operator to identify the upcoming waypoints and the path that the UAV is going to follow. Target identification allows a fast target localization, even in the presence of occlusions. The AR tool is implemented following the North Atlantic Treaty Organization (NATO) standards so that it can be used in different GCSs. The experiments show how the AR tool improves significantly the situational awareness of the UAV operators. PMID:28178189

Development of Uav Photogrammetry Method by Using Small Number of Vertical Images

Science.gov (United States)

Kunii, Y.

2018-05-01

This new and efficient photogrammetric method for unmanned aerial vehicles (UAVs) requires only a few images taken in the vertical direction at different altitudes. The method includes an original relative orientation procedure which can be applied to images captured along the vertical direction. The final orientation determines the absolute orientation for every parameter and is used for calculating the 3D coordinates of every measurement point. The measurement accuracy was checked at the UAV test site of the Japan Society for Photogrammetry and Remote Sensing. Five vertical images were taken at 70 to 90 m altitude. The 3D coordinates of the measurement points were calculated. The plane and height accuracies were ±0.093 m and ±0.166 m, respectively. These values are of higher accuracy than the results of the traditional photogrammetric method. The proposed method can measure 3D positions efficiently and would be a useful tool for construction and disaster sites and for other field surveying purposes.

Output feedback control of a quadrotor UAV using neural networks.

Science.gov (United States)

Dierks, Travis; Jagannathan, Sarangapani

2010-01-01

In this paper, a new nonlinear controller for a quadrotor unmanned aerial vehicle (UAV) is proposed using neural networks (NNs) and output feedback. The assumption on the availability of UAV dynamics is not always practical, especially in an outdoor environment. Therefore, in this work, an NN is introduced to learn the complete dynamics of the UAV online, including uncertain nonlinear terms like aerodynamic friction and blade flapping. Although a quadrotor UAV is underactuated, a novel NN virtual control input scheme is proposed which allows all six degrees of freedom (DOF) of the UAV to be controlled using only four control inputs. Furthermore, an NN observer is introduced to estimate the translational and angular velocities of the UAV, and an output feedback control law is developed in which only the position and the attitude of the UAV are considered measurable. It is shown using Lyapunov theory that the position, orientation, and velocity tracking errors, the virtual control and observer estimation errors, and the NN weight estimation errors for each NN are all semiglobally uniformly ultimately bounded (SGUUB) in the presence of bounded disturbances and NN functional reconstruction errors while simultaneously relaxing the separation principle. The effectiveness of proposed output feedback control scheme is then demonstrated in the presence of unknown nonlinear dynamics and disturbances, and simulation results are included to demonstrate the theoretical conjecture.

Evaluating rapid ground sampling and scaling estimated plant cover using UAV imagery up to Landsat for mapping arctic vegetation

Science.gov (United States)

Nelson, P.; Paradis, D. P.

2017-12-01

The small stature and spectral diversity of arctic plant taxa presents challenges in mapping arctic vegetation. Mapping vegetation at the appropriate scale is needed to visualize effects of disturbance, directional vegetation change or mapping of specific plant groups for other applications (eg. habitat mapping). Fine spatial grain of remotely sensed data (ca. 10 cm pixels) is often necessary to resolve patches of many arctic plant groups, such as bryophytes and lichens. These groups are also spectrally different from mineral, litter and vascular plants. We sought to explore method to generate high-resolution spatial and spectral data to explore better mapping methods for arctic vegetation. We sampled ground vegetation at seven sites north or west of tree-line in Alaska, four north of Fairbanks and three northwest of Bethel, respectively. At each site, we estimated cover of plant functional types in 1m2 quadrats spaced approximately every 10 m along a 100 m long transect. Each quadrat was also scanned using a field spectroradiometer (PSR+ Spectral Evolution, 400-2500 nm range) and photographed from multiple perspectives. We then flew our small UAV with a RGB camera over the transect and at least 50 m on either side collecting on imagery of the plot, which were used to generate a image mosaic and digital surface model of the plot. We compare plant functional group cover ocular estimated in situ to post-hoc estimation, either automated or using a human observer, using the quadrat photos. We also compare interpolated lichen cover from UAV scenes to estimated lichen cover using a statistical models using Landsat data, with focus on lichens. Light and yellow lichens are discernable in the UAV imagery but certain lichens, especially dark colored lichens or those with spectral signatures similar to graminoid litter, present challenges. Future efforts will focus on integrating UAV-upscaled ground cover estimates to hyperspectral sensors (eg. AVIRIS ng) for better combined

The Parrot UAV Controlled by PID Controllers

OpenAIRE

Koszewnik Andrzej

2014-01-01

The paper presents the process of modeling and designing control laws for four-rotor type of the Parrot UAV. The state space model is obtained by using several phenomena like gyroscopic effects for rigid bodies, propellers and rotors. The obtained model has been used to design PID control laws for roll, pitch, yaw angle and altitude, respectively. The numerical simulations of the closed loop model are shown that system in satisfy way stabilize flight of the quadro-rotor in all considered dire...

Volcanic Plume Measurements with UAV (Invited)

Science.gov (United States)

Shinohara, H.; Kaneko, T.; Ohminato, T.

2013-12-01

Volatiles in magmas are the driving force of volcanic eruptions and quantification of volcanic gas flux and composition is important for the volcano monitoring. Recently we developed a portable gas sensor system (Multi-GAS) to quantify the volcanic gas composition by measuring volcanic plumes and obtained volcanic gas compositions of actively degassing volcanoes. As the Multi-GAS measures variation of volcanic gas component concentrations in the pumped air (volcanic plume), we need to bring the apparatus into the volcanic plume. Commonly the observer brings the apparatus to the summit crater by himself but such measurements are not possible under conditions of high risk of volcanic eruption or difficulty to approach the summit due to topography etc. In order to overcome these difficulties, volcanic plume measurements were performed by using manned and unmanned aerial vehicles. The volcanic plume measurements by manned aerial vehicles, however, are also not possible under high risk of eruption. The strict regulation against the modification of the aircraft, such as installing sampling pipes, also causes difficulty due to the high cost. Application of the UAVs for the volcanic plume measurements has a big advantage to avoid these problems. The Multi-GAS consists of IR-CO2 and H2O gas analyzer, SO2-H2O chemical sensors and H2 semiconductor sensor and the total weight ranges 3-6 kg including batteries. The necessary conditions of the UAV for the volcanic plumes measurements with the Multi-GAS are the payloads larger than 3 kg, maximum altitude larger than the plume height and installation of the sampling pipe without contamination of the exhaust gases, as the exhaust gases contain high concentrations of H2, SO2 and CO2. Up to now, three different types of UAVs were applied for the measurements; Kite-plane (Sky Remote) at Miyakejima operated by JMA, Unmanned airplane (Air Photo Service) at Shinomoedake, Kirishima volcano, and Unmanned helicopter (Yamaha) at Sakurajima

Development of a Hybrid Uav Sensor Platform Suitable for Farm-Scale Applications in Precision Agriculture

Science.gov (United States)

Pircher, M.; Geipel, J.; Kusnierek, K.; Korsaeth, A.

2017-08-01

Today's modern precision agriculture applications have a huge demand for data with high spatial and temporal resolution. This leads to the need of unmanned aerial vehicles (UAV) as sensor platforms providing both, easy use and a high area coverage. This study shows the successful development of a prototype hybrid UAV for practical applications in precision agriculture. The UAV consists of an off-the-shelf fixed-wing fuselage, which has been enhanced with multi-rotor functionality. It was programmed to perform pre-defined waypoint missions completely autonomously, including vertical take-off, horizontal flight, and vertical landing. The UAV was tested for its return-to-home (RTH) accuracy, power consumption and general flight performance at different wind speeds. The RTH accuracy was 43.7 cm in average, with a root-mean-square error of 39.9 cm. The power consumption raised with an increase in wind speed. An extrapolation of the analysed power consumption to conditions without wind resulted in an estimated 40 km travel range, when we assumed a 25 % safety margin of remaining battery capacity. This translates to a maximal area coverage of 300 ha for a scenario with 18 m/s airspeed, 50 minutes flight time, 120 m AGL altitude, and a desired 70 % of image side-lap and 85 % forward-lap. The ground sample distance with an in-built RGB camera was 3.5 cm, which we consider sufficient for farm-scale mapping missions for most precision agriculture applications.

Estimating the Rut Depth by UAV Photogrammetry

Directory of Open Access Journals (Sweden)

Paavo Nevalainen

2017-12-01

Full Text Available The rut formation during forest operations is an undesirable phenomenon. A methodology is being proposed to measure the rut depth distribution of a logging site by photogrammetric point clouds produced by unmanned aerial vehicles (UAV. The methodology includes five processing steps that aim at reducing the noise from the surrounding trees and undergrowth for identifying the trails. A canopy height model is produced to focus the point cloud on the open pathway around the forest machine trail. A triangularized ground model is formed by a point cloud filtering method. The ground model is vectorized using the histogram of directed curvatures (HOC method to produce an overall ground visualization. Finally, a manual selection of the trails leads to an automated rut depth profile analysis. The bivariate correlation (Pearson’s r between rut depths measured manually and by UAV photogrammetry is r = 0.67 . The two-class accuracy a of detecting the rut depth exceeding 20 cm is a = 0.65 . There is potential for enabling automated large-scale evaluation of the forestry areas by using autonomous drones and the process described.

A Novel Method for Vertical Acceleration Noise Suppression of a Thrust-Vectored VTOL UAV.

Science.gov (United States)

Li, Huanyu; Wu, Linfeng; Li, Yingjie; Li, Chunwen; Li, Hangyu

2016-12-02

Acceleration is of great importance in motion control for unmanned aerial vehicles (UAVs), especially during the takeoff and landing stages. However, the measured acceleration is inevitably polluted by severe noise. Therefore, a proper noise suppression procedure is required. This paper presents a novel method to reduce the noise in the measured vertical acceleration for a thrust-vectored tail-sitter vertical takeoff and landing (VTOL) UAV. In the new procedure, a Kalman filter is first applied to estimate the UAV mass by using the information in the vertical thrust and measured acceleration. The UAV mass is then used to compute an estimate of UAV vertical acceleration. The estimated acceleration is finally fused with the measured acceleration to obtain the minimum variance estimate of vertical acceleration. By doing this, the new approach incorporates the thrust information into the acceleration estimate. The method is applied to the data measured in a VTOL UAV takeoff experiment. Two other denoising approaches developed by former researchers are also tested for comparison. The results demonstrate that the new method is able to suppress the acceleration noise substantially. It also maintains the real-time performance in the final estimated acceleration, which is not seen in the former denoising approaches. The acceleration treated with the new method can be readily used in the motion control applications for UAVs to achieve improved accuracy.

A Novel Method for Vertical Acceleration Noise Suppression of a Thrust-Vectored VTOL UAV

Directory of Open Access Journals (Sweden)

Huanyu Li

2016-12-01

Full Text Available Acceleration is of great importance in motion control for unmanned aerial vehicles (UAVs, especially during the takeoff and landing stages. However, the measured acceleration is inevitably polluted by severe noise. Therefore, a proper noise suppression procedure is required. This paper presents a novel method to reduce the noise in the measured vertical acceleration for a thrust-vectored tail-sitter vertical takeoff and landing (VTOL UAV. In the new procedure, a Kalman filter is first applied to estimate the UAV mass by using the information in the vertical thrust and measured acceleration. The UAV mass is then used to compute an estimate of UAV vertical acceleration. The estimated acceleration is finally fused with the measured acceleration to obtain the minimum variance estimate of vertical acceleration. By doing this, the new approach incorporates the thrust information into the acceleration estimate. The method is applied to the data measured in a VTOL UAV takeoff experiment. Two other denoising approaches developed by former researchers are also tested for comparison. The results demonstrate that the new method is able to suppress the acceleration noise substantially. It also maintains the real-time performance in the final estimated acceleration, which is not seen in the former denoising approaches. The acceleration treated with the new method can be readily used in the motion control applications for UAVs to achieve improved accuracy.

The Parrot UAV Controlled by PID Controllers

Directory of Open Access Journals (Sweden)

Koszewnik Andrzej

2014-08-01

Full Text Available The paper presents the process of modeling and designing control laws for four-rotor type of the Parrot UAV. The state space model is obtained by using several phenomena like gyroscopic effects for rigid bodies, propellers and rotors. The obtained model has been used to design PID control laws for roll, pitch, yaw angle and altitude, respectively. The numerical simulations of the closed loop model are shown that system in satisfy way stabilize flight of the quadro-rotor in all considered directions.

DEVELOPMENT OF UAV PHOTOGRAMMETRY METHOD BY USING SMALL NUMBER OF VERTICAL IMAGES

Directory of Open Access Journals (Sweden)

Y. Kunii

2018-05-01

Full Text Available This new and efficient photogrammetric method for unmanned aerial vehicles (UAVs requires only a few images taken in the vertical direction at different altitudes. The method includes an original relative orientation procedure which can be applied to images captured along the vertical direction. The final orientation determines the absolute orientation for every parameter and is used for calculating the 3D coordinates of every measurement point. The measurement accuracy was checked at the UAV test site of the Japan Society for Photogrammetry and Remote Sensing. Five vertical images were taken at 70 to 90 m altitude. The 3D coordinates of the measurement points were calculated. The plane and height accuracies were ±0.093 m and ±0.166 m, respectively. These values are of higher accuracy than the results of the traditional photogrammetric method. The proposed method can measure 3D positions efficiently and would be a useful tool for construction and disaster sites and for other field surveying purposes.

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.

Efficiency calibration and minimum detectable activity concentration of a real-time UAV airborne sensor system with two gamma spectrometers.

Science.gov (United States)

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

2016-04-01

A small-sized UAV (NH-UAV) airborne system with two gamma spectrometers (LaBr3 detector and HPGe detector) was developed to monitor activity concentration in serious nuclear accidents, such as the Fukushima nuclear accident. The efficiency calibration and determination of minimum detectable activity concentration (MDAC) of the specific system were studied by MC simulations at different flight altitudes, different horizontal distances from the detection position to the source term center and different source term sizes. Both air and ground radiation were considered in the models. The results obtained may provide instructive suggestions for in-situ radioactivity measurements of NH-UAV. Copyright © 2016 Elsevier Ltd. All rights reserved.

Detection of the power lines in UAV remote sensed images using spectral-spatial methods.

Science.gov (United States)

Bhola, Rishav; Krishna, Nandigam Hari; Ramesh, K N; Senthilnath, J; Anand, Gautham

2018-01-15

In this paper, detection of the power lines on images acquired by Unmanned Aerial Vehicle (UAV) based remote sensing is carried out using spectral-spatial methods. Spectral clustering was performed using Kmeans and Expectation Maximization (EM) algorithm to classify the pixels into the power lines and non-power lines. The spectral clustering methods used in this study are parametric in nature, to automate the number of clusters Davies-Bouldin index (DBI) is used. The UAV remote sensed image is clustered into the number of clusters determined by DBI. The k clustered image is merged into 2 clusters (power lines and non-power lines). Further, spatial segmentation was performed using morphological and geometric operations, to eliminate the non-power line regions. In this study, UAV images acquired at different altitudes and angles were analyzed to validate the robustness of the proposed method. It was observed that the EM with spatial segmentation (EM-Seg) performed better than the Kmeans with spatial segmentation (Kmeans-Seg) on most of the UAV images. Copyright © 2017 Elsevier Ltd. All rights reserved.

Estimating spatially distributed turbulent heat fluxes from high-resolution thermal imagery acquired with a UAV system.

Science.gov (United States)

Brenner, Claire; Thiem, Christina Elisabeth; Wizemann, Hans-Dieter; Bernhardt, Matthias; Schulz, Karsten

2017-05-19

In this study, high-resolution thermal imagery acquired with a small unmanned aerial vehicle (UAV) is used to map evapotranspiration (ET) at a grassland site in Luxembourg. The land surface temperature (LST) information from the thermal imagery is the key input to a one-source and two-source energy balance model. While the one-source model treats the surface as a single uniform layer, the two-source model partitions the surface temperature and fluxes into soil and vegetation components. It thus explicitly accounts for the different contributions of both components to surface temperature as well as turbulent flux exchange with the atmosphere. Contrary to the two-source model, the one-source model requires an empirical adjustment parameter in order to account for the effect of the two components. Turbulent heat flux estimates of both modelling approaches are compared to eddy covariance (EC) measurements using the high-resolution input imagery UAVs provide. In this comparison, the effect of different methods for energy balance closure of the EC data on the agreement between modelled and measured fluxes is also analysed. Additionally, the sensitivity of the one-source model to the derivation of the empirical adjustment parameter is tested. Due to the very dry and hot conditions during the experiment, pronounced thermal patterns developed over the grassland site. These patterns result in spatially variable turbulent heat fluxes. The model comparison indicates that both models are able to derive ET estimates that compare well with EC measurements under these conditions. However, the two-source model, with a more complex treatment of the energy and surface temperature partitioning between the soil and vegetation, outperformed the simpler one-source model in estimating sensible and latent heat fluxes. This is consistent with findings from prior studies. For the one-source model, a time-variant expression of the adjustment parameter (to account for the difference between

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

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.

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.

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.

UAV Survey Data from Clifton Camp (ST56557330, Bristol, UK

Directory of Open Access Journals (Sweden)

Stephen Gray

2015-05-01

Full Text Available This data was collected via low-altitude UAV (Unmanned Aerial Vehicle survey of an area of Clifton Camp (ST565557330, best known for its Iron Age promontory fort. The dataset comprises of metadata records, near-vertical photographs and a derived 3D polygonal mesh. This dataset has been constructed with two kinds of reuse in mind: Firstly, the area surveyed is culturally rich and underexplored; while some of the non-natural features detected by this survey can be identified, others cannot. This data is intended to inform future investigations of the site. Secondly, the survey methodologies employed and the structuring of the resulting dataset are intended to act as an exemplar, a standard method of creating survey data while prioritising open technologies, and of organising UAV survey datasets to ensure maximum re-usability.

Achievable Rates of UAV-Relayed Cooperative Cognitive Radio MIMO Systems

KAUST Repository

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

2017-01-01

We study the achievable rate of an uplink MIMO cognitive radio system where the primary user (PU) and the secondary user (SU) aim to communicate to the closest primary base station (BS) via a multi-access channel through the same unmanned aerial vehicle (UAV) relay. The SU message is then forwarded from the primary BS to the secondary network with a certain incentive reward as a part of the cooperation protocol between both networks. A special linear precoding scheme is proposed to enable the SU to exploit the PU free eigenmodes. We analyze two scenarios in which the UAV relay gain matrix is either fixed or optimized. We derive the optimal power allocation that maximizes the achievable rate of the SU respecting power budget, interference, and relay power constraints. Numerical results highlight the cognitive rate gain of our proposed scheme with respect to various problem parameters. We also highlight the effect of UAV altitude on the SU and PU rates. Finally, when the relay matrix is optimized, we show that the PU rate is remarkably enhanced and that the SU rate is only improved at high power regime.

Achievable Rates of UAV-Relayed Cooperative Cognitive Radio MIMO Systems

KAUST Repository

Sboui, Lokman

2017-04-19

We study the achievable rate of an uplink MIMO cognitive radio system where the primary user (PU) and the secondary user (SU) aim to communicate to the closest primary base station (BS) via a multi-access channel through the same unmanned aerial vehicle (UAV) relay. The SU message is then forwarded from the primary BS to the secondary network with a certain incentive reward as a part of the cooperation protocol between both networks. A special linear precoding scheme is proposed to enable the SU to exploit the PU free eigenmodes. We analyze two scenarios in which the UAV relay gain matrix is either fixed or optimized. We derive the optimal power allocation that maximizes the achievable rate of the SU respecting power budget, interference, and relay power constraints. Numerical results highlight the cognitive rate gain of our proposed scheme with respect to various problem parameters. We also highlight the effect of UAV altitude on the SU and PU rates. Finally, when the relay matrix is optimized, we show that the PU rate is remarkably enhanced and that the SU rate is only improved at high power regime.

A MICRO-UAV SYSTEM FOR FOREST MANAGEMENT

Directory of Open Access Journals (Sweden)

T. Hormigo

2013-08-01

Full Text Available Spin.Works has developed a complete micro-UAV system with the purpose of supporting forest management activities. The aircraft is based on a winged-body design spanning 1.8 m with a maximum take-off weight of 2 kg, and can carry out missions lasting up to 2 h at a cruise speed of about 60 km/h. The corresponding ground station ensures the mission planning functions, real-time flight monitoring and visualization, and serves also as a real-time and post-flight data exploitation platform. A particular emphasis is placed on image processing techniques applied to two operational concepts: a fire detection service and a forest mapping service. The real-time operations related to fire detection consist on object tracking and geo-referencing functions, which can be operated by a user directly over the video stream, enabling the quick estimation of the 3D location (latitude, longitude, altitude of suspected fires. The post-flight processing consists of extracting valuable knowledge from the payload data, in particular tree coverage maps, orthophoto mosaics and Digital Surface Models (DSMs, which can be used for further forest characterization such as wood and cork volume estimation. The system is currently entering initial operations, with expanded operations expected during Q3 2013.

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.

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

KAUST Repository

Sboui, Lokman

2017-07-20

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-access channel through the same UAV relay. The SU message is then forwarded from the primary BS to the secondary network with a certain incentive reward as a part of the cooperation protocol between both networks. We propose a special linear precoding scheme to enable the SU to exploit the PU free eigenmodes. We, also, present the expression of the power maximizing both primary and secondary rates under power budget, relay power, and interference constraints. In the numerical results, we evaluate the PU and SU rates of proposed scheme with respect to various problem parameters. We also highlight the effect of the UAV altitude on the SU and PU rates. Finally, we show that the relay matrix variation affects both rates that reach their peaks at different values of the matrix.

Short Communication. Using high resolution UAV imagery to estimate tree variables in Pinus pinea plantation in Portugal

Energy Technology Data Exchange (ETDEWEB)

Guerra Hernandez, J.; Gonzalez-Ferreiro, E.; Sarmento, A.; Silva, J.; Nunes, A.; Correia, A.C.; Fontes, L.; Tomé, M.; Diaz-Varela, D.

2016-07-01

Aim of the study: The study aims to analyse the potential use of low‑cost unmanned aerial vehicle (UAV) imagery for the estimation of Pinus pinea L. variables at the individual tree level (position, tree height and crown diameter). Area of study: This study was conducted under the PINEA project focused on 16 ha of umbrella pine afforestation (Portugal) subjected to different treatments. Material and methods: The workflow involved: a) image acquisition with consumer‑grade cameras on board an UAV; b) orthomosaic and digital surface model (DSM) generation using structure-from-motion (SfM) image reconstruction; and c) automatic individual tree segmentation by using a mixed pixel‑ and region‑based based algorithm. Main results: The results of individual tree segmentation (position, height and crown diameter) were validated using field measurements from 3 inventory plots in the study area. All the trees of the plots were correctly detected. The RMSE values for the predicted heights and crown widths were 0.45 m and 0.63 m, respectively. Research highlights: The results demonstrate that tree variables can be automatically extracted from high resolution imagery. We highlight the use of UAV systems as a fast, reliable and cost‑effective technique for small scale applications. (Author)

Short Communication. Using high resolution UAV imagery to estimate tree variables in Pinus pinea plantation in Portugal

International Nuclear Information System (INIS)

Guerra Hernandez, J.; Gonzalez-Ferreiro, E.; Sarmento, A.; Silva, J.; Nunes, A.; Correia, A.C.; Fontes, L.; Tomé, M.; Diaz-Varela, D.

2016-01-01

Aim of the study: The study aims to analyse the potential use of low‑cost unmanned aerial vehicle (UAV) imagery for the estimation of Pinus pinea L. variables at the individual tree level (position, tree height and crown diameter). Area of study: This study was conducted under the PINEA project focused on 16 ha of umbrella pine afforestation (Portugal) subjected to different treatments. Material and methods: The workflow involved: a) image acquisition with consumer‑grade cameras on board an UAV; b) orthomosaic and digital surface model (DSM) generation using structure-from-motion (SfM) image reconstruction; and c) automatic individual tree segmentation by using a mixed pixel‑ and region‑based based algorithm. Main results: The results of individual tree segmentation (position, height and crown diameter) were validated using field measurements from 3 inventory plots in the study area. All the trees of the plots were correctly detected. The RMSE values for the predicted heights and crown widths were 0.45 m and 0.63 m, respectively. Research highlights: The results demonstrate that tree variables can be automatically extracted from high resolution imagery. We highlight the use of UAV systems as a fast, reliable and cost‑effective technique for small scale applications. (Author)

Point Cloud Analysis for Uav-Borne Laser Scanning with Horizontally and Vertically Oriented Line Scanners - Concept and First Results

Science.gov (United States)

Weinmann, M.; Müller, M. S.; Hillemann, M.; Reydel, N.; Hinz, S.; Jutzi, B.

2017-08-01

In this paper, we focus on UAV-borne laser scanning with the objective of densely sampling object surfaces in the local surrounding of the UAV. In this regard, using a line scanner which scans along the vertical direction and perpendicular to the flight direction results in a point cloud with low point density if the UAV moves fast. Using a line scanner which scans along the horizontal direction only delivers data corresponding to the altitude of the UAV and thus a low scene coverage. For these reasons, we present a concept and a system for UAV-borne laser scanning using multiple line scanners. Our system consists of a quadcopter equipped with horizontally and vertically oriented line scanners. We demonstrate the capabilities of our system by presenting first results obtained for a flight within an outdoor scene. Thereby, we use a downsampling of the original point cloud and different neighborhood types to extract fundamental geometric features which in turn can be used for scene interpretation with respect to linear, planar or volumetric structures.

Indicator Species Population Monitoring in Antarctica with Uav

Science.gov (United States)

Zmarz, A.; Korczak-Abshire, M.; Storvold, R.; Rodzewicz, M.; Kędzierska, I.

2015-08-01

A program to monitor bird and pinniped species in the vicinity of Arctowski Station, King George Island, South Shetlands, Antarctica, has been conducted over the past 38 years. Annual monitoring of these indicator species includes estimations of breeding population sizes of three Pygoscelis penguin species: Adélie, gentoo and chinstrap. Six penguin colonies situated on the western shores of two bays: Admiralty and King George are investigated. To study changes in penguin populations Unmanned Aerial Vehicles were used for the first time in the 2014/15 austral summer season. During photogrammetric flights the high-resolution images of eight penguin breeding colonies were taken. Obtained high resolution images were used for estimation of breeding population size and compared with the results of measurements taken at the same time from the ground. During this Antarctic expedition eight successful photogrammetry missions (total distance 1500 km) were performed. Images were taken with digital SLR Canon 700D, Nikon D5300, Nikon D5100 with a 35mm objective lens. Flights altitude at 350 - 400 AGL, allowed images to be taken with a resolution GSD (ground sample distance) less than 5 cm. The Image J software analysis method was tested to provide automatic population estimates from obtained images. The use of UAV for monitoring of indicator species, enabled data acquisition from areas inaccessible by ground methods.

INDICATOR SPECIES POPULATION MONITORING IN ANTARCTICA WITH UAV

Directory of Open Access Journals (Sweden)

A. Zmarz

2015-08-01

Full Text Available A program to monitor bird and pinniped species in the vicinity of Arctowski Station, King George Island, South Shetlands, Antarctica, has been conducted over the past 38 years. Annual monitoring of these indicator species includes estimations of breeding population sizes of three Pygoscelis penguin species: Adélie, gentoo and chinstrap. Six penguin colonies situated on the western shores of two bays: Admiralty and King George are investigated. To study changes in penguin populations Unmanned Aerial Vehicles were used for the first time in the 2014/15 austral summer season. During photogrammetric flights the high-resolution images of eight penguin breeding colonies were taken. Obtained high resolution images were used for estimation of breeding population size and compared with the results of measurements taken at the same time from the ground. During this Antarctic expedition eight successful photogrammetry missions (total distance 1500 km were performed. Images were taken with digital SLR Canon 700D, Nikon D5300, Nikon D5100 with a 35mm objective lens. Flights altitude at 350 – 400 AGL, allowed images to be taken with a resolution GSD (ground sample distance less than 5 cm. The Image J software analysis method was tested to provide automatic population estimates from obtained images. The use of UAV for monitoring of indicator species, enabled data acquisition from areas inaccessible by ground methods.

Real-Time Autonomous Obstacle Avoidance for Low-Altitude Fixed-Wing Aircraft

Science.gov (United States)

Owlia, Shahboddin

The GeoSurv II is an Unmanned Aerial Vehicle (UAV) being developed by Carleton University and Sander Geophysics. This thesis is in support of the GeoSurv II project. The objective of the GeoSurv II project is to create a fully autonomous UAV capable of performing geophysical surveys. In order to achieve this level of autonomy, the UAV, which due to the nature of its surveys flies at low altitude, must be able to avoid potential obstacles such as trees, powerlines, telecommunication towers, etc. Developing a method to avoid these obstacles is the objective of this thesis. The literature is rich in methods for trajectory planning and mid-air collision avoidance with other aircraft. In contrast, in this thesis, a method for avoiding static obstacles that are not known a priori is developed. The potential flow theory and panel method are borrowed from fluid mechanics and are employed to generate evasive maneuvers when obstacles are encountered. By means of appropriate modelling of obstacles, the aircraft's constraints are taken into account such that the evasive maneuvers are feasible for the UAV. Moreover, the method is developed with consideration of the limitations of obstacle detection in GeoSurv II. Due to the unavailability of the GeoSurv II aircraft, and the lack of a complete model for GeoSurv II, the method developed is implemented on the non-linear model of the Aerosonde UAV. The Aerosonde model is then subjected to various obstacle scenarios and it is seen that the UAV successfully avoids the obstacles.

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.

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.

Efficiency calibration and minimum detectable activity concentration of a real-time UAV airborne sensor system with two gamma spectrometers

International Nuclear Information System (INIS)

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

2016-01-01

A small-sized UAV (NH-UAV) airborne system with two gamma spectrometers (LaBr_3 detector and HPGe detector) was developed to monitor activity concentration in serious nuclear accidents, such as the Fukushima nuclear accident. The efficiency calibration and determination of minimum detectable activity concentration (MDAC) of the specific system were studied by MC simulations at different flight altitudes, different horizontal distances from the detection position to the source term center and different source term sizes. Both air and ground radiation were considered in the models. The results obtained may provide instructive suggestions for in-situ radioactivity measurements of NH-UAV. - Highlights: • A small-sized UAV airborne sensor system was developed. • Three radioactive models were chosen to simulate the Fukushima accident. • Both the air and ground radiation were considered in the models. • The efficiency calculations and MDAC values were given. • The sensor system is able to monitor in serious nuclear accidents.

POINT CLOUD ANALYSIS FOR UAV-BORNE LASER SCANNING WITH HORIZONTALLY AND VERTICALLY ORIENTED LINE SCANNERS – CONCEPT AND FIRST RESULTS

Directory of Open Access Journals (Sweden)

M. Weinmann

2017-08-01

Full Text Available In this paper, we focus on UAV-borne laser scanning with the objective of densely sampling object surfaces in the local surrounding of the UAV. In this regard, using a line scanner which scans along the vertical direction and perpendicular to the flight direction results in a point cloud with low point density if the UAV moves fast. Using a line scanner which scans along the horizontal direction only delivers data corresponding to the altitude of the UAV and thus a low scene coverage. For these reasons, we present a concept and a system for UAV-borne laser scanning using multiple line scanners. Our system consists of a quadcopter equipped with horizontally and vertically oriented line scanners. We demonstrate the capabilities of our system by presenting first results obtained for a flight within an outdoor scene. Thereby, we use a downsampling of the original point cloud and different neighborhood types to extract fundamental geometric features which in turn can be used for scene interpretation with respect to linear, planar or volumetric structures.

ASSESMENT OF THE INFLUENCE OF UAV IMAGE QUALITY ON THE ORTHOPHOTO PRODUCTION

Directory of Open Access Journals (Sweden)

D. Wierzbicki

2015-08-01

Full Text Available Over the past years a noticeable increase of interest in using Unmanned Aerial Vehicles (UAV for acquiring low altitude images has been observed. This method creates new possibilities of using geodata captured from low altitudes to generate large scale orthophotos. Because of comparatively low costs, UAV aerial surveying systems find many applications in photogrammetry and remote sensing. One of the most significant problems with automation of processing of image data acquired with this method is its low accuracy. This paper presents the following stages of acquisition and processing of images collected in various weather and lighting conditions: aerotriangulation, generating of Digital Terrain Models (DTMs, orthorectification and mosaicking. In the research a compact, non-metric camera, mounted on a fuselage powered by an electric motor was used. The tested area covered flat, agricultural and woodland terrains. Aerotriangulation and point cloud accuracy as well as generated digital terrain model and mosaic exactness were examined. Dense multiple image matching was used as a benchmark. The processing and analysis were carried out with INPHO UASMaster programme. Based on performed accuracy analysis it was stated that images acquired in poor weather conditions (cloudy, precipitation degrade the final quality and accuracy of a photogrammetric product by an average of 25%.

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.

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.

Estimation of mean tree stand volume using high-resolution aerial RGB imagery and digital surface model, obtained from sUAV and Trestima mobile application

Directory of Open Access Journals (Sweden)

G. K. Rybakov

2017-06-01

Full Text Available This study considers a remote sensing technique for mean volume estimation based on a very high-resolution (VHR aerial RGB imagery obtained using a small-sized unmanned aerial vehicle (sUAV and a high-resolution photogrammetric digital surface model (DSM as well as an innovative technology for field measurements (Trestima. The study area covers approx. 220 ha of forestland in Finland. The work concerns the entire process from remote sensing and field data acquisition to statistical analysis and forest volume wall-to-wall mapping. The study showed that the VHR aerial imagery and the high-resolution DSM produced based on the application of the sUAV have good prospects for forest inventory. For the sUAV based estimation of forest variables such as Height, Basal Area and mean Volume, Root Mean Square Error constituted 6.6 %, 22.6 % and 26.7 %, respectively. Application of Trestima for estimation of the mean volume of the standing forest showed minor difference over the existing Forest Management Plan at all the selected forest compartments. Simultaneously, the results of the study confirmed that the technologies and the tools applied at this work could be a reliable and potentially cost-effective means of forest data acquisition with high potential of operational use.

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).

Implications of longitude and latitude on the size of solar-powered UAV

International Nuclear Information System (INIS)

Rajendran, Parvathy; Smith, Howard

2015-01-01

Highlights: • We studied solar irradiance and daylight implication on solar-powered UAV design. • We explored for perpetual UAV flight for 12 cities around the world. • All year round solar-powered UAV operation possible for cities near equatorial line. • Cities in latitudes of ±35° are the optimal for solar-powered UAV. • Longitudinal coordinates and elevation have a minor effect on UAV design. - Abstract: The implication of solar irradiance and daylight duration on the design of a small solar-powered unmanned aerial vehicle (UAV) that is capable of operating perpetually in various cities around the world was investigated. Solar data in 2013 on 12 cities distributed around the world was collected. The effects of the available solar irradiance and daylight of the city on the maximum take-off weight and wing span of a small solar-powered UAV were studied. The analysis indicates that daylight duration is as important as the available solar irradiance to the performance of the solar-powered UAV. Longitudinal coordinates and elevation have a minor effect on the estimation of daylight duration. Areas considerably high in solar irradiance and daylight duration are more conducive to the effective performance of solar-powered UAVs than other areas. Therefore, cities closer to the equator have an advantage in utilizing solar-powered UAVs; where smaller and lighter solar-powered UAV can be designed

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.

OBTAINING A PERMIT-TO-FLY FOR A HALE-UAV IN BELGIUM

Directory of Open Access Journals (Sweden)

J. Everaerts

2012-09-01

Full Text Available Ever since 2000, VITO has been working on the Pegasus project. This involves a solar High Altitude Long Endurance Unmanned Aerial Vehicle (HALE-UAV as a stratospheric platform for Earth Observation. This aircraft, called Mercator, is designed to fly for prolonged duration at altitudes up to 20 km. The technology has been proven by the aircraft’s manufacturer, QinetiQ (UK by a series of test flights over the past years, culminating in a world record flight in duration of over 14 days duration. All test flights, however, were conducted in test ranges, where other air traffic does not pose a concern. Pegasus aims to demonstrate the viability of stratospheric Earth Observation in Belgium, as a proof of concept for other areas around the world. The Belgian air space is completely different from a test range. More than 1 million aircraft movements take place over Belgium and Luxembourg every year, with routes to Amsterdam, Paris, Frankfurt, and London. Although Pegasus will usually be flying above this dense traffic, it does interfere with it during ascent and landing, and needs to be monitored during the cruise phase for safety reasons. Air traffic management in Belgium is a shared responsibility of Air Navigation Service Providers (ANSPs Belgocontrol (civil, ATCC (military and Eurocontrol MUAC (high altitude. In 2010, VITO applied for a permit-to-fly for a test flight of one day duration. Although the Belgian Civil Aviation Authority (CAA had issued a regulation on UAVs in 2007, it was the first application for a permit to fly in controlled airspace. The Belgian CAA decided to use it as a test for the procedures as well. A prerequisite for flying in controlled airspace was that the aircraft has to carry a mode-S transponder and navigation lights. During first half of 2010, the ANSPs collaborated on a Temporary Operations Instruction and studied the safety impact of this flight on their operations. As an outcome, they decided that the Pegasus

A comparative pressure analysis of air flow between horizontal and V-Tail of UAV MALE of NACA0012H with speed variation

OpenAIRE

Riza Rahmat; Kurniawan Dicky; Wicaksono Arif Budi

2018-01-01

NACA0012H is an airfoil type that could be used for Unmanned Aerial Vehicle Medium Altitude Long Endurance. This experiment was used to analyze stress in the surface of Tail of UAV MALE that was caused by air flow. The experiment was conducted using Computational Fluid Dynamics Software. Two designs of tail, horizontal and V-tail, were considered to simulate pressure occurred on the surface of leading edge, chamber and trailing edge. The simulation was developed varying the speed of the UAV M...

An adaptive dual-optimal path-planning technique for unmanned air vehicles with application to solar-regenerative high altitude long endurance flight

Science.gov (United States)

Whitfield, Clifford A.

2009-12-01

A multi-objective technique for Unmanned Air Vehicle (UAV) path and trajectory autonomy generation, through task allocation and sensor fusion has been developed. The Dual-Optimal Path-Planning (D-O.P-P.) Technique generates on-line adaptive flight paths for UAVs based on available flight windows and environmental influenced objectives. The environmental influenced optimal condition, known as the driver' determines the condition, within a downstream virtual window of possible vehicle destinations and orientation built from the UAV kinematics. The intermittent results are pursued by a dynamic optimization technique to determine the flight path. This sequential optimization technique is a multi-objective optimization procedure consisting of two goals, without requiring additional information to combine the conflicting objectives into a single-objective. An example case-study and additional applications are developed and the results are discussed; including the application to the field of Solar Regenerative (SR) High Altitude Long Endurance (HALE) UAV flight. Harnessing solar energy has recently been adapted for use on high altitude UAV platforms. An aircraft that uses solar panels and powered by the sun during the day and through the night by SR systems, in principle could sustain flight for weeks or months. The requirements and limitations of solar powered flight were determined. The SR-HALE UAV platform geometry and flight characteristics were selected from an existing aircraft that has demonstrated the capability for sustained flight through flight tests. The goals were to maintain continual Situational Awareness (SA) over a case-study selected Area of Interest (AOI) and existing UAV power and surveillance systems. This was done for still wind and constant wind conditions at altitude along with variations in latitude. The characteristics of solar flux and the dependence on the surface location and orientation were established along with fixed flight maneuvers for

Semiautonomous Avionics-and-Sensors System for a UAV

Science.gov (United States)

Shams, Qamar

2006-01-01

Unmanned Aerial Vehicles (UAVs) autonomous or remotely controlled pilotless aircraft have been recently thrust into the spotlight for military applications, for homeland security, and as test beds for research. In addition to these functions, there are many space applications in which lightweight, inexpensive, small UAVS can be used e.g., to determine the chemical composition and other qualities of the atmospheres of remote planets. Moreover, on Earth, such UAVs can be used to obtain information about weather in various regions; in particular, they can be used to analyze wide-band acoustic signals to aid in determining the complex dynamics of movement of hurricanes. The Advanced Sensors and Electronics group at Langley Research Center has developed an inexpensive, small, integrated avionics-and-sensors system to be installed in a UAV that serves two purposes. The first purpose is to provide flight data to an AI (Artificial Intelligence) controller as part of an autonomous flight-control system. The second purpose is to store data from a subsystem of distributed MEMS (microelectromechanical systems) sensors. Examples of these MEMS sensors include humidity, temperature, and acoustic sensors, plus chemical sensors for detecting various vapors and other gases in the environment. The critical sensors used for flight control are a differential- pressure sensor that is part of an apparatus for determining airspeed, an absolute-pressure sensor for determining altitude, three orthogonal accelerometers for determining tilt and acceleration, and three orthogonal angular-rate detectors (gyroscopes). By using these eight sensors, it is possible to determine the orientation, height, speed, and rates of roll, pitch, and yaw of the UAV. This avionics-and-sensors system is shown in the figure. During the last few years, there has been rapid growth and advancement in the technological disciplines of MEMS, of onboard artificial-intelligence systems, and of smaller, faster, and

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

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.

Solid oxide fuel cell/gas turbine hybrid system analysis for high-altitude long-endurance unmanned aerial vehicles

Energy Technology Data Exchange (ETDEWEB)

Aguiar, P.; Brandon, N.P. [Department of Earth Science and Engineering, Imperial College London, London SW7 2AZ (United Kingdom); Brett, D.J.L. [The Centre for CO{sub 2} Technology, University College London, London WC1E 7JE (United Kingdom)

2008-12-15

High-altitude long-endurance (HALE) unmanned aerial vehicles (UAVs) are ideally suited to provide surveillance, remote sensing and communication relay capabilities for both military and civilian applications. HALE UAVs typically cruise at an altitude between 15 km and 20 km, travelling at low speed and circling specific areas of interest. The work reported aims to investigate alternative power system architectures that enable an efficiency increase and consequent fuel consumption reduction to realise a one-week endurance target. Specifically, the application of a solid oxide fuel cell combined with a gas turbine is considered; with different system configurations modelled with a view to maximising overall efficiency. It is found that modularising the fuel cell capacity into a number of discrete stacks such that the fuel is distributed in parallel and air is fed in series results in an increased system efficiency compared with a single-stack design. An overall system efficiency of 66.3% (LHV) when operating on hydrogen is predicted for a three-stack system. (author)

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

Application of UAVs at the Savannah River Site

International Nuclear Information System (INIS)

Hofstetter, K.J.; Pendergast, M.M.

1996-01-01

Small, unmanned aerial vehicles (UAVs) equipped with sensors for physical, chemical, and radiochemical measurements of remote environments have been tested at the Savannah River Site (SRS). A miniature helicopter was used as an aerial platform for testing a variety of sensors with outputs integrated with the flight control system for real-time data acquisition and evaluation. The sensors included a precision magnetometer, two broad band infra-red radiometers, a 1-inch by 1-inch Nal(TI) scintillation detector, and an on-board color video camera. Included in the avionics package was an ultrasonic altimeter, a precision barometer, and a portable Global Positioning System. Two separate demonstration locations at SRS were flown that had been previously characterized by careful sampling and analyses and by aerial surveys at high altitudes. The Steed Pond demonstration site contains elevated levels of uranium in the soil and pond silt due to runoff from one of the site's uranium fuel and target production areas. The soil at the other site is contaminated with oil bearing materials and contains some buried objects. The results and limitations of the UAV surveys are presented and improvements for future measurements are discussed

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

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.

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.

Capabilities of unmanned aircraft vehicles for low altitude weed detection

Science.gov (United States)

Pflanz, Michael; Nordmeyer, Henning

2014-05-01

Sustainable crop production and food security require a consumer and environmental safe plant protection. It is recently known, that precise weed monitoring approaches could help apply pesticides corresponding to field variability. In this regard the site-specific weed management may contribute to an application of herbicides with higher ecologically aware and economical savings. First attempts of precision agriculture date back to the 1980's. Since that time, remote sensing from satellites or manned aircrafts have been investigated and used in agricultural practice, but are currently inadequate for the separation of weeds in an early growth stage from cultivated plants. In contrast, low-cost image capturing at low altitude from unmanned aircraft vehicles (UAV) provides higher spatial resolution and almost real-time processing. Particularly, rotary-wing aircrafts are suitable for precise path or stationary flight. This minimises motion blur and provides better image overlapping for stitching and mapping procedures. Through improved image analyses and the recent increase in the availability of microcontrollers and powerful batteries for UAVs, it can be expected that the spatial mapping of weeds will be enhanced in the future. A six rotors microcopter was equipped with a modified RGB camera taking images from agricultural fields. The hexacopter operates within predefined pathways at adjusted altitudes (from 5 to 10 m) by using GPS navigation. Different scenarios of optical weed detection have been carried out regarding to variable altitude, image resolution, weed and crop growth stages. Our experiences showed high capabilities for site-specific weed control. Image analyses with regard to recognition of weed patches can be used to adapt herbicide application to varying weed occurrence across a field.

UAV Control on the Basis of 3D Landmark Bearing-Only Observations.

Science.gov (United States)

Karpenko, Simon; Konovalenko, Ivan; Miller, Alexander; Miller, Boris; Nikolaev, Dmitry

2015-11-27

The article presents an approach to the control of a UAV on the basis of 3D landmark observations. The novelty of the work is the usage of the 3D RANSAC algorithm developed on the basis of the landmarks' position prediction with the aid of a modified Kalman-type filter. Modification of the filter based on the pseudo-measurements approach permits obtaining unbiased UAV position estimation with quadratic error characteristics. Modeling of UAV flight on the basis of the suggested algorithm shows good performance, even under significant external perturbations.

The application of micro UAV in construction project

Science.gov (United States)

Kaamin, Masiri; Razali, Siti Nooraiin Mohd; Ahmad, Nor Farah Atiqah; Bukari, Saifullizan Mohd; Ngadiman, Norhayati; Kadir, Aslila Abd; Hamid, Nor Baizura

2017-10-01

In every outstanding construction project, there is definitely have an effective construction management. Construction management allows a construction project to be implemented according to plan. Every construction project must have a progress development works that is usually created by the site engineer. Documenting the progress of works is one of the requirements in construction management. In a progress report it is necessarily have a visual image as an evidence. The conventional method used for photographing on the construction site is by using common digital camera which is has few setback comparing to Micro Unmanned Aerial Vehicles (UAV). Besides, site engineer always have a current issues involving limitation of monitoring on high reach point and entire view of the construction site. The purpose of this paper is to provide a concise review of Micro UAV technology in monitoring the progress on construction site through visualization approach. The aims of this study are to replace the conventional method of photographing on construction site using Micro UAV which can portray the whole view of the building, especially on high reach point and allows to produce better images, videos and 3D model and also facilitating site engineer to monitor works in progress. The Micro UAV was flown around the building construction according to the Ground Control Points (GCPs) to capture images and record videos. The images taken from Micro UAV have been processed generate 3D model and were analysed to visualize the building construction as well as monitoring the construction progress work and provides immediate reliable data for project estimation. It has been proven that by using Micro UAV, a better images and videos can give a better overview of the construction site and monitor any defects on high reach point building structures. Not to be forgotten, with Micro UAV the construction site progress is more efficiently tracked and kept on the schedule.

Unmanned air vehicle (UAV) ultra-persitence research

Energy Technology Data Exchange (ETDEWEB)

Dron, S. B.

2012-03-01

Sandia National Laboratories and Northrop Grumman Corporation Integrated Systems, Unmanned Systems (NGIS UMS) collaborated to further ultra-persistence technologies for unmanned air vehicles (UAVs). The greatest shortfalls in UAV capabilities have been repeatedly identified as (1) insufficient flight persistence or 'hang time,' (2) marginal electrical power for running higher power avionics and payload systems, and (3) inadequate communications bandwidth and reach. NGIS UMS requested support from Sandia to develop an ultra-persistent propulsion and power system (UP3S) for potential incorporation into next generation UAV systems. The team members tried to determine which energy storage and power generation concepts could most effectively push UAV propulsion and electrical power capabilities to increase UAV sortie duration from days to months while increasing available electrical power at least two-fold. Primary research and development areas that were pursued included these goals: perform general system engineering and integration analyses; develop initial thermal and electrical power estimates; provide mass, volume, dimensional, and balance estimates; conduct preliminary safety assessments; assess logistics support requirements; perform, preliminary assessments of any security and safeguards; evaluate options for removal, replacement, and disposition of materials; generally advance the potential of the UP3S concept. The effort contrasted and compared eight heat sources technologies, three power conversion, two dual cycle propulsion system configurations, and a single electrical power generation scheme. Overall performance, specific power parameters, technical complexities, security, safety, and other operational features were successfully investigated. Large and medium sized UAV systems were envisioned and operational flight profiles were developed for each concept. Heat source creation and support challenges for domestic and expeditionary operations were

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...

Research on the Application of Rapid Surveying and Mapping for Large Scare Topographic Map by Uav Aerial Photography System

Science.gov (United States)

Gao, Z.; Song, Y.; Li, C.; Zeng, F.; Wang, F.

2017-08-01

Rapid acquisition and processing method of large scale topographic map data, which relies on the Unmanned Aerial Vehicle (UAV) low-altitude aerial photogrammetry system, is studied in this paper, elaborating the main work flow. Key technologies of UAV photograph mapping is also studied, developing a rapid mapping system based on electronic plate mapping system, thus changing the traditional mapping mode and greatly improving the efficiency of the mapping. Production test and achievement precision evaluation of Digital Orth photo Map (DOM), Digital Line Graphic (DLG) and other digital production were carried out combined with the city basic topographic map update project, which provides a new techniques for large scale rapid surveying and has obvious technical advantage and good application prospect.

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.

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

Performance evaluation of optical channel transmission between UAVs and Ground Stations

Directory of Open Access Journals (Sweden)

Hatziefremidis Antonis

2016-01-01

Full Text Available Free space optical (FSO communications links is a promising solution for the provision of high data rate point to point communications. In particular deploying FSO technology for mobile links between Unmanned Aerial Vehicles (UAVs and fixed Ground Stations (GS introduces several interesting challenges. In this paper, we investigate the ability of a mobile FSO system to operate in different atmospheric conditions. Specifically, we characterize the quality of the optical channel with a proper model in terms of Bit Error Rate (BER and average Signal to Noise Ratio (SNR and we report a detailed optical amplification model able to support a constant Quality of Service for different distances from 1 km up to 35 km at 10 Gbps with 1550 nm wavelength. An extensive comparative analysis among different FSO configurations links considering the altitude of the UAV, the wavelength and the atmospheric conditions is provided. The results show that there is degradation at the BER over a slanted path compared to a horizontal path at the same conditions.

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.

Hurricane Harvey Building Damage Assessment Using UAV Data

Science.gov (United States)

Yeom, J.; Jung, J.; Chang, A.; Choi, I.

2017-12-01

Hurricane Harvey which was extremely destructive major hurricane struck southern Texas, U.S.A on August 25, causing catastrophic flooding and storm damages. We visited Rockport suffered severe building destruction and conducted UAV (Unmanned Aerial Vehicle) surveying for building damage assessment. UAV provides very high resolution images compared with traditional remote sensing data. In addition, prompt and cost-effective damage assessment can be performed regardless of several limitations in other remote sensing platforms such as revisit interval of satellite platforms, complicated flight plan in aerial surveying, and cloud amounts. In this study, UAV flight and GPS surveying were conducted two weeks after hurricane damage to generate an orthomosaic image and a DEM (Digital Elevation Model). 3D region growing scheme has been proposed to quantitatively estimate building damages considering building debris' elevation change and spectral difference. The result showed that the proposed method can be used for high definition building damage assessment in a time- and cost-effective way.

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.

A comparative pressure analysis of air flow between horizontal and V-Tail of UAV MALE of NACA0012H with speed variation

Directory of Open Access Journals (Sweden)

Riza Rahmat

2018-01-01

Full Text Available NACA0012H is an airfoil type that could be used for Unmanned Aerial Vehicle Medium Altitude Long Endurance. This experiment was used to analyze stress in the surface of Tail of UAV MALE that was caused by air flow. The experiment was conducted using Computational Fluid Dynamics Software. Two designs of tail, horizontal and V-tail, were considered to simulate pressure occurred on the surface of leading edge, chamber and trailing edge. The simulation was developed varying the speed of the UAV MALE. The results showed that pressure occurred on the surface of horizontal tail higher than pressure on the V-tail.

Hemoglobin correction factors for estimating the prevalence of iron deficiency anemia in pregnant women residing at high altitudes in Bolivia

Directory of Open Access Journals (Sweden)

Jennifer Hadary Cohen

1999-12-01

Full Text Available This study had two primary objectives: 1 to derive a method to determine hemoglobin cutoffs that could be used to better estimate the prevalence of iron deficiency anemia in pregnancy at high altitudes and 2 to estimate the prevalence of anemia in a sample of pregnant women residing in two cities in Bolivia, La Paz (3 600 meters and El Alto (4 000 meters. We derived a hemoglobin-altitude curve from previously published data on the mean hemoglobin concentrations of nonanemic women of childbearing age at various altitudes. In addition, we abstracted data on hemoglobin concentration during pregnancy from medical records of women from La Paz and El Alto who had given birth at a maternity hospital in La Paz between January and June of 1996. Using our approach and two other previously published, currently used methods, we calculated and compared prevalences of iron deficiency anemia in this population using hemoglobin cutoffs determined from a hemoglobin-altitude curve corrected for pregnancy. The hemoglobin-altitude curve derived in this study provided a better fit to data for women of childbearing age than the two other models. Those models used cutoffs based on non-iron-replete populations of children or men, both of which were residing below 4 000 m, and then extrapolated to women and higher altitudes. The estimated prevalences of iron deficiency anemia in pregnancy using the hemoglobin cutoffs determined in this study were higher than those estimated by the two other approaches.

Cooperative Search by UAV Teams: A Model Predictive Approach Using Dynamic Graphs

Science.gov (United States)

2011-10-01

Consequently , target estimation is a challenging problem and a rich field of study in itself. We refer the reader to [1] and [11] for a deeper analysis of...decentralized processing and control architecture. SLAMEM asset models accurately represent the Unicorn UAV platforms and other standard military platforms in...IMPLEMENTATION The CGBMPS algorithm has been successfully field-tested using both Unicorn [27] and Raven [20] UAV platforms. This section describes

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

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.

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.

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

The Analysis of Burrows Recognition Accuracy in XINJIANG'S Pasture Area Based on Uav Visible Images with Different Spatial Resolution

Science.gov (United States)

Sun, D.; Zheng, J. H.; Ma, T.; Chen, J. J.; Li, X.

2018-04-01

The rodent disaster is one of the main biological disasters in grassland in northern Xinjiang. The eating and digging behaviors will cause the destruction of ground vegetation, which seriously affected the development of animal husbandry and grassland ecological security. UAV low altitude remote sensing, as an emerging technique with high spatial resolution, can effectively recognize the burrows. However, how to select the appropriate spatial resolution to monitor the calamity of the rodent disaster is the first problem we need to pay attention to. The purpose of this study is to explore the optimal spatial scale on identification of the burrows by evaluating the impact of different spatial resolution for the burrows identification accuracy. In this study, we shoot burrows from different flight heights to obtain visible images of different spatial resolution. Then an object-oriented method is used to identify the caves, and we also evaluate the accuracy of the classification. We found that the highest classification accuracy of holes, the average has reached more than 80 %. At the altitude of 24 m and the spatial resolution of 1cm, the accuracy of the classification is the highest We have created a unique and effective way to identify burrows by using UAVs visible images. We draw the following conclusion: the best spatial resolution of burrows recognition is 1 cm using DJI PHANTOM-3 UAV, and the improvement of spatial resolution does not necessarily lead to the improvement of classification accuracy. This study lays the foundation for future research and can be extended to similar studies elsewhere.

Assessing Optimal Flight Parameters for Generating Accurate Multispectral Orthomosaicks by UAV to Support Site-Specific Crop Management

Directory of Open Access Journals (Sweden)

Francisco-Javier Mesas-Carrascosa

2015-09-01

Full Text Available This article describes the technical specifications and configuration of a multirotor unmanned aerial vehicle (UAV to acquire remote images using a six-band multispectral sensor. Several flight missions were programmed as follows: three flight altitudes (60, 80 and 100 m, two flight modes (stop and cruising modes and two ground control point (GCP settings were considered to analyze the influence of these parameters on the spatial resolution and spectral discrimination of multispectral orthomosaicked images obtained using Pix4Dmapper. Moreover, it is also necessary to consider the area to be covered or the flight duration according to any flight mission programmed. The effect of the combination of all these parameters on the spatial resolution and spectral discrimination of the orthomosaicks is presented. Spectral discrimination has been evaluated for a specific agronomical purpose: to use the UAV remote images for the detection of bare soil and vegetation (crop and weeds for in-season site-specific weed management. These results show that a balance between spatial resolution and spectral discrimination is needed to optimize the mission planning and image processing to achieve   every agronomic objective. In this way, users do not have to sacrifice flying at low altitudes to cover the whole area of interest completely.

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.

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.

UAV Remote Sensing for Urban Vegetation Mapping Using Random Forest and Texture Analysis

Directory of Open Access Journals (Sweden)

Quanlong Feng

2015-01-01

Full Text Available Unmanned aerial vehicle (UAV remote sensing has great potential for vegetation mapping in complex urban landscapes due to the ultra-high resolution imagery acquired at low altitudes. Because of payload capacity restrictions, off-the-shelf digital cameras are widely used on medium and small sized UAVs. The limitation of low spectral resolution in digital cameras for vegetation mapping can be reduced by incorporating texture features and robust classifiers. Random Forest has been widely used in satellite remote sensing applications, but its usage in UAV image classification has not been well documented. The objectives of this paper were to propose a hybrid method using Random Forest and texture analysis to accurately differentiate land covers of urban vegetated areas, and analyze how classification accuracy changes with texture window size. Six least correlated second-order texture measures were calculated at nine different window sizes and added to original Red-Green-Blue (RGB images as ancillary data. A Random Forest classifier consisting of 200 decision trees was used for classification in the spectral-textural feature space. Results indicated the following: (1 Random Forest outperformed traditional Maximum Likelihood classifier and showed similar performance to object-based image analysis in urban vegetation classification; (2 the inclusion of texture features improved classification accuracy significantly; (3 classification accuracy followed an inverted U relationship with texture window size. The results demonstrate that UAV provides an efficient and ideal platform for urban vegetation mapping. The hybrid method proposed in this paper shows good performance in differentiating urban vegetation mapping. The drawbacks of off-the-shelf digital cameras can be reduced by adopting Random Forest and texture analysis at the same time.

Output Feedback Tracking Control of an Underactuated Quad-Rotor UAV

National Research Council Canada - National Science Library

Lee, DongBin; Burg, Timothy; Xian, Bin; Dawson, Darren

2006-01-01

...) using output feedback (OFB). Specifically, an observer is designed to estimate the velocities and an output feedback controller is designed for a nonlinear UAV system in which only position and angles are measurable...

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.

UAV Swarm Operational Risk Assessment System

Science.gov (United States)

2015-09-01

are detected, clear monitoring is required to track and identify the possible intentions of inbound UAVs. And when a target is identified, enough...armed UAVs (Davis et al. 2014). Although manufacturers in the U.S. and Israel dominate the global UAV market (approximately 75 percent share between

Direct Georeferencing of a Pushbroom, Lightweight Hyperspectral System for Mini-UAV Applications

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Marion Jaud

2018-01-01

Full Text Available Hyperspectral imagery has proven its potential in many research applications, especially in the field of environmental sciences. Currently, hyperspectral imaging is generally performed by satellite or aircraft platforms, but mini-UAV (Unmanned Aerial Vehicle platforms (<20 kg are now emerging. On such platforms, payload restrictions are critical, so sensors must be selected according to stringent specifications. This article presents the integration of a light pushbroom hyperspectral sensor onboard a multirotor UAV, which we have called Hyper-DRELIO (Hyperspectral DRone for Environmental and LIttoral Observations. This article depicts the system design: the UAV platform, the imaging module, the navigation module, and the interfacing between the different elements. Pushbroom sensors offer a better combination of spatial and spectral resolution than full-frame cameras. Nevertheless, data georectification has to be performed line by line, the quality of direct georeferencing being limited by mechanical stability, good timing accuracy, and the resolution and accuracy of the proprioceptive sensors. A georegistration procedure is proposed for geometrical pre-processing of hyperspectral data. The specifications of Hyper-DRELIO surveys are described through two examples of surveys above coastal or inland waters, with different flight altitudes. This system can collect hyperspectral data in VNIR (Visible and Near InfraRed domain above small study sites (up to about 4 ha with both high spatial resolution (<10 cm and high spectral resolution (1.85 nm and with georectification accuracy on the order of 1 to 2 m.

UAV survey of a Thyrrenian micro-tidal beach for shoreline evolution update

Science.gov (United States)

Benassai, Guido; Pugliano, Giovanni; Di Paola, Gianluigi; Mucerino, Luigi

2015-04-01

Coastal geomorphology requires increasingly accurate topographic information of the beach systems to perform reliable simulation of coastal erosion, flooding phenomena, and coastal vulnerability assessment. Among the range of terrestrial and aerial methods available to produce such a dataset, this study tests the utility of low-altitude aerial imageries collected by Unmanned Aerial Vehicle (UAV). The 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 high-resolution Digital Surface Model (DSM) of the micro-tidal beach of Serapo - Gaeta (LT) in order to obtain recent update of erosional/accretional trends already established through historical shoreline evolution. A UAV exacopter (fig. 1a) was used, weighing about 2500g, carrying on board a GPS and multi-directional accelerometer to ensure a recovery of the beach features (fig. 1b) through a sweep with constant speed, direction and altitude. The on-board camera was a Canon 16M pixels, with fixed and constant focal takeoff in order to perform the 3D cloud points. Six adjacent strips were performed for the survey realization with pictures taken every second in sequence, in order to allow a minimum 80% overlap. A direct on site survey was also carried out with a DGPS for the placement of GPS markers and the geo-referencing of the final product (fig. 1c). Each flight with constant speed, direction and altitude recorded from 500 to 800 shots. The height of flight was dictated by the scale of the final report, an altitude of 100m was used for the beach survey. The topographic survey on the ground for the placement of the control points was performed with the Trimble R6 DGPS in RTK mode. The long-term shoreline evolution was obtained by a sixty-year historical shoreline time-series, through the analysis of a number of aerial photographs dating from 1954 to 2013. The

DOA Estimation of Low Altitude Target Based on Adaptive Step Glowworm Swarm Optimization-multiple Signal Classification Algorithm

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Zhou Hao

2015-06-01

Full Text Available The traditional MUltiple SIgnal Classification (MUSIC algorithm requires significant computational effort and can not be employed for the Direction Of Arrival (DOA estimation of targets in a low-altitude multipath environment. As such, a novel MUSIC approach is proposed on the basis of the algorithm of Adaptive Step Glowworm Swarm Optimization (ASGSO. The virtual spatial smoothing of the matrix formed by each snapshot is used to realize the decorrelation of the multipath signal and the establishment of a fullorder correlation matrix. ASGSO optimizes the function and estimates the elevation of the target. The simulation results suggest that the proposed method can overcome the low altitude multipath effect and estimate the DOA of target readily and precisely without radar effective aperture loss.

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

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

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

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

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.

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.

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.

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

Visual navigation of the UAVs on the basis of 3D natural landmarks

Science.gov (United States)

Karpenko, Simon; Konovalenko, Ivan; Miller, Alexander; Miller, Boris; Nikolaev, Dmitry

2015-12-01

This work considers the tracking of the UAV (unmanned aviation vehicle) on the basis of onboard observations of natural landmarks including azimuth and elevation angles. It is assumed that UAV's cameras are able to capture the angular position of reference points and to measure the angles of the sight line. Such measurements involve the real position of UAV in implicit form, and therefore some of nonlinear filters such as Extended Kalman filter (EKF) or others must be used in order to implement these measurements for UAV control. Recently it was shown that modified pseudomeasurement method may be used to control UAV on the basis of the observation of reference points assigned along the UAV path in advance. However, the use of such set of points needs the cumbersome recognition procedure with the huge volume of on-board memory. The natural landmarks serving as such reference points which may be determined on-line can significantly reduce the on-board memory and the computational difficulties. The principal difference of this work is the usage of the 3D reference points coordinates which permits to determine the position of the UAV more precisely and thereby to guide along the path with higher accuracy which is extremely important for successful performance of the autonomous missions. The article suggests the new RANSAC for ISOMETRY algorithm and the use of recently developed estimation and control algorithms for tracking of given reference path under external perturbation and noised angular measurements.

Unmanned Aerial Vehicles unique cost estimating requirements

Science.gov (United States)

Malone, P.; Apgar, H.; Stukes, S.; Sterk, S.

Unmanned Aerial Vehicles (UAVs), also referred to as drones, are aerial platforms that fly without a human pilot onboard. UAVs are controlled autonomously by a computer in the vehicle or under the remote control of a pilot stationed at a fixed ground location. There are a wide variety of drone shapes, sizes, configurations, complexities, and characteristics. Use of these devices by the Department of Defense (DoD), NASA, civil and commercial organizations continues to grow. UAVs are commonly used for intelligence, surveillance, reconnaissance (ISR). They are also use for combat operations, and civil applications, such as firefighting, non-military security work, surveillance of infrastructure (e.g. pipelines, power lines and country borders). UAVs are often preferred for missions that require sustained persistence (over 4 hours in duration), or are “ too dangerous, dull or dirty” for manned aircraft. Moreover, they can offer significant acquisition and operations cost savings over traditional manned aircraft. Because of these unique characteristics and missions, UAV estimates require some unique estimating methods. This paper describes a framework for estimating UAV systems total ownership cost including hardware components, software design, and operations. The challenge of collecting data, testing the sensitivities of cost drivers, and creating cost estimating relationships (CERs) for each key work breakdown structure (WBS) element is discussed. The autonomous operation of UAVs is especially challenging from a software perspective.

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...

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.

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.

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%.

Wind and Wake Sensing with UAV Formation Flight: System Development and Flight Testing

Science.gov (United States)

Larrabee, Trenton Jameson

Wind turbulence including atmospheric turbulence and wake turbulence have been widely investigated; however, only recently it become possible to use Unmanned Aerial Vehicles (UAVs) as a validation tool for research in this area. Wind can be a major contributing factor of adverse weather for aircraft. More importantly, it is an even greater risk towards UAVs because of their small size and weight. Being able to estimate wind fields and gusts can potentially provide substantial benefits for both unmanned and manned aviation. Possible applications include gust suppression for improving handling qualities, a better warning system for high wind encounters, and enhanced control for small UAVs during flight. On the other hand, the existence of wind can be advantageous since it can lead to fuel savings and longer duration flights through dynamic soaring or thermal soaring. Wakes are an effect of the lift distribution across an aircraft's wing or tail. Wakes can cause substantial disturbances when multiple aircraft are moving through the same airspace. In fact, the perils from an aircraft flying through the wake of another aircraft is a leading cause of the delay between takeoff times at airports. Similar to wind, though, wakes can be useful for energy harvesting and increasing an aircraft's endurance when flying in formation which can be a great advantage to UAVs because they are often limited in flight time due to small payload capacity. Formation flight can most often be seen in manned aircraft but can be adopted for use with unmanned systems. Autonomous flight is needed for flying in the "sweet spot" of the generated wakes for energy harvesting as well as for thermal soaring during long duration flights. For the research presented here formation flight was implemented for the study of wake sensing and gust alleviation. The major contributions of this research are in the areas of a novel technique to estimate wind using an Unscented Kalman filter and experimental wake

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.

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.

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.

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.

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

Observing Crop-Height Dynamics Using a UAV

Science.gov (United States)

Ziliani, M. G.; Parkes, S. D.; McCabe, M.

2017-12-01

Retrieval of vegetation height during a growing season is a key indicator for monitoring crop status, offering insight to the forecast yield relative to previous planting cycles. Improvement in Unmanned Aerial Vehicle (UAV) technologies, supported by advances in computer vision and photogrammetry software, has enabled retrieval of crop heights with much higher spatial resolution and coverage. These methodologies retrieve a Digital Surface Map (DSM), which combine terrain and crop elements to obtain a Crop Surface Map (CSM). Here we describe an automated method for deriving high resolution CSMs from a DSM, using RGB imagery from a UAV platform. Importantly, the approach does not require the need for a digital terrain map (DTM). The method involves distinguishing between vegetation and bare-ground cover pixels, using vegetation index maps from the RGB orthomosaic derived from the same flight as the DSM. We show that the absolute crop height can be extracted to within several centimeters, exploiting the data captured from a single UAV flight. In addition, the method is applied across five surveys during a maize growing cycle and compared against a terrain map constructed from a baseline UAV survey undertaken prior to crop growth. Results show that the approach is able to reproduce the observed spatial variability of the crop height within the maize field throughout the duration of the growing season. This is particularly valuable since it may be employed to detect intra-field problems (i.e. fertilizer variability, inefficiency in the irrigation system, salinity etc.) at different stages of the season, from which remedial action can be initiated to mitigate against yield loss. The method also demonstrates that UAV imagery combined with commercial photogrammetry software can determine a CSM from a single flight without the requirement of a prior DTM. This, together with the dynamic crop height estimation, provide useful information with which to inform precision

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.

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.

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

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.

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

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.

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

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.

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....

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.

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

Design of UAV (Diseño de un UAV)

OpenAIRE

Sacristán Estévez, José María

2016-01-01

En este proyecto se ha diseñado un dron, un vehículo aéreo no tripulado (UAV en sus siglas inglesas). El propósito de este proyecto es empezar el diseño desde cero hasta poder vender el dron y que sea rentable. Han sido calculados los parámetros necesarios para comenzar el diseño. Se ha comprobado si todas las partes del UAV son capaces de resistir un impacto contra el suelo durante su uso, y se ha buscado la forma más óptima de conseguir los materiales, así de cómo fabricar ciertas partes y ...

Collaborative UAV Exploration of Hostile Environments

National Research Council Canada - National Science Library

Luotsinen, Linus J; Gonzalez, Avelino J; Boeloeni, Ladislau

2004-01-01

.... UAVs can be lost or significantly damaged during the exploration process. Although employing multiple UAVs can increase the chance of success, their efficiency depends on the collaboration strategies used...

The Channel Estimation and Modeling in High Altitude Platform Station Wireless Communication Dynamic Network

Directory of Open Access Journals (Sweden)

Xiaoyang Liu

2017-01-01

Full Text Available In order to analyze the channel estimation performance of near space high altitude platform station (HAPS in wireless communication system, the structure and formation of HAPS are studied in this paper. The traditional Least Squares (LS channel estimation method and Singular Value Decomposition-Linear Minimum Mean-Squared (SVD-LMMS channel estimation method are compared and investigated. A novel channel estimation method and model are proposed. The channel estimation performance of HAPS is studied deeply. The simulation and theoretical analysis results show that the performance of the proposed method is better than the traditional methods. The lower Bit Error Rate (BER and higher Signal Noise Ratio (SNR can be obtained by the proposed method compared with the LS and SVD-LMMS methods.

Radio Channel Modelling for UAV Communication over Cellular Networks

DEFF Research Database (Denmark)

Amorim, Rafhael Medeiros de; Nguyen, Huan Cong; Mogensen, Preben Elgaard

2017-01-01

a commercial UAV. Our results show that path loss exponents decrease as the UAV moves up, approximating freespace propagation for horizontal ranges up to tens of kilometers at UAV heights around 100m. Our findings support the need of heightdependent parameters for describing the propagation channel for UAVs...

The Way Ahead For Maritime UAVS

National Research Council Canada - National Science Library

Pearson , II, F. C

2006-01-01

.... There is an overarching USN plan for UAVs, but I propose an emphasis should be placed on the close range or tactical UAVs that will directly complement battle space management, increase situational...

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.

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.

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.

Applications of UAVs to Measurement and Monitoring of Anthropogenic Contamination of an Urban Wildlife Preserve

Science.gov (United States)

Higa, E.; Valencia, D.; Hunt, A.

2017-12-01

Over the past decade, the use of unmanned aerial vehicles (UAV's) has seen unprecedented growth in diverse research areas due to advances in UAV hardware and reduced total operating costs. These developments have given environmental investigators a new aerial data acquisition technique that can be used to not only survey large areas of terrain in a time-efficient and cost-effective manner but can be used to gather previously almost unattainable air quality data. Vertically resolved profiles of air pollutant data can be readily constructed. This project's goal is to produce a time resolved (seasonal) aerial survey of a 150-acre section from a 1300-acre ecologically diverse park of bottomland forests, wetlands and prairies. This ecosystem provides abundant habitats for a diverse wildlife community. This section was chosen due to its close proximity to the city landfill located 0.5 miles due north from the chosen section. The process of collecting UAV aerial images at a constant altitude of ( 200ft) on a bi-monthly basis (for a period of 6 months) has commenced. The UAV has been fitted with a custom made mount to secure an Ultrafine Particle (UFP) counter; this is providing information on UFP levels over the study area as a proxy for airborne particle inputs to the site. Sediment samples will be taken from several runoff ponds within the survey area to evaluate possible anthropogenic contamination of the park . Post processing imaging software, DroneDeploy, is being used to create an orthomosaic, topographic surface and 3D model that can be integrated with GIS platforms to create a comprehensive and cohesive multi-layered data set. Data sets of this nature will provide information on temporally constrained sources of runoff material to the pond areas in the preserve.

Stereo Vision Guiding for the Autonomous Landing of Fixed-Wing UAVs: A Saliency-Inspired Approach

Directory of Open Access Journals (Sweden)

Zhaowei Ma

2016-03-01

Full Text Available It is an important criterion for unmanned aerial vehicles (UAVs to land on the runway safely. This paper concentrates on stereo vision localization of a fixed-wing UAV's autonomous landing within global navigation satellite system (GNSS denied environments. A ground stereo vision guidance system imitating the human visual system (HVS is presented for the autonomous landing of fixed-wing UAVs. A saliency-inspired algorithm is presented and developed to detect flying UAV targets in captured sequential images. Furthermore, an extended Kalman filter (EKF based state estimation is employed to reduce localization errors caused by measurement errors of object detection and pan-tilt unit (PTU attitudes. Finally, stereo-vision-dataset-based experiments are conducted to verify the effectiveness of the proposed visual detection method and error correction algorithm. The compared results between the visual guidance approach and differential GPS-based approach indicate that the stereo vision system and detection method can achieve the better guiding effect.

Air Force UAVs: The Secret History

Science.gov (United States)

2010-07-01

iA Mitchell Institute Study i Air Force UAVs The Secret History A Mitchell Institute Study July 2010 By Thomas P. Ehrhard Report Documentation Page...DATES COVERED 00-00-2010 to 00-00-2010 4. TITLE AND SUBTITLE Air Force UAVs The Secret History 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c...opening phases of Operation Enduring Freedom in Afghanistan. By Thomas P. Ehrhard a miTchEll insTiTuTE sTudy July 2010 Air Force UAVs The Secret History

Review of the Current State of UAV Regulations

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Claudia Stöcker

2017-05-01

Full Text Available 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 importance, impact, and diversity of UAV regulations, this paper provides an exploratory investigation of UAV regulations on the global scale. For this, the methodological approach consists of a research synthesis of UAV regulations, including a thorough literature review and a comparative analysis of national regulatory frameworks. Similarities and contrasting elements in the various national UAV regulations are explored including their statuses from the perspectives of past, present, and future trends. Since the early 2000s, countries have gradually established national legal frameworks. Although all UAV regulations have one common goal—minimizing the risks to other airspace users and to both people and property on the ground—the results reveal distinct variations in all the compared variables. Furthermore, besides the clear presence of legal frameworks, market forces such as industry design standards and reliable information about UAVs as public goods are expected to shape future developments.

Flight safety measurements of UAVs in congested airspace

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Xiang Jinwu

2016-10-01

Full Text Available Describing spatial safety status is crucial for high-density air traffic involving multiple unmanned aerial vehicles (UAVs in a complex environment. A probabilistic approach is proposed to measure safety situation in congested airspace. The occupancy distribution of the airspace is represented with conflict probability between spatial positions and UAV. The concept of a safety envelope related to flight performance and response time is presented first instead of the conventional fixed-size protected zones around aircraft. Consequently, the conflict probability is performance-dependent, and effects of various UAVs on safety can be distinguished. The uncertainty of a UAV future position is explicitly accounted for as Brownian motion. An analytic approximate algorithm for the conflict probability is developed to decrease the computational consumption. The relationship between safety and flight performance are discussed for different response times and prediction intervals. To illustrate the applications of the approach, an experiment of three UAVs in formation flight is performed. In addition, an example of trajectory planning is simulated for one UAV flying over airspace where five UAVs exist. The validation of the approach shows its potential in guaranteeing flight safety in highly dynamic environment.

Air Force UAV’s: The Secret History

Science.gov (United States)

2010-07-01

iA Mitchell Institute Study i Air Force UAVs The Secret History A Mitchell Institute Study July 2010 By Thomas P. Ehrhard Report Documentation Page...DATES COVERED 00-00-2010 to 00-00-2010 4. TITLE AND SUBTITLE Air Force UAVs The Secret History 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c... The Secret History 2 Air Force UAVs: The Secret History2 air Force uaVs: The secret history Has any airplane in the past decade captured the public

Parametric analysis of a down-scaled turbo jet engine suitable for drone and UAV propulsion

Science.gov (United States)

Wessley, G. Jims John; Chauhan, Swati

2018-04-01

This paper presents a detailed study on the need for downscaling gas turbine engines for UAV and drone propulsion. Also, the procedure for downscaling and the parametric analysis of a downscaled engine using Gas Turbine Simulation Program software GSP 11 is presented. The need for identifying a micro gas turbine engine in the thrust range of 0.13 to 4.45 kN to power UAVs and drones weighing in the range of 4.5 to 25 kg is considered and in order to meet the requirement a parametric analysis on the scaled down Allison J33-A-35 Turbojet engine is performed. It is evident from the analysis that the thrust developed by the scaled engine and the Thrust Specific Fuel Consumption TSFC depends on pressure ratio, mass flow rate of air and Mach number. A scaling factor of 0.195 corresponding to air mass flow rate of 7.69 kg/s produces a thrust in the range of 4.57 to 5.6 kN while operating at a Mach number of 0.3 within the altitude of 5000 to 9000 m. The thermal and overall efficiency of the scaled engine is found to be 67% and 75% respectively for a pressure ratio of 2. The outcomes of this analysis form a strong base for further analysis, design and fabrication of micro gas turbine engines to propel future UAVs and drones.

Robust drone detection for day/night counter-UAV with static VIS and SWIR cameras

Science.gov (United States)

Müller, Thomas

2017-05-01

Recent progress in the development of unmanned aerial vehicles (UAVs) has led to more and more situations in which drones like quadrocopters or octocopters pose a potential serious thread or could be used as a powerful tool for illegal activities. Therefore, counter-UAV systems are required in a lot of applications to detect approaching drones as early as possible. In this paper, an efficient and robust algorithm is presented for UAV detection using static VIS and SWIR cameras. Whereas VIS cameras with a high resolution enable to detect UAVs in the daytime in further distances, surveillance at night can be performed with a SWIR camera. First, a background estimation and structural adaptive change detection process detects movements and other changes in the observed scene. Afterwards, the local density of changes is computed used for background density learning and to build up the foreground model which are compared in order to finally get the UAV alarm result. The density model is used to filter out noise effects, on the one hand. On the other hand, moving scene parts like moving leaves in the wind or driving cars on a street can easily be learned in order to mask such areas out and suppress false alarms there. This scene learning is done automatically simply by processing without UAVs in order to capture the normal situation. The given results document the performance of the presented approach in VIS and SWIR in different situations.

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.

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.

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...

THE APPLICABILITY OF EXISTING COMPUTER TECHNOLOGY TO AUTOMATE FUZZY SYNTHESIS OF TRAFFIC LIGHT UAV IN ADVERSE WEATHER CONDITIONS

Directory of Open Access Journals (Sweden)

L. N. Lysenko

2014-01-01

Full Text Available The results of the analysis of the applicability of known application software systems for automated synthesis of fuzzy control traffic light UAV during its flight in adverse weather conditions. The solution is based on a previously formulated and put into consideration the principle of permissible limited a priori estimation of the uncertainty of aerodynamic characteristics of UAVs.

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

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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.

Contour Detection for UAV-Based Cadastral Mapping

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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.

Moving object detection using dynamic motion modelling from UAV aerial images.

Science.gov (United States)

Saif, A F M Saifuddin; Prabuwono, Anton Satria; Mahayuddin, Zainal Rasyid

2014-01-01

Motion analysis based moving object detection from UAV aerial image is still an unsolved issue due to inconsideration of proper motion estimation. Existing moving object detection approaches from UAV aerial images did not deal with motion based pixel intensity measurement to detect moving object robustly. Besides current research on moving object detection from UAV aerial images mostly depends on either frame difference or segmentation approach separately. There are two main purposes for this research: firstly to develop a new motion model called DMM (dynamic motion model) and secondly to apply the proposed segmentation approach SUED (segmentation using edge based dilation) using frame difference embedded together with DMM model. The proposed DMM model provides effective search windows based on the highest pixel intensity to segment only specific area for moving object rather than searching the whole area of the frame using SUED. At each stage of the proposed scheme, experimental fusion of the DMM and SUED produces extracted moving objects faithfully. Experimental result reveals that the proposed DMM and SUED have successfully demonstrated the validity of the proposed methodology.

USE OF UAV PLATFORM AS AN AUTONOMOUS TOOL FOR ESTIMATING EXPANSION ON INVADED AGRICULTURAL LAND

Directory of Open Access Journals (Sweden)

Niarkios Luiz Santos de Salles Graça

Full Text Available Abstract: For a long time, in many countries, questions involving disputes about land ownership has generated demand for geoinformation and documentation. In most cases, access for researchers is restricted or humanely impossible by eminence of conflicts, even armed. In these cases, researchers use Remote Sensing and Photogrammetry to enable their studies. However, the dynamics of the phenomenon being studied often requires approaches that traditional techniques become unviable or unable to fulfil. This work shows the results of an approach that used a photogrammetric UAV platform to take pictures of an invaded rural area in Brazil and estimate its expansion over two years. From the taken images, mosaics were generated and then classified using Decision Tree to identify tents. Then it was developed a Matlab algorithm, to detect and quantify the tents on the classified Images. It was possible to infer that there was an expansion of 7.3% between the two analyzed dates and probably more than three thousand people occupied the invasion site.

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.

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.

State estimation and control for low-cost unmanned aerial vehicles

CERN Document Server

Hajiyev, Chingiz; Yenal Vural, Sıtkı

2015-01-01

This book discusses state estimation and control procedures for a low-cost unmanned aerial vehicle (UAV). The authors consider the use of robust adaptive Kalman filter algorithms and demonstrate their advantages over the optimal Kalman filter in the context of the difficult and varied environments in which UAVs may be employed. Fault detection and isolation (FDI) and data fusion for UAV air-data systems are also investigated, and control algorithms, including the classical, optimal, and fuzzy controllers, are given for the UAV. The performance of different control methods is investigated and the results compared. State Estimation and Control of Low-Cost Unmanned Aerial Vehicles covers all the important issues for designing a guidance, navigation and control (GNC) system of a low-cost UAV. It proposes significant new approaches that can be exploited by GNC system designers in the future and also reviews the current literature. The state estimation, control and FDI methods are illustrated by examples and MATLAB...

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).

Leaf Area Index Estimation in Vineyards from Uav Hyperspectral Data, 2d Image Mosaics and 3d Canopy Surface Models

Science.gov (United States)

Kalisperakis, I.; Stentoumis, Ch.; Grammatikopoulos, L.; Karantzalos, K.

2015-08-01

The indirect estimation of leaf area index (LAI) in large spatial scales is crucial for several environmental and agricultural applications. To this end, in this paper, we compare and evaluate LAI estimation in vineyards from different UAV imaging datasets. In particular, canopy levels were estimated from i.e., (i) hyperspectral data, (ii) 2D RGB orthophotomosaics and (iii) 3D crop surface models. The computed canopy levels have been used to establish relationships with the measured LAI (ground truth) from several vines in Nemea, Greece. The overall evaluation indicated that the estimated canopy levels were correlated (r2 > 73%) with the in-situ, ground truth LAI measurements. As expected the lowest correlations were derived from the calculated greenness levels from the 2D RGB orthomosaics. The highest correlation rates were established with the hyperspectral canopy greenness and the 3D canopy surface models. For the later the accurate detection of canopy, soil and other materials in between the vine rows is required. All approaches tend to overestimate LAI in cases with sparse, weak, unhealthy plants and canopy.

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.

Internal and external potential-field estimation from regional vector data at varying satellite altitude

Science.gov (United States)

Plattner, Alain; Simons, Frederik J.

2017-10-01

When modelling satellite data to recover a global planetary magnetic or gravitational potential field, the method of choice remains their analysis in terms of spherical harmonics. When only regional data are available, or when data quality varies strongly with geographic location, the inversion problem becomes severely ill-posed. In those cases, adopting explicitly local methods is to be preferred over adapting global ones (e.g. by regularization). Here, we develop the theory behind a procedure to invert for planetary potential fields from vector observations collected within a spatially bounded region at varying satellite altitude. Our method relies on the construction of spatiospectrally localized bases of functions that mitigate the noise amplification caused by downward continuation (from the satellite altitude to the source) while balancing the conflicting demands for spatial concentration and spectral limitation. The `altitude-cognizant' gradient vector Slepian functions (AC-GVSF) enjoy a noise tolerance under downward continuation that is much improved relative to the `classical' gradient vector Slepian functions (CL-GVSF), which do not factor satellite altitude into their construction. Furthermore, venturing beyond the realm of their first application, published in a preceding paper, in the present article we extend the theory to being able to handle both internal and external potential-field estimation. Solving simultaneously for internal and external fields under the limitation of regional data availability reduces internal-field artefacts introduced by downward-continuing unmodelled external fields, as we show with numerical examples. We explain our solution strategies on the basis of analytic expressions for the behaviour of the estimation bias and variance of models for which signal and noise are uncorrelated, (essentially) space- and band-limited, and spectrally (almost) white. The AC-GVSF are optimal linear combinations of vector spherical harmonics

EVALUATION OF A NOVEL UAV-BORNE TOPO-BATHYMETRIC LASER PROFILER

Directory of Open Access Journals (Sweden)

G. Mandlburger

2016-06-01

Full Text Available We present a novel topo-bathymetric laser profiler. The sensor system (RIEGL BathyCopter comprises a laser range finder, an Inertial Measurement Unit (IMU, a Global Navigation Satellite System (GNSS receiver, a control unit, and digital cameras mounted on an octocopter UAV (RiCOPTER. The range finder operates on the time-of-flight measurement principle and utilizes very short laser pulses (<1 ns in the green domain of the spectrum (λ=532 nm for measuring distances to both the water surface and the river bottom. For assessing the precision and accuracy of the system an experiment was carried out in October 2015 at a pre-alpine river (Pielach in Lower Austria. A 200 m longitudinal section and 12 river cross sections were measured with the BathyCopter sensor system at a flight altitude of 15-20 m above ground level and a measurement rate of 4 kHz. The 3D laser profiler points were compared with independent, quasi-simultaneous data acquisitions using (i the RIEGL VUX1-UAV lightweight topographic laser scanning system (bare earth, water surface and (ii terrestrial survey (river bed. Over bare earth the laser profiler heights have a std. dev. of 3 cm, the water surface height appears to be underestimated by 5 cm, and river bottom heights differ from the reference measurements by 10 cm with a std. dev. of 13 cm. When restricting the comparison to laser profiler bottom points and reference measurements with a lateral offset below 1 m, the values improve to 4 cm bias with a std. dev. of 6 cm. We report additionally on challenges in comparing UAV-borne to terrestrial profiles. Based on the accuracy and the small footprint (3.5 cm at the water surface we concluded that the acquired 3D points can potentially serve as input data (river bed geometry, grain roughness and validation data (water surface, water depth for hydrodynamic-numerical models.

Station-keeping of a high-altitude balloon with electric propulsion and wireless power transmission: A concept study

Science.gov (United States)

van Wynsberghe, Erinn; Turak, Ayse

2016-11-01

A stable, ultra long-duration high-altitude balloon (HAB) platform which can maintain stationary position would represent a new paradigm for telecommunications and high-altitude observation and transmission services, with greatly reduced cost and complexity compared to existing technologies including satellites, telecom towers, and unmanned aerial vehicles (UAVs). This contribution proposes a lightweight superpressure balloon platform for deployment to an altitude of 25 km. Electrohydrodynamic (EHD) thrusters are presented to maintain position by overcoming stratospheric winds. Critical to maintaining position is a continual supply of electrical power to operate the on-board propulsion system. One viable solution is to deliver power wirelessly to a high-altitude craft from a ground-based transmitter. Microwave energy, not heavily attenuated by the atmosphere, can be provided remotely from a ground-based generator (magnetron, klystron, etc.) and steered electrically with an antenna array (phased array) at a designated frequency (such as 2.45 or 5.8 GHz). A rectifying antenna ("rectenna") on the bottom of the balloon converts waves into direct current for on-board use. Preliminary mission architecture, energy requirements, and safety concerns for a proposed system are presented along with recommended future work.

RAVEN-2: Around-The-World UAV Project

National Research Council Canada - National Science Library

Burleigh, Chris

2003-01-01

The Raven around-the-world UAV project is part of an on-going effort to build up a significant European capability in the design, construction and operation of large UAVs and manned reconnaissance aircraft...

Using crowd sourcing to combat potentially illegal or dangerous UAV operations

Science.gov (United States)

Tapsall, Brooke T.

2016-10-01

The UAV (Unmanned Aerial Vehicles) industry is growing exponentially at a pace that policy makers, individual countries and law enforcement agencies are finding difficult to keep up. The UAV market is large, as such the amount of UAVs being operated in potentially dangerous situations is prevalent and rapidly increasing. Media is continually reporting `near-miss' incidents between UAVs and commercial aircraft, UAV breaching security in sensitive areas or invading public privacy. One major challenge for law enforcement agencies is gaining tangible evidence against potentially dangerous or illegal UAV operators due to the rapidity with which UAV operators are able to enter, fly and exit a scene before authorities can arrive or before they can be located. DroneALERT, an application available via the Airport-UAV.com website, allows users to capture potentially dangerous or illegal UAV activity using their mobile device as it the incident is occurring. A short online DroneALERT Incident Report (DIR) is produced, emailed to the user and the Airport-UAV.com custodians. The DIR can be used to aid authorities in their investigations. The DIR contains details such as images and videos, location, time, date of the incident, drone model, its distance and height. By analysing information from the DIR, photos or video, there is a high potential for law enforcement authorities to use this evidence to identify the type of UAV used, triangulate the location of the potential dangerous UAV and operator, create a timeline of events, potential areas of operator exit and to determine the legalities breached. All provides crucial evidence for identifying and prosecuting a UAV operator.

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.

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

Systemic Approach to Elevation Data Acquisition for Geophysical Survey Alignments in Hilly Terrains Using UAVs

Science.gov (United States)

Ismail, M. A. M.; Kumar, N. S.; Abidin, M. H. Z.; Madun, A.

2018-04-01

This study is about systematic approach to photogrammetric survey that is applicable in the extraction of elevation data for geophysical surveys in hilly terrains using Unmanned Aerial Vehicles (UAVs). The outcome will be to acquire high-quality geophysical data from areas where elevations vary by locating the best survey lines. The study area is located at the proposed construction site for the development of a water reservoir and related infrastructure in Kampus Pauh Putra, Universiti Malaysia Perlis. Seismic refraction surveys were carried out for the modelling of the subsurface for detailed site investigations. Study were carried out to identify the accuracy of the digital elevation model (DEM) produced from an UAV. At 100 m altitude (flying height), over 135 overlapping images were acquired using a DJI Phantom 3 quadcopter. All acquired images were processed for automatic 3D photo-reconstruction using Agisoft PhotoScan digital photogrammetric software, which was applied to all photogrammetric stages. The products generated included a 3D model, dense point cloud, mesh surface, digital orthophoto, and DEM. In validating the accuracy of the produced DEM, the coordinates of the selected ground control point (GCP) of the survey line in the imaging area were extracted from the generated DEM with the aid of Global Mapper software. These coordinates were compared with the GCPs obtained using a real-time kinematic global positioning system. The maximum percentage of difference between GCP’s and photogrammetry survey is 13.3 %. UAVs are suitable for acquiring elevation data for geophysical surveys which can save time and cost.

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

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.

Automatic Reverse Engineering of Private Flight Control Protocols of UAVs

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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.

Mapping of radiation anomalies using UAV mini-airborne gamma-ray spectrometry.

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Šálek, Ondřej; Matolín, Milan; Gryc, Lubomír

2018-02-01

Localization of size-limited gamma-ray anomalies plays a fundamental role in uranium prospecting and environmental studies. Possibilities of a newly developed mini-airborne gamma-ray spectrometric equipment were tested on a uranium anomaly near the village of Třebsko, Czech Republic. The measurement equipment was based on a scintillation gamma-ray spectrometer specially developed for unmanned aerial vehicles (UAV) mounted on powerful hexacopter. The gamma-ray spectrometer has two 103 cm 3 BGO scintillation detectors of relatively high sensitivity. The tested anomaly, which is 80 m by 40 m in size, was investigated by ground gamma-ray spectrometric measurement in a detail rectangular measurement grid. Average uranium concentration is 25 mg/kg eU attaining 700 mg/kg eU locally. The mini-airborne measurement across the anomaly was carried out on three 100 m long parallel profiles at eight flight altitudes from 5 to 40 m above the ground. The resulting 1 s 1024 channel gamma-ray spectra, recorded in counts per second (cps), were processed to concentration units of K, U and Th, while total count (TC) was reported in cps. Increased gamma ray intensity of the anomaly was indicated by mini-airborne measurement at all profiles and altitudes, including the highest altitude of 40 m, at which the recorded intensity is close to the natural radiation background. The reported instrument is able to record data with comparable quality as standard airborne survey, due to relative sensitive detector, lower flight altitude and relatively low flight speed of 1 m/s. The presented experiment brings new experience with using unmanned semi-autonomous aerial vehicles and the latest mini-airborne radiometric instrument. The experiment has demonstrated the instrument's ability to localize size-limited uranium anomalies. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

Slic Superpixels for Object Delineation from Uav Data

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Crommelinck, S.; Bennett, R.; Gerke, M.; Koeva, M. N.; Yang, M. Y.; Vosselman, G.

2017-08-01

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 image analysis methods to improve existing mapping procedures that are cost, time and labor intensive and of little reproducibility. This study investigates a superpixel approach, namely simple linear iterative clustering (SLIC), in terms of its applicability to UAV data. The approach is investigated in terms of its applicability to high-resolution UAV orthoimages and in terms of its ability to delineate object outlines of roads and roofs. Results show that the approach is applicable to UAV orthoimages of 0.05 m GSD and extents of 100 million and 400 million pixels. Further, the approach delineates the objects with the high accuracy provided by the UAV orthoimages at completeness rates of up to 64 %. The approach is not suitable as a standalone approach for object delineation. However, it shows high potential for a combination with further methods that delineate objects at higher correctness rates in exchange of a lower localization quality. This study provides a basis for future work that will focus on the incorporation of multiple methods for an interactive, comprehensive and accurate object delineation from UAV data. This aims to support numerous application fields such as topographic and cadastral mapping.

Estimating and forecasting the precipitable water vapor from GOES satellite data at high altitude sites

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Marín, Julio C.; Pozo, Diana; Curé, Michel

2015-01-01

In this work, we describe a method to estimate the precipitable water vapor (PWV) from Geostationary Observational Environmental Satellite (GOES) data at high altitude sites. The method was applied at Atacama Pathfinder Experiment (APEX) and Cerro Toco sites, located above 5000 m altitude in the Chajnantor plateau, in the north of Chile. It was validated using GOES-12 satellite data over the range 0-1.2 mm since submillimeter/millimeter astronomical observations are only useful within this PWV range. The PWV estimated from GOES and the Final Analyses (FNL) at APEX for 2007 and 2009 show root mean square error values of 0.23 mm and 0.36 mm over the ranges 0-0.4 mm and 0.4-1.2 mm, respectively. However, absolute relative errors of 51% and 33% were shown over these PWV ranges, respectively. We recommend using high-resolution thermodynamic profiles from the Global Forecast System (GFS) model to estimate the PWV from GOES data since they are available every three hours and at an earlier time than the FNL data. The estimated PWV from GOES/GFS agrees better with the observed PWV at both sites during night time. The largest errors are shown during daytime. Short-term PWV forecasts were implemented at both sites, applying a simple persistence method to the PWV estimated from GOES/GFS. The 12 h and 24 h PWV forecasts evaluated from August to October 2009 indicates that 25% of them show a very good agreement with observations whereas 50% of them show reasonably good agreement with observations. Transmission uncertainties calculated for PWV estimations and forecasts over the studied sites are larger over the range 0-0.4 mm than over the range 0.4-1.2 mm. Thus, the method can be used over the latter interval with more confidence.

Design of a high altitude long endurance flying-wing solar-powered unmanned air vehicle

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Alsahlani, A. A.; Johnston, L. J.; Atcliffe, P. A.

2017-06-01

The low-Reynolds number environment of high-altitude §ight places severe demands on the aerodynamic design and stability and control of a high altitude, long endurance (HALE) unmanned air vehicle (UAV). The aerodynamic efficiency of a §ying-wing configuration makes it an attractive design option for such an application and is investigated in the present work. The proposed configuration has a high-aspect ratio, swept-wing planform, the wing sweep being necessary to provide an adequate moment arm for outboard longitudinal and lateral control surfaces. A design optimization framework is developed under a MATLAB environment, combining aerodynamic, structural, and stability analysis. Low-order analysis tools are employed to facilitate efficient computations, which is important when there are multiple optimization loops for the various engineering analyses. In particular, a vortex-lattice method is used to compute the wing planform aerodynamics, coupled to a twodimensional (2D) panel method to derive aerofoil sectional characteristics. Integral boundary-layer methods are coupled to the panel method in order to predict §ow separation boundaries during the design iterations. A quasi-analytical method is adapted for application to flyingwing con¦gurations to predict the wing weight and a linear finite-beam element approach is used for structural analysis of the wing-box. Stability is a particular concern in the low-density environment of high-altitude flight for flying-wing aircraft and so provision of adequate directional stability and control power forms part of the optimization process. At present, a modified Genetic Algorithm is used in all of the optimization loops. Each of the low-order engineering analysis tools is validated using higher-order methods to provide con¦dence in the use of these computationally-efficient tools in the present design-optimization framework. This paper includes the results of employing the present optimization tools in the design of a

Flocking of quad-rotor UAVs with fuzzy control.

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Mao, Xiang; Zhang, Hongbin; Wang, Yanhui

2018-03-01

This paper investigates the flocking problem of quad-rotor UAVs. Considering the actual situations, we derived a new simplified quad-rotor UAV model which is more reasonable. Based on the model, the T-S fuzzy model of attitude dynamic equation and the corresponding T-S fuzzy feedback controller are discussed. By introducing a double-loop control construction, we adjust its attitude to realize the position control. Then a flocking algorithm is proposed to achieve the flocking of the quad-rotor UAVs. Compared with the flocking algorithm of the mass point model, we dealt with the collision problem of the quad-rotor UAVs. In order to improve the airspace utilization, a more compact configuration called quasi e-lattice is constructed to guarantee the compact flight of the quad-rotor UAVs. Finally, numerical simulations are provided to illustrate the effectiveness of the obtained theoretical results. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Autonomous Control of a Quadrotor UAV Using Fuzzy Logic

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Sureshkumar, Vijaykumar

UAVs are being increasingly used today than ever before in both military and civil applications. They are heavily preferred in "dull, dirty or dangerous" mission scenarios. Increasingly, UAVs of all kinds are being used in policing, fire-fighting, inspection of structures, pipelines etc. Recently, the FAA gave its permission for UAVs to be used on film sets for motion capture and high definition video recording. The rapid development in MEMS and actuator technology has made possible a plethora of UAVs that are suited for commercial applications in an increasingly cost effective manner. An emerging popular rotary wing UAV platform is the Quadrotor A Quadrotor is a helicopter with four rotors, that make it more stable; but more complex to model and control. Characteristics that provide a clear advantage over other fixed wing UAVs are VTOL and hovering capabilities as well as a greater maneuverability. It is also simple in construction and design compared to a scaled single rotorcraft. Flying such UAVs using a traditional radio Transmitter-Receiver setup can be a daunting task especially in high stress situations. In order to make such platforms widely applicable, a certain level of autonomy is imperative to the future of such UAVs. This thesis paper presents a methodology for the autonomous control of a Quadrotor UAV using Fuzzy Logic. Fuzzy logic control has been chosen over conventional control methods as it can deal effectively with highly nonlinear systems, allows for imprecise data and is extremely modular. Modularity and adaptability are the key cornerstones of FLC. The objective of this thesis is to present the steps of designing, building and simulating an intelligent flight control module for a Quadrotor UAV. In the course of this research effort, a Quadrotor UAV is indigenously developed utilizing the resources of an online open source project called Aeroquad. System design is comprehensively dealt with. A math model for the Quadrotor is developed and a

Development of a bio-inspired UAV perching system

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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

A Novel Online Data-Driven Algorithm for Detecting UAV Navigation Sensor Faults

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Rui Sun

2017-09-01

Full Text Available 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.

State-Of in Uav Remote Sensing Survey - First Insights Into Applications of Uav Sensing Systems

Science.gov (United States)

Aasen, H.

2017-08-01

UAVs are increasingly adapted as remote sensing platforms. Together with specialized sensors, they become powerful sensing systems for environmental monitoring and surveying. Spectral data has great capabilities to the gather information about biophysical and biochemical properties. Still, capturing meaningful spectral data in a reproducible way is not trivial. Since a couple of years small and lightweight spectral sensors, which can be carried on small flexible platforms, have become available. With their adaption in the community, the responsibility to ensure the quality of the data is increasingly shifted from specialized companies and agencies to individual researchers or research teams. Due to the complexity of the data acquisition of spectral data, this poses a challenge for the community and standardized protocols, metadata and best practice procedures are needed to make data intercomparable. In November 2016, the ESSEM COST action Innovative optical Tools for proximal sensing of ecophysiological processes (OPTIMISE; http://optimise.dcs.aber.ac.uk/) held a workshop on best practices for UAV spectral sampling. The objective of this meeting was to trace the way from particle to pixel and identify influences on the data quality / reliability, to figure out how well we are currently doing with spectral sampling from UAVs and how we can improve. Additionally, a survey was designed to be distributed within the community to get an overview over the current practices and raise awareness for the topic. This talk will introduce the approach of the OPTIMISE community towards best practises in UAV spectral sampling and present first results of the survey (http://optimise.dcs.aber.ac.uk/uav-survey/). This contribution briefly introduces the survey and gives some insights into the first results given by the interviewees.

A mini-UAV VTOL Platform for Surveying Applications

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Kuldeep Rawat

2014-05-01

Full Text Available In this paper we discuss implementation of a mini-Unmanned Aerial Vehicle (UAV vertical take-off and landing (VTOL platform for surveying activities related to highway construction. Recent advances in sensor and communication technologies have allowed scaling sizes of unmanned aerial platforms, and explore them for tasks that are economical and safe over populated or inhabited areas. In highway construction the capability of mini-UAVs to survey in hostile and/or hardly accessible areas can greatly reduce human risks. The project focused on developing a cost effective, remotely controlled, fuel powered mini-UAV VTOL (helicopter platform with certain payload capacity and configuration and demonstrated its use in surveying and monitoring activities required for highway planning and construction. With an on-board flight recorder global positioning system (GPS device, memory storage card, telemetry, inertial navigation sensors, and a video camera the mini-UAV can record flying coordinates and relay live video images to a remote ground receiver and surveyor. After all necessary integration and flight tests were done the mini-UAV helicopter was tested to operate and relay video from the areas where construction was underway. The mini-UAV can provide a platform for a range of sensors and instruments that directly support the operational requirements of transportation sector.

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

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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.

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.

A method of fast mosaic for massive UAV images

Science.gov (United States)

Xiang, Ren; Sun, Min; Jiang, Cheng; Liu, Lei; Zheng, Hui; Li, Xiaodong

2014-11-01

With the development of UAV technology, UAVs are used widely in multiple fields such as agriculture, forest protection, mineral exploration, natural disaster management and surveillances of public security events. In contrast of traditional manned aerial remote sensing platforms, UAVs are cheaper and more flexible to use. So users can obtain massive image data with UAVs, but this requires a lot of time to process the image data, for example, Pix4UAV need approximately 10 hours to process 1000 images in a high performance PC. But disaster management and many other fields require quick respond which is hard to realize with massive image data. Aiming at improving the disadvantage of high time consumption and manual interaction, in this article a solution of fast UAV image stitching is raised. GPS and POS data are used to pre-process the original images from UAV, belts and relation between belts and images are recognized automatically by the program, in the same time useless images are picked out. This can boost the progress of finding match points between images. Levenberg-Marquard algorithm is improved so that parallel computing can be applied to shorten the time of global optimization notably. Besides traditional mosaic result, it can also generate superoverlay result for Google Earth, which can provide a fast and easy way to show the result data. In order to verify the feasibility of this method, a fast mosaic system of massive UAV images is developed, which is fully automated and no manual interaction is needed after original images and GPS data are provided. A test using 800 images of Kelan River in Xinjiang Province shows that this system can reduce 35%-50% time consumption in contrast of traditional methods, and increases respond speed of UAV image processing rapidly.

Single and Multiple UAV Cyber-Attack Simulation and Performance Evaluation

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Ahmad Y. Javaid

2015-02-01

Full Text Available Usage of ground, air and underwater unmanned vehicles (UGV, UAV and UUV has increased exponentially in the recent past with industries producing thousands of these unmanned vehicles every year.With the ongoing discussion of integration of UAVs in the US National Airspace, the need of a cost-effective way to verify the security and resilience of a group of communicating UAVs under attack has become very important. The answer to this need is a simulation testbed which can be used to simulate the UAV Network (UAVNet. One of these attempts is - UAVSim (Unmanned Aerial Vehicle Simulation testbed developed at the University of Toledo. It has the capability of simulating large UAV networks as well as small UAV networks with large number of attack nodes. In this paper, we analyse the performance of the simulation testbed for two attacks, targeting single and multiple UAVs. Traditional and generic computing resource available in a regular computer laboratory was used. Various evaluation results have been presented and analysed which suggest the suitability of UAVSim for UAVNet attack and swarm simulation applications.

Vision-Based Detection and Distance Estimation of Micro Unmanned Aerial Vehicles

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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.

Surveillance mission planning for UAVs in GPS-denied urban environment

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Pengfei, Wang

In this thesis, the issues involved in the mission planning of UAVs for city surveillance have been studied. In this thesis, the research includes two major parts. Firstly, a mission planning system is developed that generates mission plans for a group of fixed-wing UAVs with on-board gimballed cameras to provide continuous surveillance over an urban area. Secondly, the problem of perching location selection (as part of perch-and-stare surveillance mission) for rotary-wing UAVs in a GPS-denied environment is studied. In this kind of mission, a UAV is dispatched to perch on a roof of a building to keep surveillance on a given target. The proposed algorithms to UAV surveillance mission planning (fixed-wing and rotary-wing) have been implemented and tested. It represents an important step towards achieving autonomous planning in UAV surveillance missions.

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

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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.

Mini UAV as an improvised air threat

NARCIS (Netherlands)

Kraker, K.J. de; Wiel, R.A.N. van de

2013-01-01

The use of UAVs for military and law enforcement purposes is increasing dramatically. Simultaneously, possible opponents are also developing UAV capabilities that they may deploy for their purposes. For example, a terrorist may deploy a commercially available model airplane or multicopter with an

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.

BEACH VOLUME CHANGE USING UAV PHOTOGRAMMETRY SONGJUNG BEACH, KOREA

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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.

High Altitude Long Endurance UAV Analysis Model Development and Application Study Comparing Solar Powered Airplane and Airship Station-Keeping Capabilities

Science.gov (United States)

Ozoroski, Thomas A.; Nickol, Craig L.; Guynn, Mark D.

2015-01-01

There have been ongoing efforts in the Aeronautics Systems Analysis Branch at NASA Langley Research Center to develop a suite of integrated physics-based computational utilities suitable for modeling and analyzing extended-duration missions carried out using solar powered aircraft. From these efforts, SolFlyte has emerged as a state-of-the-art vehicle analysis and mission simulation tool capable of modeling both heavier-than-air (HTA) and lighter-than-air (LTA) vehicle concepts. This study compares solar powered airplane and airship station-keeping capability during a variety of high altitude missions, using SolFlyte as the primary analysis component. Three Unmanned Aerial Vehicle (UAV) concepts were designed for this study: an airplane (Operating Empty Weight (OEW) = 3285 kilograms, span = 127 meters, array area = 450 square meters), a small airship (OEW = 3790 kilograms, length = 115 meters, array area = 570 square meters), and a large airship (OEW = 6250 kilograms, length = 135 meters, array area = 1080 square meters). All the vehicles were sized for payload weight and power requirements of 454 kilograms and 5 kilowatts, respectively. Seven mission sites distributed throughout the United States were selected to provide a basis for assessing the vehicle energy budgets and site-persistent operational availability. Seasonal, 30-day duration missions were simulated at each of the sites during March, June, September, and December; one-year duration missions were simulated at three of the sites. Atmospheric conditions during the simulated missions were correlated to National Climatic Data Center (NCDC) historical data measurements at each mission site, at four flight levels. Unique features of the SolFlyte model are described, including methods for calculating recoverable and energy-optimal flight trajectories and the effects of shadows on solar energy collection. Results of this study indicate that: 1) the airplane concept attained longer periods of on

UAV VISUAL AUTOLOCALIZATON BASED ON AUTOMATIC LANDMARK RECOGNITION

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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.

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

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.

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

Nonlinear control of fixed-wing UAVs in presence of stochastic winds

Science.gov (United States)

Rubio Hervas, Jaime; Reyhanoglu, Mahmut; Tang, Hui; Kayacan, Erdal

2016-04-01

This paper studies the control of fixed-wing unmanned aerial vehicles (UAVs) in the presence of stochastic winds. A nonlinear controller is designed based on a full nonlinear mathematical model that includes the stochastic wind effects. The air velocity is controlled exclusively using the position of the throttle, and the rest of the dynamics are controlled with the aileron, elevator, and rudder deflections. The nonlinear control design is based on a smooth approximation of a sliding mode controller. An extended Kalman filter (EKF) is proposed for the state estimation and filtering. A case study is presented: landing control of a UAV on a ship deck in the presence of wind based exclusively on LADAR measurements. The effectiveness of the nonlinear control algorithm is illustrated through a simulation example.

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.

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...

Critical infrastructure monitoring using UAV imagery

Science.gov (United States)

Maltezos, Evangelos; Skitsas, Michael; Charalambous, Elisavet; Koutras, Nikolaos; Bliziotis, Dimitris; Themistocleous, Kyriacos

2016-08-01

The constant technological evolution in Computer Vision enabled the development of new techniques which in conjunction with the use of Unmanned Aerial Vehicles (UAVs) may extract high quality photogrammetric products for several applications. Dense Image Matching (DIM) is a Computer Vision technique that can generate a dense 3D point cloud of an area or object. The use of UAV systems and DIM techniques is not only a flexible and attractive solution to produce accurate and high qualitative photogrammetric results but also is a major contribution to cost effectiveness. In this context, this study aims to highlight the benefits of the use of the UAVs in critical infrastructure monitoring applying DIM. A Multi-View Stereo (MVS) approach using multiple images (RGB digital aerial and oblique images), to fully cover the area of interest, is implemented. The application area is an Olympic venue in Attica, Greece, at an area of 400 acres. The results of our study indicate that the UAV+DIM approach respond very well to the increasingly greater demands for accurate and cost effective applications when provided with, a 3D point cloud and orthomosaic.

Heterogeneous CPU-GPU moving targets detection for UAV video

Science.gov (United States)

Li, Maowen; Tang, Linbo; Han, Yuqi; Yu, Chunlei; Zhang, Chao; Fu, Huiquan

2017-07-01

Moving targets detection is gaining popularity in civilian and military applications. On some monitoring platform of motion detection, some low-resolution stationary cameras are replaced by moving HD camera based on UAVs. The pixels of moving targets in the HD Video taken by UAV are always in a minority, and the background of the frame is usually moving because of the motion of UAVs. The high computational cost of the algorithm prevents running it at higher resolutions the pixels of frame. Hence, to solve the problem of moving targets detection based UAVs video, we propose a heterogeneous CPU-GPU moving target detection algorithm for UAV video. More specifically, we use background registration to eliminate the impact of the moving background and frame difference to detect small moving targets. In order to achieve the effect of real-time processing, we design the solution of heterogeneous CPU-GPU framework for our method. The experimental results show that our method can detect the main moving targets from the HD video taken by UAV, and the average process time is 52.16ms per frame which is fast enough to solve the problem.

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.

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.

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...

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.

Tropical Peatland Burn Depth and Combustion Heterogeneity Assessed Using UAV Photogrammetry and Airborne LiDAR

Directory of Open Access Journals (Sweden)

Jake E. Simpson

2016-12-01

Full Text Available We provide the first assessment of tropical peatland depth of burn (DoB using structure from motion (SfM photogrammetry, applied to imagery collected using a low-cost, low-altitude unmanned aerial vehicle (UAV system operated over a 5.2 ha tropical peatland in Jambi Province on Sumatra, Indonesia. Tropical peat soils are the result of thousands of years of dead biomass accumulation, and when burned are globally significant net sources of carbon emissions. The El Niño year of 2015 saw huge areas of Indonesia affected by tropical peatland fires, more so than any year since 1997. However, the Depth of Burn (DoB of these 2015 fires has not been assessed, and indeed has only previously been assessed in few tropical peatland burns in Kalimantan. Therefore, DoB remains arguably the largest uncertainty when undertaking fire emissions calculations in these tropical peatland environments. We apply a SfM photogrammetric methodology to map this DoB metric, and also investigate combustion heterogeneity using orthomosaic photography collected using the UAV system. We supplement this information with pre-burn airborne light detection and ranging (LiDAR data, reducing uncertainty by estimating pre-burn soil height more accurately than from interpolation of adjacent unburned areas alone. Our pre-and post-fire Digital Terrain Models (DTMs show accuracies of 0.04 and 0.05 m (root-mean-square error, RMSE respectively, compared to ground-based global navigation satellite system (GNSS surveys. Our final DoB map of a 5.2 ha degraded peat swamp forest area neighboring Berbak National Park (Sumatra, Indonesia shows burn depths extending from close to zero to over 1 m, with a mean (±1σ DoB of 0.23 ± 0.19 m. This lies well within the range found by the few other studies available (on Kalimantan; none are available on Sumatra. Our combustion heterogeneity analysis suggests the deepest burns, which extend to ~1.3 m, occur around tree roots. We use these DoB data within

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.

Classical Photogrammetry and Uav - Selected Ascpects

Science.gov (United States)

Mikrut, S.

2016-06-01

The UAV technology seems to be highly future-oriented due to its low costs as compared to traditional aerial images taken from classical photogrammetry aircrafts. The AGH University of Science and Technology in Cracow - Department of Geoinformation, Photogrammetry and Environmental Remote Sensing focuses mainly on geometry and radiometry of recorded images. Various scientific research centres all over the world have been conducting the relevant research for years. The paper presents selected aspects of processing digital images made with the UAV technology. It provides on a practical example a comparison between a digital image taken from an airborne (classical) height, and the one made from an UAV level. In his research the author of the paper is trying to find an answer to the question: to what extent does the UAV technology diverge today from classical photogrammetry, and what are the advantages and disadvantages of both methods? The flight plan was made over the Tokarnia Village Museum (more than 0.5 km2) for two separate flights: the first was made by an UAV - System FT-03A built by FlyTech Solution Ltd. The second was made with the use of a classical photogrammetric Cesna aircraft furnished with an airborne photogrammetric camera (Ultra Cam Eagle). Both sets of photographs were taken with pixel size of about 3 cm, in order to have reliable data allowing for both systems to be compared. The project has made aerotriangulation independently for the two flights. The DTM was generated automatically, and the last step was the generation of an orthophoto. The geometry of images was checked under the process of aerotriangulation. To compare the accuracy of these two flights, control and check points were used. RMSE were calculated. The radiometry was checked by a visual method and using the author's own algorithm for feature extraction (to define edges with subpixel accuracy). After initial pre-processing of data, the images were put together, and shown side by side

Landing spot selection for UAV emergency landing

NARCIS (Netherlands)

Eendebak, P.T.; Eekeren, A.W.M. van; Hollander, R.J.M. den

2013-01-01

We present a robust method for landing zone selection using obstacle detection to be used for UAV emergency landings. The method is simple enough to allow real-time implementation on a UAV system. The method is able to detect objects in the presence of camera movement and motion parallax. Using the

Estimated values of the environmental tritium concentration and the altitude isotope effects of δD and δ18O in Hokkaido

International Nuclear Information System (INIS)

Ikeda, Mitsuyoshi; Takata, Sigeru; Matsueda, Hiroharu

1998-01-01

Tritium ( 3 H) concentration and stable isotopic ratios δD and δ 18 O are important environmental tracer data. In Hokkaido, however, hydrological studies using these data were difficult due to a lack of environmental tritium and the altitude isotope effect values. In this study, 3 H concentrations of Hokkaido wine were measured to estimate the past rain 3 H concentrations. In addition, environmental δD and δ 18 O samples taken on Mt. Daisetsuzan, the highest peak in Hokkaido, and in the Tokachi Plain were measured. The results obtained are as follows: Estimated concentrations of 3 H in Hokkaido were higher than those in Tokyo and Tsukuba, and were consistent with geographical 3 H levels in rain around Hokkaido. Some model calculations suggested that the 3 H concentrations in the 1950's and 1960's were at least 30% higher than those in Tokyo. The altitude isotope effects obtained were -1.75±0.30 per mille/100 m and -0.24±0.01 per mille/100 m for δD and δ 18 O, respectively. These values are almost the same as, or slightly lower than those in the Chubu and Tohoku districts. Using these data, the approximate age of groundwater and the altitude of original precipitation could be estimated. (author)

Longitudinal Static Stability and wake visualization of high altitude long endurance aircraft developed in Bandung institute of technology

Science.gov (United States)

Irsyad Lukman, E.; Agoes Moelyadi, M.

2018-04-01

A High Altitude Long Endurance (HALE) Unamanned Aerial Vehicle (UAV) is currently being researched in Bandung Institute of Technology. The HALE is designed to be a pseudo-sattelite for information and communication purpose in Indonesia. This paper would present the longitudinal static stability of the aircraft that was analysed using DATCOM as well as simulation of the wing using ANSYS CFX. Result shows that the aircraft has acceptable stability and the wake from the wing at climbing condition cannot be ignored, however it does not affect the horizontal tail.

Weed detection by UAV with camera guided landing sequence

DEFF Research Database (Denmark)

Dyrmann, Mads

UAVs gain more and more currency in agriculture, as they allow for inspection of even remote areas of farmland. Measurements of weed occurrence in fields is one branch of this growing field of research. A problem with UAVs is that they have a limited energy capacity: Consequently, after a short...... flight, they must return to the farm to charge. By installing a landing platform in the field it is possible to have charging facilities close to the area where the UAV is used, providing greater opportunity for autonomous flight in distant fields. A landing platform in the field will also allow...... for greater computing capacity, whereby collected images can be processed and appropriate actions can be taken. The present study uses an entry level UAV with a Pixhawk controller and a GPS specified with an accuracy of 2.5m, meaning that the GPS alone is not sufficient to coordinate the UAV landing. Using...

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

USING DISTANCE SENSORS TO PERFORM COLLISION AVOIDANCE MANEUVRES ON UAV APPLICATIONS

Directory of Open Access Journals (Sweden)

A. Raimundo

2017-08-01

Full Text Available The Unmanned Aerial Vehicles (UAV and its applications are growing for both civilian and military purposes. The operability of an UAV proved that some tasks and operations can be done easily and at a good cost-efficiency ratio. Nowadays, an UAV can perform autonomous missions. It is very useful to certain UAV applications, such as meteorology, vigilance systems, agriculture, environment mapping and search and rescue operations. One of the biggest problems that an UAV faces is the possibility of collision with other objects in the flight area. To avoid this, an algorithm was developed and implemented in order to prevent UAV collision with other objects. “Sense and Avoid” algorithm was developed as a system for UAVs to avoid objects in collision course. This algorithm uses a Light Detection and Ranging (LiDAR, to detect objects facing the UAV in mid-flights. This light sensor is connected to an on-board hardware, Pixhawk’s flight controller, which interfaces its communications with another hardware: Raspberry Pi. Communications between Ground Control Station and UAV are made via Wi-Fi or cellular third or fourth generation (3G/4G. Some tests were made in order to evaluate the “Sense and Avoid” algorithm’s overall performance. These tests were done in two different environments: A 3D simulated environment and a real outdoor environment. Both modes worked successfully on a simulated 3D environment, and “Brake” mode on a real outdoor, proving its concepts.

Using Distance Sensors to Perform Collision Avoidance Maneuvres on Uav Applications

Science.gov (United States)

Raimundo, A.; Peres, D.; Santos, N.; Sebastião, P.; Souto, N.

2017-08-01

The Unmanned Aerial Vehicles (UAV) and its applications are growing for both civilian and military purposes. The operability of an UAV proved that some tasks and operations can be done easily and at a good cost-efficiency ratio. Nowadays, an UAV can perform autonomous missions. It is very useful to certain UAV applications, such as meteorology, vigilance systems, agriculture, environment mapping and search and rescue operations. One of the biggest problems that an UAV faces is the possibility of collision with other objects in the flight area. To avoid this, an algorithm was developed and implemented in order to prevent UAV collision with other objects. "Sense and Avoid" algorithm was developed as a system for UAVs to avoid objects in collision course. This algorithm uses a Light Detection and Ranging (LiDAR), to detect objects facing the UAV in mid-flights. This light sensor is connected to an on-board hardware, Pixhawk's flight controller, which interfaces its communications with another hardware: Raspberry Pi. Communications between Ground Control Station and UAV are made via Wi-Fi or cellular third or fourth generation (3G/4G). Some tests were made in order to evaluate the "Sense and Avoid" algorithm's overall performance. These tests were done in two different environments: A 3D simulated environment and a real outdoor environment. Both modes worked successfully on a simulated 3D environment, and "Brake" mode on a real outdoor, proving its concepts.

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.

Photogrammetric Measurements in Fixed Wing Uav Imagery

Science.gov (United States)

Gülch, E.

2012-07-01

Several flights have been undertaken with PAMS (Photogrammetric Aerial Mapping System) by Germap, Germany, which is briefly introduced. This system is based on the SmartPlane fixed-wing UAV and a CANON IXUS camera system. The plane is equipped with GPS and has an infrared sensor system to estimate attitude values. A software has been developed to link the PAMS output to a standard photogrammetric processing chain built on Trimble INPHO. The linking of the image files and image IDs and the handling of different cases with partly corrupted output have to be solved to generate an INPHO project file. Based on this project file the software packages MATCH-AT, MATCH-T DSM, OrthoMaster and OrthoVista for digital aerial triangulation, DTM/DSM generation and finally digital orthomosaik generation are applied. The focus has been on investigations on how to adapt the "usual" parameters for the digital aerial triangulation and other software to the UAV flight conditions, which are showing high overlaps, large kappa angles and a certain image blur in case of turbulences. It was found, that the selected parameter setup shows a quite stable behaviour and can be applied to other flights. A comparison is made to results from other open source multi-ray matching software to handle the issue of the described flight conditions. Flights over the same area at different times have been compared to each other. The major objective was here to see, on how far differences occur relative to each other, without having access to ground control data, which would have a potential for applications with low requirements on the absolute accuracy. The results show, that there are influences of weather and illumination visible. The "unusual" flight pattern, which shows big time differences for neighbouring strips has an influence on the AT and DTM/DSM generation. The results obtained so far do indicate problems in the stability of the camera calibration. This clearly requests a usage of GCPs for all

A Natural Interaction Interface for UAVs Using Intuitive Gesture Recognition

Science.gov (United States)

Chandarana, Meghan; Trujillo, Anna; Shimada, Kenji; Allen, Danette

2016-01-01

The popularity of unmanned aerial vehicles (UAVs) is increasing as technological advancements boost their favorability for a broad range of applications. One application is science data collection. In fields like Earth and atmospheric science, researchers are seeking to use UAVs to augment their current portfolio of platforms and increase their accessibility to geographic areas of interest. By increasing the number of data collection platforms UAVs will significantly improve system robustness and allow for more sophisticated studies. Scientists would like be able to deploy an available fleet of UAVs to fly a desired flight path and collect sensor data without needing to understand the complex low-level controls required to describe and coordinate such a mission. A natural interaction interface for a Ground Control System (GCS) using gesture recognition is developed to allow non-expert users (e.g., scientists) to define a complex flight path for a UAV using intuitive hand gesture inputs from the constructed gesture library. The GCS calculates the combined trajectory on-line, verifies the trajectory with the user, and sends it to the UAV controller to be flown.

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.

IMPROVED UAV-BORNE 3D MAPPING BY FUSING OPTICAL AND LASERSCANNER DATA

Directory of Open Access Journals (Sweden)

B. Jutzi

2013-08-01

Full Text Available In this paper, a new method for fusing optical and laserscanner data is presented for improved UAV-borne 3D mapping. We propose to equip an unmanned aerial vehicle (UAV with a small platform which includes two sensors: a standard low-cost digital camera and a lightweight Hokuyo UTM-30LX-EW laserscanning device (210 g without cable. Initially, a calibration is carried out for the utilized devices. This involves a geometric camera calibration and the estimation of the position and orientation offset between the two sensors by lever-arm and bore-sight calibration. Subsequently, a feature tracking is performed through the image sequence by considering extracted interest points as well as the projected 3D laser points. These 2D results are fused with the measured laser distances and fed into a bundle adjustment in order to obtain a Simultaneous Localization and Mapping (SLAM. It is demonstrated that an improvement in terms of precision for the pose estimation is derived by fusing optical and laserscanner data.

Altitude training and haemoglobin mass from the optimised carbon monoxide rebreathing method determined by a meta-analysis.

Science.gov (United States)

Gore, Christopher J; Sharpe, Ken; Garvican-Lewis, Laura A; Saunders, Philo U; Humberstone, Clare E; Robertson, Eileen Y; Wachsmuth, Nadine B; Clark, Sally A; McLean, Blake D; Friedmann-Bette, Birgit; Neya, Mitsuo; Pottgiesser, Torben; Schumacher, Yorck O; Schmidt, Walter F

2013-12-01

To characterise the time course of changes in haemoglobin mass (Hbmass) in response to altitude exposure. This meta-analysis uses raw data from 17 studies that used carbon monoxide rebreathing to determine Hbmass prealtitude, during altitude and postaltitude. Seven studies were classic altitude training, eight were live high train low (LHTL) and two mixed classic and LHTL. Separate linear-mixed models were fitted to the data from the 17 studies and the resultant estimates of the effects of altitude used in a random effects meta-analysis to obtain an overall estimate of the effect of altitude, with separate analyses during altitude and postaltitude. In addition, within-subject differences from the prealtitude phase for altitude participant and all the data on control participants were used to estimate the analytical SD. The 'true' between-subject response to altitude was estimated from the within-subject differences on altitude participants, between the prealtitude and during-altitude phases, together with the estimated analytical SD. During-altitude Hbmass was estimated to increase by ∼1.1%/100 h for LHTL and classic altitude. Postaltitude Hbmass was estimated to be 3.3% higher than prealtitude values for up to 20 days. The within-subject SD was constant at ∼2% for up to 7 days between observations, indicative of analytical error. A 95% prediction interval for the 'true' response of an athlete exposed to 300 h of altitude was estimated to be 1.1-6%. Camps as short as 2 weeks of classic and LHTL altitude will quite likely increase Hbmass and most athletes can expect benefit.

Mapping Glacier Dynamics and Proglacial Wetlands with a Multispectral UAV at 5000m in the Cordillera Blanca, Peru

Science.gov (United States)

Wigmore, O.; Mark, B. G.

2015-12-01

The glaciers of the Cordillera Blanca, Peru are rapidly retreating as a result of rising temperatures, transforming the hydrology and impacting the socio-economic and environmental systems of the Rio Santa basin. Documenting the heterogeneous spatial patterns of these changes to understand processes of water storage and flow is hindered by technologic and logistic challenges. Highly complex topography, cloud cover and coarse spatial resolution limit the application of satellite data while airborne data collection remains costly and potentially dangerous. However, recent developments have made Unmanned Aerial Vehicle (UAV) technology a viable and potentially transformative method for studying glacier dynamics and proglacial hydrology. The extreme altitudes (4000-6700m) of the Cordillera Blanca limit the use of 'off the shelf' UAVs. Therefore we developed a low cost multispectral (visible, near-infrared and thermal infrared) multirotor UAV capable of conducting fully autonomous aerial surveys at elevations over 5000m within the glacial valleys of the Cordillera Blanca. Using this platform we have completed repeat aerial surveys (in 2014 and 2015) of the debris covered Llaca Glacier, generating highly accurate 10-20cm DEM's and 5cm orthomosaics using a structure from motion workflow. Analysis of these data reveals a highly dynamic system with some areas of the glacier losing as much as 16m of vertical elevation, while other areas have gained up to 5m of elevation over one year. The magnitude and direction of these changes appears to be associated with the presence of debris free ice faces and meltwater ponds. Additionally, we have mapped proglacial meadow and wetland systems. Thermal mosaics at 10-20cm resolution are providing novel insights into the hydrologic pathways of glacier meltwater including mapping the distribution of artesian springs that feed these wetland systems. The high spatial resolution of these UAV datasets facilitates a better understanding of the

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

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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.

Analysis of Landslide Kinematics using Multi-temporal UAV Imagery, La Honda, California

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Carey, J.; Pickering, A.; Prentice, C. S.; Pinter, N.; DeLong, S.

2017-12-01

High-resolution topographic data are vital to studies of earth-surface processes. The combination of unmanned aerial vehicle (UAV) photography and structure-from-motion (SfM) digital photogrammetry provide a quickly deployable and cost-effective method for monitoring geomorphic change and landscape evolution. We acquired imagery of an active landslide in La Honda, California using a GPS-enabled quadcopter UAV with a 12.4 megapixel camera. Deep-seated landslides were previously documented in this region during the winter of 1997-98, with movement recurring and the landslide expanding during the winters of 2004-05 and 2005-06. This study documents the kinematics of a new and separate landslide immediately adjacent to the previous ones, throughout the winter of 2016-17. The roughly triangular-shaped, deep-seated landslide covers an area of approximately 10,000 m2. The area is underlain by SW dipping late Miocene to Pliocene sandstones and mudstones. A 3 m high head scarp stretches along the northeast portion of the slide for approximately 100 m. Internally, the direction of movement is towards the southwest, with two prominent NW-SE striking extensional grabens and numerous tension cracks across the landslide body. Here we calculate displaced landslide volumes and surface displacements from multi-temporal UAV surveys. Photogrammetric reconstruction of UAV/SfM-derived point clouds allowed creation of six digital elevation models (DEMs) with spatial resolutions ranging from 3 to 15 cm per pixel. We derived displacement magnitude, direction and rate by comparing multiple generations of DEMs and orthophotos, and estimated displaced volumes by differencing subsequent DEMs. We then correlated displacements with total rainfall and rainfall intensity measurements. Detailed geomorphic maps identify major landslide features, documenting dominant surface processes. Additionally, we compare the accuracy of the UAV/SfM-derived DEM with a DEM sourced from a synchronous terrestrial

MONITORING PHENOLOGY OF FLOODPLAIN GRASSLAND AND HERBACEOUS VEGETATION WITH UAV IMAGERY

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W. K. van Iersel

2016-06-01

Full Text Available River restoration projects, which aim at improved flood safety and increased ecological value, have resulted in more heterogeneous vegetation. However, they also resulted in increasing hydraulic roughness, which leads to higher flood water levels during peak discharges. Due to allowance of vegetation development and succession, both ecological and hydraulic characteristics of the floodplain change more rapidly over time. Monitoring of floodplain vegetation has become essential to document and evaluate the changing floodplain characteristics and associated functioning. Extraction of characteristics of low vegetation using single-epoch remote sensing data, however, remains challenging. The aim of this study was to (1 evaluate the performance of multi-temporal, high-spatial-resolution UAV imagery for extracting temporal vegetation height profiles of grassland and herbaceous vegetation in floodplains and (2 to assess the relation between height development and NDVI changes. Vegetation height was measured six times during one year in 28 field plots within a single floodplain. UAV true-colour and false-colour imagery of the floodplain were recorded coincidently with each field survey. We found that: (1 the vertical accuracy of UAV normalized digital surface models (nDSMs is sufficiently high to obtain temporal height profiles of low vegetation over a growing season, (2 vegetation height can be estimated from the time series of nDSMs, with the highest accuracy found for combined imagery from February and November (RMSE = 29-42 cm, (3 temporal relations between NDVI and observed vegetation height show different hysteresis behaviour for grassland and herbaceous vegetation. These results show the high potential of using UAV imagery for increasing grassland and herbaceous vegetation classification accuracy.

Towards a Biosynthetic UAV

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Block, Eli; Byemerwa, Jovita; Dispenza, Ross; Doughty, Benjamin; Gillyard, KaNesha; Godbole, Poorwa; Gonzales-Wright, Jeanette; Hull, Ian; Kannappan, Jotthe; Levine, Alexander;

Radar sensing via a Micro-UAV-borne system

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Catapano, Ilaria; Ludeno, Giovanni; Gennarelli, Gianluca; Soldovieri, Francesco; Rodi Vetrella, Amedeo; Fasano, Giancarmine

2017-04-01

In recent years, the miniaturization of flight control systems and payloads has contributed to a fast and widespread diffusion of micro-UAV (Unmanned Aircraft Vehicle). While micro-UAV can be a powerful tool in several civil applications such as environmental monitoring and surveillance, unleashing their full potential for societal benefits requires augmenting their sensing capability beyond the realm of active/passive optical sensors [1]. In this frame, radar systems are drawing attention since they allow performing missions in all-weather and day/night conditions and, thanks to the microwave ability to penetrate opaque media, they enable the detection and localization not only of surface objects but also of sub-surface/hidden targets. However, micro-UAV-borne radar imaging represents still a new frontier, since it is much more than a matter of technology miniaturization or payload installation, which can take advantage of the newly developed ultralight systems. Indeed, micro-UAV-borne radar imaging entails scientific challenges in terms of electromagnetic modeling and knowledge of flight dynamics and control. As a consequence, despite Synthetic Aperture Radar (SAR) imaging is a traditional remote sensing tool, its adaptation to micro-UAV is an open issue and so far only few case studies concerning the integration of SAR and UAV technologies have been reported worldwide [2]. In addition, only early results concerning subsurface imaging by means of an UAV-mounted radar are available [3]. As a contribution to radar imaging via autonomous micro-UAV, this communication presents a proof-of-concept experiment. This experiment represents the first step towards the development of a general methodological approach that exploits expertise about (sub-)surface imaging and aerospace systems with the aim to provide high-resolution images of the surveyed scene. In details, at the conference, we will present the results of a flight campaign carried out by using a single radar

A biomimetic, energy-harvesting, obstacle-avoiding, path-planning algorithm for UAVs

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Gudmundsson, Snorri

This dissertation presents two new approaches to energy harvesting for Unmanned Aerial Vehicles (UAV). One method is based on the Potential Flow Method (PFM); the other method seeds a wind-field map based on updraft peak analysis and then applies a variant of the Bellman-Ford algorithm to find the minimum-cost path. Both methods are enhanced by taking into account the performance characteristics of the aircraft using advanced performance theory. The combined approach yields five possible trajectories from which the one with the minimum energy cost is selected. The dissertation concludes by using the developed theory and modeling tools to simulate the flight paths of two small Unmanned Aerial Vehicles (sUAV) in the 500 kg and 250 kg class. The results show that, in mountainous regions, substantial energy can be recovered, depending on topography and wind characteristics. For the examples presented, as much as 50% of the energy was recovered for a complex, multi-heading, multi-altitude, 170 km mission in an average wind speed of 9 m/s. The algorithms constitute a Generic Intelligent Control Algorithm (GICA) for autonomous unmanned aerial vehicles that enables an extraction of atmospheric energy while completing a mission trajectory. At the same time, the algorithm. automatically adjusts the flight path in order to avoid obstacles, in a fashion not unlike what one would expect from living organisms, such as birds and insects. This multi-disciplinary approach renders the approach biomimetic, i.e. it constitutes a synthetic system that “mimics the formation and function of biological mechanisms and processes.”.

Multisensor Super Resolution Using Directionally-Adaptive Regularization for UAV Images.

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Kang, Wonseok; Yu, Soohwan; Ko, Seungyong; Paik, Joonki

2015-05-22

In various unmanned aerial vehicle (UAV) imaging applications, the multisensor super-resolution (SR) technique has become a chronic problem and attracted increasing attention. Multisensor SR algorithms utilize multispectral low-resolution (LR) images to make a higher resolution (HR) image to improve the performance of the UAV imaging system. The primary objective of the paper is to develop a multisensor SR method based on the existing multispectral imaging framework instead of using additional sensors. In order to restore image details without noise amplification or unnatural post-processing artifacts, this paper presents an improved regularized SR algorithm by combining the directionally-adaptive constraints and multiscale non-local means (NLM) filter. As a result, the proposed method can overcome the physical limitation of multispectral sensors by estimating the color HR image from a set of multispectral LR images using intensity-hue-saturation (IHS) image fusion. Experimental results show that the proposed method provides better SR results than existing state-of-the-art SR methods in the sense of objective measures.

Two NextGen Air Safety Tools: An ADS-B Equipped UAV and a Wake Turbulence Estimator

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Handley, Ward A.

Two air safety tools are developed in the context of the FAA's NextGen program. The first tool addresses the alarming increase in the frequency of near-collisions between manned and unmanned aircraft by equipping a common hobby class UAV with an ADS-B transponder that broadcasts its position, speed, heading and unique identification number to all local air traffic. The second tool estimates and outputs the location of dangerous wake vortex corridors in real time based on the ADS-B data collected and processed using a custom software package developed for this project. The TRansponder based Position Information System (TRAPIS) consists of data packet decoders, an aircraft database, Graphical User Interface (GUI) and the wake vortex extension application. Output from TRAPIS can be visualized in Google Earth and alleviates the problem of pilots being left to imagine where invisible wake vortex corridors are based solely on intuition or verbal warnings from ATC. The result of these two tools is the increased situational awareness, and hence safety, of human pilots in the National Airspace System (NAS).

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...

UAV PHOTOGRAMMETRY: BLOCK TRIANGULATION COMPARISONS

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R. Gini

2013-08-01

Full Text Available UAVs systems represent a flexible technology able to collect a big amount of high resolution information, both for metric and interpretation uses. In the frame of experimental tests carried out at Dept. ICA of Politecnico di Milano to validate vector-sensor systems and to assess metric accuracies of images acquired by UAVs, a block of photos taken by a fixed wing system is triangulated with several software. The test field is a rural area included in an Italian Park ("Parco Adda Nord", useful to study flight and imagery performances on buildings, roads, cultivated and uncultivated vegetation. The UAV SenseFly, equipped with a camera Canon Ixus 220HS, flew autonomously over the area at a height of 130 m yielding a block of 49 images divided in 5 strips. Sixteen pre-signalized Ground Control Points, surveyed in the area through GPS (NRTK survey, allowed the referencing of the block and accuracy analyses. Approximate values for exterior orientation parameters (positions and attitudes were recorded by the flight control system. The block was processed with several software: Erdas-LPS, EyeDEA (Univ. of Parma, Agisoft Photoscan, Pix4UAV, in assisted or automatic way. Results comparisons are given in terms of differences among digital surface models, differences in orientation parameters and accuracies, when available. Moreover, image and ground point coordinates obtained by the various software were independently used as initial values in a comparative adjustment made by scientific in-house software, which can apply constraints to evaluate the effectiveness of different methods of point extraction and accuracies on ground check points.

a Three-Dimensional Simulation and Visualization System for Uav Photogrammetry

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Liang, Y.; Qu, Y.; Cui, T.

2017-08-01

Nowadays UAVs has been widely used for large-scale surveying and mapping. Compared with manned aircraft, UAVs are more cost-effective and responsive. However, UAVs are usually more sensitive to wind condition, which greatly influences their positions and orientations. The flight height of a UAV is relative low, and the relief of the terrain may result in serious occlusions. Moreover, the observations acquired by the Position and Orientation System (POS) are usually less accurate than those acquired in manned aerial photogrammetry. All of these factors bring in uncertainties to UAV photogrammetry. To investigate these uncertainties, a three-dimensional simulation and visualization system has been developed. The system is demonstrated with flight plan evaluation, image matching, POS-supported direct georeferencing, and ortho-mosaicing. Experimental results show that the presented system is effective for flight plan evaluation. The generated image pairs are accurate and false matches can be effectively filtered. The presented system dynamically visualizes the results of direct georeferencing in three-dimensions, which is informative and effective for real-time target tracking and positioning. The dynamically generated orthomosaic can be used in emergency applications. The presented system has also been used for teaching theories and applications of UAV photogrammetry.

Rancang Bangun Prototype Unmanned Aerial Vehicle (UAV dengan Tiga Rotor

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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.

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

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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

Intification and modelling of flight characteristics for self-build shock flyer type UAV

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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.

Multi-UAV Routing for Area Coverage and Remote Sensing with Minimum Time.

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Avellar, Gustavo S C; Pereira, Guilherme A S; Pimenta, Luciano C A; Iscold, Paulo

2015-11-02

This paper presents a solution for the problem of minimum time coverage of ground areas using a group of unmanned air vehicles (UAVs) equipped with image sensors. The solution is divided into two parts: (i) the task modeling as a graph whose vertices are geographic coordinates determined in such a way that a single UAV would cover the area in minimum time; and (ii) the solution of a mixed integer linear programming problem, formulated according to the graph variables defined in the first part, to route the team of UAVs over the area. The main contribution of the proposed methodology, when compared with the traditional vehicle routing problem's (VRP) solutions, is the fact that our method solves some practical problems only encountered during the execution of the task with actual UAVs. In this line, one of the main contributions of the paper is that the number of UAVs used to cover the area is automatically selected by solving the optimization problem. The number of UAVs is influenced by the vehicles' maximum flight time and by the setup time, which is the time needed to prepare and launch a UAV. To illustrate the methodology, the paper presents experimental results obtained with two hand-launched, fixed-wing UAVs.

The use of UAVs for monitoring land degradation

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Themistocleous, Kyriacos

2017-10-01

Land degradation is one of the causes of desertification of drylands in the Mediterranean. UAVs can be used to monitor and document the various variables that cause desertification in drylands, including overgrazing, aridity, vegetation loss, etc. This paper examines the use of UAVs and accompanying sensors to monitor overgrazing, vegetation stress and aridity in the study area. UAV images can be used to generate digital elevation models (DEMs) to examine the changes in microtopography as well as ortho-photos were used to detect changes in vegetation patterns. The combined data of the digital elevation models and the orthophotos can be used to identify the mechanisms for desertification in the study area.

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

UAV-based Radar Sounding of Antarctic Ice

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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

Developing stochastic model of thrust and flight dynamics for small UAVs

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Tjhai, Chandra

This thesis presents a stochastic thrust model and aerodynamic model for small propeller driven UAVs whose power plant is a small electric motor. First a model which relates thrust generated by a small propeller driven electric motor as a function of throttle setting and commanded engine RPM is developed. A perturbation of this model is then used to relate the uncertainty in throttle and engine RPM commanded to the error in the predicted thrust. Such a stochastic model is indispensable in the design of state estimation and control systems for UAVs where the performance requirements of the systems are specied in stochastic terms. It is shown that thrust prediction models for small UAVs are not a simple, explicit functions relating throttle input and RPM command to thrust generated. Rather they are non-linear, iterative procedures which depend on a geometric description of the propeller and mathematical model of the motor. A detailed derivation of the iterative procedure is presented and the impact of errors which arise from inaccurate propeller and motor descriptions are discussed. Validation results from a series of wind tunnel tests are presented. The results show a favorable statistical agreement between the thrust uncertainty predicted by the model and the errors measured in the wind tunnel. The uncertainty model of aircraft aerodynamic coefficients developed based on wind tunnel experiment will be discussed at the end of this thesis.

Multi‐angular observations of vegetation indices from UAV cameras

DEFF Research Database (Denmark)

Sobejano-Paz, Veronica; Wang, Sheng; Jakobsen, Jakob

Unmanned aerial vehicles (UAVs) are found as an alternative to the classical manned aerial photogrammetry, which can be used to obtain environmental data or as a complementary solution to other methods (Nex and Remondino, 2014). Although UAVs have coverage limitations, they have better resolution...... (Berni et al., 2009), hyper spectral camera (Burkart et al., 2015) and photometric elevation mapping sensor (Shahbazi et al., 2015) among others. Therefore, UAVs can be used in many fields such as agriculture, forestry, archeology, architecture, environment and traffic monitoring (Nex and Remondino, 2014......). In this study, the UAV used is a hexacopter s900 equipped with a Global Positioning System (GPS) and two cameras; a digital RGB photo camera and a multispectral camera (MCA), with a resolution of 5472 x 3648 pixels and 1280 x 1024 pixels, respectively. In terms of applications, traditional methods using...

Experiment on Uav Photogrammetry and Terrestrial Laser Scanning for Ict-Integrated Construction

Science.gov (United States)

Takahashi, N.; Wakutsu, R.; Kato, T.; Wakaizumi, T.; Ooishi, T.; Matsuoka, R.

2017-08-01

In the 2016 fiscal year the Ministry of Land, Infrastructure, Transport and Tourism of Japan started a program integrating construction and ICT in earthwork and concrete placing. The new program named "i-Construction" focusing on productivity improvement adopts such new technologies as UAV photogrammetry and TLS. We report a field experiment to investigate whether the procedures of UAV photogrammetry and TLS following the standards for "i-Construction" are feasible or not. In the experiment we measured an embankment of about 80 metres by 160 metres immediately after earthwork was done on the embankment. We used two sets of UAV and camera in the experiment. One is a larger UAV enRoute Zion QC730 and its onboard camera Sony α6000. The other is a smaller UAV DJI Phantom 4 and its dedicated onboard camera. Moreover, we used a terrestrial laser scanner FARO Focus3D X330 based on the phase shift principle. The experiment results indicate that the procedures of UAV photogrammetry using a QC730 with an α6000 and TLS using a Focus3D X330 following the standards for "i-Construction" would be feasible. Furthermore, the experiment results show that UAV photogrammetry using a lower price UAV Phantom 4 was unable to satisfy the accuracy requirement for "i-Construction." The cause of the low accuracy by Phantom 4 is under investigation. We also found that the difference of image resolution on the ground would not have a great influence on the measurement accuracy in UAV photogrammetry.

New Calibration Method Using Low Cost MEM IMUs to Verify the Performance of UAV-Borne MMS Payloads

Directory of Open Access Journals (Sweden)

Kai-Wei Chiang

2015-03-01

Full Text Available Spatial information plays a critical role in remote sensing and mapping applications such as environment surveying and disaster monitoring. An Unmanned Aerial Vehicle (UAV-borne mobile mapping system (MMS can accomplish rapid spatial information acquisition under limited sky conditions with better mobility and flexibility than other means. This study proposes a long endurance Direct Geo-referencing (DG-based fixed-wing UAV photogrammetric platform and two DG modules that each use different commercial Micro-Electro Mechanical Systems’ (MEMS tactical grade Inertial Measurement Units (IMUs. Furthermore, this study develops a novel kinematic calibration method which includes lever arms, boresight angles and camera shutter delay to improve positioning accuracy. The new calibration method is then compared with the traditional calibration approach. The results show that the accuracy of the DG can be significantly improved by flying at a lower altitude using the new higher specification hardware. The new proposed method improves the accuracy of DG by about 20%. The preliminary results show that two-dimensional (2D horizontal DG positioning accuracy is around 5.8 m at a flight height of 300 m using the newly designed tactical grade integrated Positioning and Orientation System (POS. The positioning accuracy in three-dimensions (3D is less than 8 m.

New calibration method using low cost MEM IMUs to verify the performance of UAV-borne MMS payloads.

Science.gov (United States)

Chiang, Kai-Wei; Tsai, Meng-Lun; Naser, El-Sheimy; Habib, Ayman; Chu, Chien-Hsun

2015-03-19

Spatial information plays a critical role in remote sensing and mapping applications such as environment surveying and disaster monitoring. An Unmanned Aerial Vehicle (UAV)-borne mobile mapping system (MMS) can accomplish rapid spatial information acquisition under limited sky conditions with better mobility and flexibility than other means. This study proposes a long endurance Direct Geo-referencing (DG)-based fixed-wing UAV photogrammetric platform and two DG modules that each use different commercial Micro-Electro Mechanical Systems' (MEMS) tactical grade Inertial Measurement Units (IMUs). Furthermore, this study develops a novel kinematic calibration method which includes lever arms, boresight angles and camera shutter delay to improve positioning accuracy. The new calibration method is then compared with the traditional calibration approach. The results show that the accuracy of the DG can be significantly improved by flying at a lower altitude using the new higher specification hardware. The new proposed method improves the accuracy of DG by about 20%. The preliminary results show that two-dimensional (2D) horizontal DG positioning accuracy is around 5.8 m at a flight height of 300 m using the newly designed tactical grade integrated Positioning and Orientation System (POS). The positioning accuracy in three-dimensions (3D) is less than 8 m.

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...

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.

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.

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.

Low-Altitude Aerial Methane Concentration Mapping

Directory of Open Access Journals (Sweden)

Bara J. Emran

2017-08-01

Full Text Available Detection of leaks of fugitive greenhouse gases (GHGs from landfills and natural gas infrastructure is critical for not only their safe operation but also for protecting the environment. Current inspection practices involve moving a methane detector within the target area by a person or vehicle. This procedure is dangerous, time consuming, labor intensive and above all unavailable when access to the desired area is limited. Remote sensing by an unmanned aerial vehicle (UAV equipped with a methane detector is a cost-effective and fast method for methane detection and monitoring, especially for vast and remote areas. This paper describes the integration of an off-the-shelf laser-based methane detector into a multi-rotor UAV and demonstrates its efficacy in generating an aerial methane concentration map of a landfill. The UAV flies a preset flight path measuring methane concentrations in a vertical air column between the UAV and the ground surface. Measurements were taken at 10 Hz giving a typical distance between measurements of 0.2 m when flying at 2 m/s. The UAV was set to fly at 25 to 30 m above the ground. We conclude that besides its utility in landfill monitoring, the proposed method is ready for other environmental applications as well as the inspection of natural gas infrastructure that can release methane with much higher concentrations.

Multidepot UAV Routing Problem with Weapon Configuration and Time Window

Directory of Open Access Journals (Sweden)

Tianren Zhou

2018-01-01

Full Text Available In recent wars, there is an increasing trend that unmanned aerial vehicles (UAVs are utilized to conduct military attacking missions. In this paper, we investigate a novel multidepot UAV routing problem with consideration of weapon configuration in the UAV and the attacking time window of the target. A mixed-integer linear programming model is developed to jointly optimize three kinds of decisions: the weapon configuration strategy in the UAV, the routing strategy of target, and the allocation strategy of weapons to targets. An adaptive large neighborhood search (ALNS algorithm is proposed for solving the problem, which is tested by randomly generated instances covering the small, medium, and large sizes. Experimental results confirm the effectiveness and robustness of the proposed ALNS algorithm.

HIL Tuning of UAV for Exploration of Risky Environments

Directory of Open Access Journals (Sweden)

C. D. Melita

2008-11-01

Full Text Available In this paper the latest results of an HIL architecture, optimized to develop and test UAV platforms are presented. This architecture has been used to realize the different devices involved in the navigation and stability control of the Volcan UAV, a plane designed to operate in volcanic environments. The proposed architecture is strongly modular and flexible and allows the development of avionic hardware and software, testing and tuning the involved algorithms with non-destructive trials. A flight simulator (X-Plane with a suitable plane model and plug-in, has been adopted to simulate the UAV dynamics. The flight simulator, interfaced with the real electronic boards, allows an easy tuning of all the control parameters and data collecting for test and validation. The effectiveness of adopted methodology was confirmed by several flight tests performed subsequently by using the designed avionic modules on the real UAV.

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.

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.

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.

IMPLEMENTATION AND TESTING OF LOW COST UAV PLATFORM FOR ORTHOPHOTO IMAGING

Directory of Open Access Journals (Sweden)

D. Brucas

2013-08-01

Full Text Available Implementation of Unmanned Aerial Vehicles for civilian applications is rapidly increasing. Technologies which were expensive and available only for military use have recently spread on civilian market. There is a vast number of low cost open source components and systems for implementation on UAVs available. Using of low cost hobby and open source components ensures considerable decrease of UAV price, though in some cases compromising its reliability. In Space Science and Technology Institute (SSTI in collaboration with Vilnius Gediminas Technical University (VGTU researches have been performed in field of constructing and implementation of small UAVs composed of low cost open source components (and own developments. Most obvious and simple implementation of such UAVs – orthophoto imaging with data download and processing after the flight. The construction, implementation of UAVs, flight experience, data processing and data implementation will be further covered in the paper and presentation.

Implementation and Testing of Low Cost Uav Platform for Orthophoto Imaging

Science.gov (United States)

Brucas, D.; Suziedelyte-Visockiene, J.; Ragauskas, U.; Berteska, E.; Rudinskas, D.

2013-08-01

Implementation of Unmanned Aerial Vehicles for civilian applications is rapidly increasing. Technologies which were expensive and available only for military use have recently spread on civilian market. There is a vast number of low cost open source components and systems for implementation on UAVs available. Using of low cost hobby and open source components ensures considerable decrease of UAV price, though in some cases compromising its reliability. In Space Science and Technology Institute (SSTI) in collaboration with Vilnius Gediminas Technical University (VGTU) researches have been performed in field of constructing and implementation of small UAVs composed of low cost open source components (and own developments). Most obvious and simple implementation of such UAVs - orthophoto imaging with data download and processing after the flight. The construction, implementation of UAVs, flight experience, data processing and data implementation will be further covered in the paper and presentation.

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.

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.

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.

Automatic Generation of Complex Spatial Trajectories of the UAV and Synthesis of Control

Directory of Open Access Journals (Sweden)

S. B. Tkachev

2015-01-01

Full Text Available In this paper, we propose a new method and algorithms that allow us to design complex spatial trajectories for an unmanned aerial vehicle (UAV passing through a given sequence of waypoints in the three-dimensional space.The nonlinear six-dimensional model of the UAV center-of-mass motion given in the trajectory frame is used for calculations. The state vector includes the altitude, the along-track deviation, the cross-track position, the velocity, the flight-path angle and the heading angle. The longitudinal and transverse overloads and the angle between the cross overload vector and vertical plane are considered as controls. This angle is often named as the roll angle.The feature of the problem is that both positions at waypoints and additional conditions are given. These conditions determine orientation of the velocity vector at each point (using the flight path angle and the heading angle. We also set either the point-visiting time or the pointvisiting velocity. The full state vector and controls are fixed at the starting waypoint.To construct a spatial trajectory, the concept of inverse dynamics problems is applied, as well as modern results of mathematical control theory of nonlinear dynamical systems. The introduction of new virtual controls allows us to represent the original system as an affine (linear in control system. Then, the designed system is converted into the regular canonical form.When we set flight times between any two waypoints, the corresponding segments of the trajectory are designed using time-dependent polynomials of the fifth degree. These polynomials specify the altitude variation, the variation of the along-track deviation and that of the cross-track position. If the point-visiting times are not fixed, the transition to a new independent variable (the normalized mechanical energy of the system is used. This transition is possible if the energy varies monotonically. In this case, the spatial trajectory is defined as a

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.

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...

Evapotranspiration from UAV Images

DEFF Research Database (Denmark)

Nielsen, Helene Hoffmann Munk

and is thus of importance in both hydrological, agricultural and atmospheric sciences. Still today, accurate measurements of ET are not achieved easily. The state-of the-art method to measure ET, the eddy covariance method, is associated with uncertainties and its footprint, though at the order of around 1...... hectare, varies much with the atmospheric stability and wind conditions. Indirect measurements of ET are obtained with satellite imagery, as a residual of the surface energy balance. Satellite images provide spatially distributed measurements, however high resolution satellite products provide footprints...... of measurements and thus new understandings of ET and its inferred parameters such as crop water stress and heat fluxes in the surface energy balance. However, UAV data collection is a new measuring method and the lightweight sensors are novel instrumentations. Workflows for processing UAV data, and the data...

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.

Using UAV photogrammetry to study topographic change: application to Saskatchewan Glacier, Alberta, Canada

Science.gov (United States)

Meunier Cardinal, G.; Demuth, M. N.; Kinnard, C.

2016-12-01

Glaciers are an important source of fresh water in the headwaters of the Canadian Rocky Mountains, and ongoing climate warming could reduce their future hydrological contribution. Unmanned Aerial Vehicles UAVs) are an emergent technology that allow studying glacial processes with an unprecedented level of detail, but their usefulness for deriving accurate topographic data on glaciers has not yet been fully assessed. In this perspective we tested the use of a UAV platform to acquire images at a very high spatial resolution (using the Structure from Motion (SfM) algorithm. A detailed assessment of DEM errors was performed by cross-validation of an network of ground control points (GCPs) deployed on the glacier surface. The influence of checkpoint position in the network, border effects, number of photos calibrated and GPS accuracy were examined. Topographical changes were measured from the DEM difference and surface displacements estimated by applying feature tracking techniques to the orthomosaics. Further, the dominant scales of topographic spatial variability were examined using a semivariogram analysis of the DEMs. Results show that UAV-based photogrammetry is promising to further our understanding of high-resolution glacier surface processes and to perform repeat, on-demand monitoring of glacier changes, but their application on remote glaciers remains challenging.

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 ...

UAV-Borne Profiling Radar for Forest Research

Directory of Open Access Journals (Sweden)

Yuwei Chen

2017-01-01

Full Text Available Microwave Radar is an attractive solution for forest mapping and inventories because microwave signals penetrates into the forest canopy and the backscattering signal can provide information regarding the whole forest structure. Satellite-borne and airborne imaging radars have been used in forest resources mapping for many decades. However, their accuracy with respect to the main forest inventory attributes substantially varies depending on the wavelength and techniques used in the estimation. Systems providing canopy backscatter as a function of canopy height are, practically speaking, missing. Therefore, there is a need for a radar system that would enable the scientific community to better understand the radar backscatter response from the forest canopy. Consequently, we undertook a research study to develop an unmanned aerial vehicle (UAV-borne profiling (i.e., waveform radar that could be used to improve the understanding of the radar backscatter response for forestry mapping and inventories. A frequency modulation continuous waveform (FMCW profiling radar, termed FGI-Tomoradar, was introduced, designed and tested. One goal is the total weight of the whole system is less than 7 kg, including the radar system and georeferencing system, with centimetre-level positioning accuracy. Achieving this weight goal would enable the FGI-Tomoradar system to be installed on the Mini-UAV platform. The prototype system had all four linear polarization measuring capabilities, with bistatic configuration in Ku-band. In system performance tests in this study, FGI-Tomoradar was mounted on a manned helicopter together with a Riegl VQ-480-U laser scanner and tested in several flight campaigns performed at the Evo site, Finland. Airborne laser scanning data was simultaneously collected to investigate the differences and similarities of the outputs for the same target area for better understanding the penetration of the microwave signal into the forest canopy

Adoption of an unmanned helicopter for low-altitude remote sensing to estimate yield and total biomass of a rice crop

Science.gov (United States)

A radio-controlled unmanned helicopter-based LARS (Low-Altitude Remote Sensing) platform was used to acquire quality images of high spatial and temporal resolution, in order to estimate yield and total biomass of a rice crop (Oriza Sativa, L.). Fifteen rice field plots with five N-treatments (0, 33,...

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.

Control of fixed-wing UAV at levelling phase using artificial intelligence

Science.gov (United States)

Sayfeddine, Daher

2018-03-01

The increase in the share of fly-by-wire and software controlled UAV is explained by the need to release the human-operator and the desire to reduce the degree of influence of the human factor errors that account for 26% of aircraft accidents. An important reason for the introduction of new control algorithms is also the high level of UAV failures due loss of communication channels and possible hacking. This accounts for 17% of the total number of accidents. The comparison with manned flights shows that the frequency of accidents of unmanned flights is 27,000 times higher. This means that the UAV has 1611 failures per million flight hours and only 0.06 failures at the same time for the manned flight. In view of that, this paper studies the flight autonomy of fixed-wing UAV at the levelling phase. Landing parameters of the UAV are described. They will be used to setup a control scheme for an autopilot based on fuzzy logic algorithm.

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...

A Survey of Open-Source UAV Flight Controllers and Flight Simulators

DEFF Research Database (Denmark)

Ebeid, Emad Samuel Malki; Skriver, Martin; Terkildsen, Kristian Husum

2018-01-01

The current disruptive innovation in civilian drone (UAV) applications has led to an increased need for research and development in UAV technology. The key challenges currently being addressed are related to UAV platform properties such as functionality, reliability, fault tolerance, and endurance......-source drone platform elements that can be used for research and development. The survey covers open-source hardware, software, and simulation drone platforms and compares their main features....

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.

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

Interactive Cadastral Boundary Delineation from Uav Data

Science.gov (United States)

Crommelinck, S.; Höfle, B.; Koeva, M. N.; Yang, M. Y.; Vosselman, G.

2018-05-01

Unmanned aerial vehicles (UAV) are evolving as an alternative tool to acquire land tenure data. UAVs can capture geospatial data at high quality and resolution in a cost-effective, transparent and flexible manner, from which visible land parcel boundaries, i.e., cadastral boundaries are delineable. This delineation is to no extent automated, even though physical objects automatically retrievable through image analysis methods mark a large portion of cadastral boundaries. This study proposes (i) a methodology that automatically extracts and processes candidate cadastral boundary features from UAV data, and (ii) a procedure for a subsequent interactive delineation. Part (i) consists of two state-of-the-art computer vision methods, namely gPb contour detection and SLIC superpixels, as well as a classification part assigning costs to each outline according to local boundary knowledge. Part (ii) allows a user-guided delineation by calculating least-cost paths along previously extracted and weighted lines. The approach is tested on visible road outlines in two UAV datasets from Germany. Results show that all roads can be delineated comprehensively. Compared to manual delineation, the number of clicks per 100 m is reduced by up to 86 %, while obtaining a similar localization quality. The approach shows promising results to reduce the effort of manual delineation that is currently employed for indirect (cadastral) surveying.

Establishing a disruptive new capability for NASA to fly UAV's into hazardous conditions

Science.gov (United States)

Ely, Jay; Nguyen, Truong; Wilson, Jennifer; Brown, Robert; Laughter, Sean; Teets, Ed; Parker, Allen; Chan, Hon M.; Richards, Lance

2015-05-01

A 2015 NASA Aeronautics Mission "Seedling" Proposal is described for a Severe-Environment UAV (SE-UAV) that can perform in-situ measurements in hazardous atmospheric conditions like lightning, volcanic ash and radiation. Specifically, this paper describes the design of a proof-of-concept vehicle and measurement system that can survive lightning attachment during flight operations into thunderstorms. Elements from three NASA centers draw together for the SE-UAV concept. 1) The NASA KSC Genesis UAV was developed in collaboration with the DARPA Nimbus program to measure electric field and X-rays present within thunderstorms. 2) A novel NASA LaRC fiber-optic sensor uses Faraday-effect polarization rotation to measure total lightning electric current on an air vehicle fuselage. 3) NASA AFRC's state-of-the-art Fiber Optics and Systems Integration Laboratory is envisioned to transition the Faraday system to a compact, light-weight, all-fiber design. The SE-UAV will provide in-flight lightning electric-current return stroke and recoil leader data, and serve as a platform for development of emerging sensors and new missions into hazardous environments. NASA's Aeronautics and Science Missions are interested in a capability to perform in-situ volcanic plume measurements and long-endurance UAV operations in various weather conditions. (Figure 1 shows an artist concept of a SE-UAV flying near a volcano.) This paper concludes with an overview of the NASA Aeronautics Strategic Vision, Programs, and how a SE-UAV is envisioned to impact them. The SE-UAV concept leverages high-value legacy research products into a new capability for NASA to fly a pathfinder UAV into hazardous conditions, and is presented in the SPIE DSS venue to explore teaming, collaboration and advocacy opportunities outside NASA.

Establishing a Disruptive New Capability for NASA to Fly UAV's into Hazardous Conditions

Science.gov (United States)

Ely, Jay; Nguyen, Truong; Wilson, Jennifer; Brown, Robert; Laughter, Sean; Teets, Ed; Parker, Allen; Chan, Patrick Hon Man; Richards, Lance

2015-01-01

A 2015 NASA Aeronautics Mission "Seedling" Proposal is described for a Severe-Environment UAV (SE-UAV) that can perform in-situ measurements in hazardous atmospheric conditions like lightning, volcanic ash and radiation. Specifically, this paper describes the design of a proof-of-concept vehicle and measurement system that can survive lightning attachment during flight operations into thunderstorms. Elements from three NASA centers draw together for the SE-UAV concept. 1) The NASA KSC Genesis UAV was developed in collaboration with the DARPA Nimbus program to measure electric field and X-rays present within thunderstorms. 2) A novel NASA LaRC fiber-optic sensor uses Faraday-effect polarization rotation to measure total lightning electric current on an air vehicle fuselage. 3) NASA AFRC's state-of-the-art Fiber Optics and Systems Integration Laboratory is envisioned to transition the Faraday system to a compact, light-weight, all-fiber design. The SE-UAV will provide in-flight lightning electric-current return stroke and recoil leader data, and serve as a platform for development of emerging sensors and new missions into hazardous environments. NASA's Aeronautics and Science Missions are interested in a capability to perform in-situ volcanic plume measurements and long-endurance UAV operations in various weather conditions. (Figure 1 shows an artist concept of a SE-UAV flying near a volcano.) This paper concludes with an overview of the NASA Aeronautics Strategic Vision, Programs, and how a SE-UAV is envisioned to impact them. The SE-UAV concept leverages high-value legacy research products into a new capability for NASA to fly a pathfinder UAV into hazardous conditions, and is presented in the SPIE DSS venue to explore teaming, collaboration and advocacy opportunities outside NASA.

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.

Design of attitude solution algorithm for tail-sitter VTOL UAV

Directory of Open Access Journals (Sweden)

Donghui LIU

2016-02-01

Full Text Available The tail-sitter Vertical Takeoff and Landing (VTOL Unmanned Aerial Vehicle(UAV, flying in a fixed-wing model, overcomes many shortcomings of traditional fixed-wing UAVs, and inherits the advantage of high overall efficiency, which means it has great development potential and very broad application prospects. The attitude of tail-sitter VTOL UAV shows a wide change range in its takeoff and landing stages, and when the attitude sensor changes more than 90 degrees in pitch direction, the Euler angles converted by the Quaternions will have singular points, which means gimbal deadlock appears. From the solution algorithm, this paper provides a method of changing the order of rotation to avoid the appearance of singular points. The results show that this method can be well applied to the attitude solution of the VTOL UAV.

Generació de mapes a partir d'imatges preses amb un UAV

OpenAIRE

Perarnau, Guim; Universitat Autònoma de Barcelona. Escola d'Enginyeria

2015-01-01

En els darrers anys s'ha popularitzat l'ús dels UAVs (drones) en una gran varietat d'àmbits. Aquest treball se centra en el camp de generació de mapes (vistes àrees) òptima basat en imatges enregistrades amb un UAV. Per millorar la qualitat del mapa resultant es vol treure profit de la instal•lació de sensors en l'UAV que proporcionin informació que pugui ser útil en el procés, com la posició i l'orientació de l'UAV. Com a tal, es descriuran tots els passos emprats per tal d'aprofitar les dad...

Analysis of Nondeterministic Search Patterns for Minimization of UAV Counter-Targeting

Science.gov (United States)

2013-03-01

64 Figure 4.9 Procerus Unicorn UAV [48] used in multi-UAV look-ahead Levy search demonstration conducted at 13-2 JIFX in February, 2013...minimum time or coverage path, minimal overlap, increased robustness to localization errors, etc. [3–5]. The role of randomized coverage and search...to the Procerus Unicorn UAV employed during these flight experiments, shown in Figure 4.9. Figure 4.10 shows the straight-line path between the major

Subpixel Inundation Mapping Using Landsat-8 OLI and UAV Data for a Wetland Region on the Zoige Plateau, China

Directory of Open Access Journals (Sweden)

Haoming Xia

2017-01-01

Full Text Available Wetland inundation is crucial to the survival and prosperity of fauna and flora communities in wetland ecosystems. Even small changes in surface inundation may result in a substantial impact on the wetland ecosystem characteristics and function. This study presented a novel method for wetland inundation mapping at a subpixel scale in a typical wetland region on the Zoige Plateau, northeast Tibetan Plateau, China, by combining use of an unmanned aerial vehicle (UAV and Landsat-8 Operational Land Imager (OLI data. A reference subpixel inundation percentage (SIP map at a Landsat-8 OLI 30 m pixel scale was first generated using high resolution UAV data (0.16 m. The reference SIP map and Landsat-8 OLI imagery were then used to develop SIP estimation models using three different retrieval methods (Linear spectral unmixing (LSU, Artificial neural networks (ANN, and Regression tree (RT. Based on observations from 2014, the estimation results indicated that the estimation model developed with RT method could provide the best fitting results for the mapping wetland SIP (R2 = 0.933, RMSE = 8.73% compared to the other two methods. The proposed model with RT method was validated with observations from 2013, and the estimated SIP was highly correlated with the reference SIP, with an R2 of 0.986 and an RMSE of 9.84%. This study highlighted the value of high resolution UAV data and globally and freely available Landsat data in combination with the developed approach for monitoring finely gradual inundation change patterns in wetland ecosystems.

[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.

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

Short Communication. Using high resolution UAV imagery to estimate tree variables in Pinus pinea plantation in Portugal

Directory of Open Access Journals (Sweden)

Juan Guerra Hernandez

2016-07-01

Research highlights: The results demonstrate that tree variables can be automatically extracted from high resolution imagery. We highlight the use of UAV systems as a fast, reliable and cost‑effective technique for small scale applications. Keywords: Unmanned aerial systems (UAS; forest inventory; tree crown variables; 3D image modelling; canopy height model (CHM; object‑based image analysis (OBIA, structure‑from‑motion (SfM.

A quantitative analysis of TIMS data obtained on the Learjet 23 at various altitudes

Science.gov (United States)

Jaggi, S.

1992-01-01

A series of Thermal Infrared Multispectral Scanner (TIMS) data acquisition flights were conducted on the NASA Learjet 23 at different altitudes over a test site. The objective was to monitor the performance of the TIMS (its estimation of the brightness temperatures of the ground scene) with increasing altitude. The results do not show any significant correlation between the brightness temperatures and the altitude. The analysis indicates that the estimation of the temperatures is a function of the accuracy of the atmospheric correction used for each altitude.

Tracking, aiming, and hitting the UAV with ordinary assault rifle

Science.gov (United States)

Racek, František; Baláž, Teodor; Krejčí, Jaroslav; Procházka, Stanislav; Macko, Martin

2017-10-01

The usage small-unmanned aerial vehicles (UAVs) is significantly increasing nowadays. They are being used as a carrier of military spy and reconnaissance devices (taking photos, live video streaming and so on), or as a carrier of potentially dangerous cargo (intended for destruction and killing). Both ways of utilizing the UAV cause the necessity to disable it. From the military point of view, to disable the UAV means to bring it down by a weapon of an ordinary soldier that is the assault rifle. This task can be challenging for the soldier because he needs visually detect and identify the target, track the target visually and aim on the target. The final success of the soldier's mission depends not only on the said visual tasks, but also on the properties of the weapon and ammunition. The paper deals with possible methods of prediction of probability of hitting the UAV targets.

Pathloss Measurements and Modeling for UAVs Connected to Cellular Networks

DEFF Research Database (Denmark)

Amorim, Rafhael Medeiros de; Mogensen, Preben Elgaard; Sørensen, Troels Bundgaard

2017-01-01

. The measurements were conducted in an operating LTE network (850 MHz), using a commercial cell phone, placed inside the frame of the UAV. Trials were conducted for UAV flying at 5 different heights measured above ground level (20, 40, 60, 80 and 100m) and a pathloss regression line was obtained from results. Then......This paper assess field measurements, as part of the investigation of the suitability of cellular networks for providing connectivity to UAVs (unmanned aerial vehicles). Evaluation is done by means of field measurements obtained in a rural environment in Denmark with an airbone UAV......, downlink (DL) SINR levels obtained during flight measurements are also presented. An important result obtained from the measurents reveal that there is a height-related DL SINR degradation. Three main sources of uncertainty on the pathloss model that could be responsible for the SINR degradation are also...

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.

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.

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

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.

Coastal areas mapping using UAV photogrammetry

Science.gov (United States)

Nikolakopoulos, Konstantinos G.; Kozarski, Dimitrios; Kogkas, Stefanos

2017-10-01

The coastal areas in the Patras Gulf suffer degradation due to the sea action and other natural and human-induced causes. Changes in beaches, ports, and other man made constructions need to be assessed, both after severe events and on a regular basis, to build models that can predict the evolution in the future. Thus, reliable spatial data acquisition is a critical process for the identification of the coastline and the broader coastal zones for geologists and other scientists involved in the study of coastal morphology. High resolution satellite data, airphotos and airborne Lidar provided in the past the necessary data for the coastline monitoring. High-resolution digital surface models (DSMs) and orthophoto maps had become a necessity in order to map with accuracy all the variations in costal environments. Recently, unmanned aerial vehicles (UAV) photogrammetry offers an alternative solution to the acquisition of high accuracy spatial data along the coastline. This paper presents the use of UAV to map the coastline in Rio area Western Greece. Multiple photogrammetric aerial campaigns were performed. A small commercial UAV (DJI Phantom 3 Advance) was used to acquire thousands of images with spatial resolutions better than 5 cm. Different photogrammetric software's were used to orientate the images, extract point clouds, build a digital surface model and produce orthoimage mosaics. In order to achieve the best positional accuracy signalised ground control points were measured with a differential GNSS receiver. The results of this coastal monitoring programme proved that UAVs can replace many of the conventional surveys, with considerable gains in the cost of the data acquisition and without any loss in the accuracy.

Development and Testing of a Low-Cost Instrumentation Platform for Fixed-Wing UAV Performance Analysis

Directory of Open Access Journals (Sweden)

Tulio Dapper e Silva

2018-05-01

Full Text Available The flight data of a fixed-wing Unmanned Aerial Vehicle (UAV can be evaluated by its designers in order to analyze its performance, to validate the project criteria and to make new decisions based on the data analyses. In this paper, the authors propose the development of a low-cost instrumentation platform capable of collecting the following data: airspeed, orientation and altitude of the airplane, and the current drained by the electric system. Moreover, this paper presents the use of a telemetry system in order to display the flight conditions to the pilot. The system contains a variety of sensors, which were chosen based on their price, applicability and ease of use. After a test flight had been performed, the collected measurements were plotted and analyzed. Having the flight data, a set of flight characteristics might be observed.

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

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.

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.

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.

Teaching UAVs to Race With Observational Imitation Learning

KAUST Repository

Li, Guohao; Mueller, Matthias; Casser, Vincent; Smith, Neil; Michels, Dominik L.; Ghanem, Bernard

2018-01-01

Recent work has tackled the problem of autonomous navigation by imitating a teacher and learning an end-to-end policy, which directly predicts controls from raw images. However, these approaches tend to be sensitive to mistakes by the teacher and do not scale well to other environments or vehicles. To this end, we propose a modular network architecture that decouples perception from control, and is trained using Observational Imitation Learning (OIL), a novel imitation learning variant that supports online training and automatic selection of optimal behavior from observing multiple teachers. We apply our proposed methodology to the challenging problem of unmanned aerial vehicle (UAV) racing. We develop a simulator that enables the generation of large amounts of synthetic training data (both UAV captured images and its controls) and also allows for online learning and evaluation. We train a perception network to predict waypoints from raw image data and a control network to predict UAV controls from these waypoints using OIL. Our modular network is able to autonomously fly a UAV through challenging race tracks at high speeds. Extensive experiments demonstrate that our trained network outperforms its teachers, end-to-end baselines, and even human pilots in simulation. The supplementary video can be viewed at https://youtu.be/PeTXSoriflc

Teaching UAVs to Race With Observational Imitation Learning

KAUST Repository

Li, Guohao

2018-03-03

Recent work has tackled the problem of autonomous navigation by imitating a teacher and learning an end-to-end policy, which directly predicts controls from raw images. However, these approaches tend to be sensitive to mistakes by the teacher and do not scale well to other environments or vehicles. To this end, we propose a modular network architecture that decouples perception from control, and is trained using Observational Imitation Learning (OIL), a novel imitation learning variant that supports online training and automatic selection of optimal behavior from observing multiple teachers. We apply our proposed methodology to the challenging problem of unmanned aerial vehicle (UAV) racing. We develop a simulator that enables the generation of large amounts of synthetic training data (both UAV captured images and its controls) and also allows for online learning and evaluation. We train a perception network to predict waypoints from raw image data and a control network to predict UAV controls from these waypoints using OIL. Our modular network is able to autonomously fly a UAV through challenging race tracks at high speeds. Extensive experiments demonstrate that our trained network outperforms its teachers, end-to-end baselines, and even human pilots in simulation. The supplementary video can be viewed at https://youtu.be/PeTXSoriflc

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.

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.

Distinguishing plant population and variety with UAV-derived vegetation indices

Science.gov (United States)

Oakes, Joseph; Balota, Maria

2017-05-01

Variety selection and seeding rate are two important choice that a peanut grower must make. High yielding varieties can increase profit with no additional input costs, while seeding rate often determines input cost a grower will incur from seed costs. The overall purpose of this study was to examine the effect that seeding rate has on different peanut varieties. With the advent of new UAV technology, we now have the possibility to use indices collected with the UAV to measure emergence, seeding rate, growth rate, and perhaps make yield predictions. This information could enable growers to make management decisions early in the season based on low plant populations due to poor emergence, and could be a useful tool for growers to use to estimate plant population and growth rate in order to help achieve desired crop stands. Red-Green-Blue (RGB) and near-infrared (NIR) images were collected from a UAV platform starting two weeks after planting and continued weekly for the next six weeks. Ground NDVI was also collected each time aerial images were collected. Vegetation indices were derived from both the RGB and NIR images. Greener area (GGA- the proportion of green pixels with a hue angle from 80° to 120°) and a* (the average red/green color of the image) were derived from the RGB images while Normalized Differential Vegetative Index (NDVI) was derived from NIR images. Aerial indices were successful in distinguishing seeding rates and determining emergence during the first few weeks after planting, but not later in the season. Meanwhile, these aerial indices are not an adequate predictor of yield in peanut at this point.

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.

MISSION-ORIENTED SENSOR ARRAYS AND UAVs – A CASE STUDY ON ENVIRONMENTAL MONITORING

Directory of Open Access Journals (Sweden)

N. M. Figueira

2015-08-01

Full Text Available This paper presents a new concept of UAV mission design in geomatics, applied to the generation of thematic maps for a multitude of civilian and military applications. We discuss the architecture of Mission-Oriented Sensors Arrays (MOSA, proposed in Figueira et Al. (2013, aimed at splitting and decoupling the mission-oriented part of the system (non safety-critical hardware and software from the aircraft control systems (safety-critical. As a case study, we present an environmental monitoring application for the automatic generation of thematic maps to track gunshot activity in conservation areas. The MOSA modeled for this application integrates information from a thermal camera and an on-the-ground microphone array. The use of microphone arrays technology is of particular interest in this paper. These arrays allow estimation of the direction-of-arrival (DOA of the incoming sound waves. Information about events of interest is obtained by the fusion of the data provided by the microphone array, captured by the UAV, fused with information from the termal image processing. Preliminary results show the feasibility of the on-the-ground sound processing array and the simulation of the main processing module, to be embedded into an UAV in a future work. The main contributions of this paper are the proposed MOSA system, including concepts, models and architecture.

APPLICABILITY ANALYSIS OF ULTRA-LIGHT UAV FOR FLOODING SITE SURVEY IN SOUTH KOREA

Directory of Open Access Journals (Sweden)

I. Lee

2013-05-01

Full Text Available Recently, UAV (Unmanned Aerial Vehicle is used in a variety of fields such as the military service, fire prevention, traffic supervision, mapping, and etc. The increased demand for UAVs is typically attributed to the low manufacturing and operational costs, flexibility of the platforms to accommodate the consumer’s particular needs and the elimination of the risk to pilots’ lives in difficult missions. But, in South Korea, UAV might be first introduced to military service, and is still in its infancy, just being available for construction site monitoring, landscape photographing, spraying agricultural chemicals, broadcasting fields. This study presents the background and the aim of flood mapping, and presents the possibility analysis of how to use UAV effectively for flooding area. And author tries to overlap UAV image with the flooding area trace surveyed by ground surveys. As a result, it is expected that UAV photogrammetry will contributes to investigating the flooded area by providing images, which is describing the flooded area in near real-time and also making a decision like paying compensation.

EVALUATION OF THE QUALITY OF ACTION CAMERAS WITH WIDE-ANGLE LENSES IN UAV PHOTOGRAMMETRY

OpenAIRE

Hastedt, H.; Ekkel, T.; Luhmann, T.

2016-01-01

The application of light-weight cameras in UAV photogrammetry is required due to restrictions in payload. In general, consumer cameras with normal lens type are applied to a UAV system. The availability of action cameras, like the GoPro Hero4 Black, including a wide-angle lens (fish-eye lens) offers new perspectives in UAV projects. With these investigations, different calibration procedures for fish-eye lenses are evaluated in order to quantify their accuracy potential in UAV photogrammetry....

Possibilities of Use of UAVS for Technical Inspection of Buildings and Constructions

Science.gov (United States)

Banaszek, Anna; Banaszek, Sebastian; Cellmer, Anna

2017-12-01

In recent years, Unmanned Aerial Vehicles (UAVs) have been used in various sectors of the economy. This is due to the development of new technologies for acquiring and processing geospatial data. The paper presents the results of experiments using UAV, equipped with a high resolution digital camera, for a visual assessment of the technical condition of the building roof and for the inventory of energy infrastructure and its surroundings. The usefulness of digital images obtained from the UAV deck is presented in concrete examples. The use of UAV offers new opportunities in the area of technical inspection due to the detail and accuracy of the data, low operating costs and fast data acquisition.

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...

Atmospheric electron flux at airplane altitude

International Nuclear Information System (INIS)

Enomoto, R.; Chiba, J.; Ogawa, K.; Sumiyoshi, T.; Takasaki, F.; Kifune, T.; Matsubara, Y.; Nishimura, J.

1991-01-01

We have developed a new detector to systematically measure the cosmic-ray electron flux at airplane altitudes. We loaded a lead-glass-based electron telescope onto a commercial cargo airplane. The first experiment was carried out using the air route between Narita (Japan) and Sydney (Australia); during this flight we measured the electron flux at various altitudes and latitudes. The thresholds of the electron energies were 1, 2, and 4 GeV. The results agree with a simple estimation using one-dimensional shower theory. A comparison with a Monte Carlo calculation was made

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

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...

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.

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.

Quantifying altitude of human habitation in studies of human health using geographical name server data

Directory of Open Access Journals (Sweden)

Stephen Thielke

2016-11-01

Full Text Available Almost all studies examining the effects of altitude on human health have estimated the geographical altitude of defined regions, yet the primary interest lies in where people live, not the land around them. Populations are not homogenously distributed across altitudes. We propose a straightforward and computationally simple method for estimating the average altitude of habitation within the regional units for which health statistics are typically reported (such as counties. The United States Board on Geographical Names database contains records for over 2.7 million places, which can be processed to select places that are associated with human habitation. These points can easily be averaged by region yielding a representative altitude of human habitation within city, county, state regions, or by longitude and latitude zones. We provide an example of using this approach in a study of human health, and compare it with three other previously used methods of estimating altitude for counties.

Assessing UAV platform types and optical sensor specifications

Science.gov (United States)

Altena, B.; Goedemé, T.

2014-05-01

Photogrammetric acquisition with unmanned aerial vehicles (UAV) has grown extensively over the last couple of years. Such mobile platforms and their processing software have matured, resulting in a market which offers off-the-shelf mapping solutions to surveying companies and geospatial enterprises. Different approaches in platform type and optical instruments exist, though its resulting products have similar specifications. To demonstrate differences in acquisitioning practice, a case study over an open mine was flown with two different off-the-shelf UAVs (a fixed-wing and a multi-rotor). The resulting imagery is analyzed to clarify the differences in collection quality. We look at image settings, and stress the fact of photographic experience if manual setting are applied. For mapping production it might be safest to set the camera on automatic. Furthermore, we try to estimate if blur is present due to image motion. A subtle trend seems to be present, for the fast flying platform though its extent is of similar order to the slow moving one. It shows both systems operate at their limits. Finally, the lens distortion is assessed with special attention to chromatic aberration. Here we see that through calibration such aberrations could be present, however detecting this phenomena directly on imagery is not straightforward. For such effects a normal lens is sufficient, though a better lens and collimator does give significant improvement.

Comparison of a UAV-derived point-cloud to Lidar data at Haig Glacier, Alberta, Canada

Science.gov (United States)

Bash, E. A.; Moorman, B.; Montaghi, A.; Menounos, B.; Marshall, S. J.

2016-12-01

The use of unmanned aerial vehicles (UAVs) is expanding rapidly in glaciological research as a result of technological improvements that make UAVs a cost-effective solution for collecting high resolution datasets with relative ease. The cost and difficult access traditionally associated with performing fieldwork in glacial environments makes UAVs a particularly attractive tool. In the small, but growing, body of literature using UAVs in glaciology the accuracy of UAV data is tested through the comparison of a UAV-derived DEM to measured control points. A field campaign combining simultaneous lidar and UAV flights over Haig Glacier in April 2015, provided the unique opportunity to directly compare UAV data to lidar. The UAV was a six-propeller Mikrokopter carrying a Panasonic Lumix DMC-GF1 camera with a 12 Megapixel Live MOS sensor and Lumix G 20 mm lens flown at a height of 90 m, resulting in sub-centimetre ground resolution per image pixel. Lidar data collection took place April 20, while UAV flights were conducted April 20-21. A set of 65 control points were laid out and surveyed on the glacier surface on April 19 and 21 using a RTK GPS with a vertical uncertainty of 5 cm. A direct comparison of lidar points to these control points revealed a 9 cm offset between the control points and the lidar points on average, but the difference changed distinctly from points collected on April 19 versus those collected April 21 (7 cm and 12 cm). Agisoft Photoscan was used to create a point-cloud from imagery collected with the UAV and CloudCompare was used to calculate the difference between this and the lidar point cloud, revealing an average difference of less than 17 cm. This field campaign also highlighted some of the benefits and drawbacks of using a rotary UAV for glaciological research. The vertical takeoff and landing capabilities, combined with quick responsiveness and higher carrying capacity, make the rotary vehicle favourable for high-resolution photos when

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

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

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.

Technologies Advance UAVs for Science, Military

Science.gov (United States)

2010-01-01

A Space Act Agreement with Goddard Space Flight Center and West Virginia University enabled Aurora Flight Sciences Corporation, of Manassas, Virginia, to develop cost-effective composite manufacturing capabilities and open a facility in West Virginia. The company now employs 160 workers at the plant, tasked with crafting airframe components for the Global Hawk unmanned aerial vehicle (UAV) program. While one third of the company's workforce focuses on Global Hawk production, the rest of the company develops advanced UAV technologies that are redefining traditional approaches to unmanned aviation. Since the company's founding, Aurora s cutting-edge work has been supported with funding from NASA's Small Business Innovation Research (SBIR) and Small Business Technology Transfer (STTR) programs.

Quantifying Boreal Forest Structure and Composition Using UAV Structure from Motion

Directory of Open Access Journals (Sweden)

Michael Alonzo

2018-03-01

Full Text Available The vast extent and inaccessibility of boreal forest ecosystems are barriers to routine monitoring of forest structure and composition. In this research, we bridge the scale gap between intensive but sparse plot measurements and extensive remote sensing studies by collecting forest inventory variables at the plot scale using an unmanned aerial vehicle (UAV and a structure from motion (SfM approach. At 20 Forest Inventory and Analysis (FIA subplots in interior Alaska, we acquired overlapping imagery and generated dense, 3D, RGB (red, green, blue point clouds. We used these data to model forest type at the individual crown scale as well as subplot-scale tree density (TD, basal area (BA, and aboveground biomass (AGB. We achieved 85% cross-validation accuracy for five species at the crown level. Classification accuracy was maximized using three variables representing crown height, form, and color. Consistent with previous UAV-based studies, SfM point cloud data generated robust models of TD (r2 = 0.91, BA (r2 = 0.79, and AGB (r2 = 0.92, using a mix of plot- and crown-scale information. Precise estimation of TD required either segment counts or species information to differentiate black spruce from mixed white spruce plots. The accuracy of species-specific estimates of TD, BA, and AGB at the plot scale was somewhat variable, ranging from accurate estimates of black spruce TD (+/−1% and aspen BA (−2% to misallocation of aspen AGB (+118% and white spruce AGB (−50%. These results convey the potential utility of SfM data for forest type discrimination in FIA plots and the remaining challenges to develop classification approaches for species-specific estimates at the plot scale that are more robust to segmentation error.

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.

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.

Recce and UAV: mass memory an enabling technology for merger

Science.gov (United States)

Hall, Walter J., Jr.

1996-11-01

In the era of Declining Defense Dollars, the cost of sophisticated aircraft and highly trained personnel has heightened interest in Unmanned Air Vehicles (UAVs). The obvious lure is the lower vehicle cost (no crew station and crew support systems) and reduced needs for highly skilled air crews. Reconnaissance (commonly called recce) aircraft and their missions are among the commonly sighted applications for UAVs. Today's UAV recce aircraft (such as the Predator) are the genesis of much more sophisticated UAVs of the future. The evolution of the UAV will not be constrained to recce aircraft, but the recce mission will be significant for UAVs. The recce hole has historically been that of a battlefield data collector for post mission review and planning. In the electronic battlefield of the future, that role will be expanded. Envisioned mission for future recce aircraft include real-time scout, target location and fire coordination, battle damage assessment, and large area surveillance. Associated with many of these new roles is the need to store or assess much higher volumes of data. The higher volume data requirements are the result of higher resolution sensors (the Advanced Helicopter Pilotage infrared sensor has a data rate of near 1.2 Gigabits per second) and multi-sensor applications (the Multi-Sensor Aided Targeting program considered infrared, TV, and radar). The evolution of the UAV recce role, and associated increased data storage needs (from higher data rates and increased coverage requirements), requires the development of new data storage equipment. One solution to the increased storage needs is solid-state memory. As solid-state memories become faster, smaller, and cheaper they will enable the UAV recce mission capability to expand. Because of the speed of the memory, it will be possible to buffer and assess (identify the existence of targets or other points of interest) data before committing to consumption of limited storage assets. Faster memory

A hybrid system approach to airspeed, angle of attack and sideslip estimation in Unmanned Aerial Vehicles

KAUST Repository

Shaqura, Mohammad

2015-06-01

Fixed wing Unmanned Aerial Vehicles (UAVs) are an increasingly common sensing platform, owing to their key advantages: speed, endurance and ability to explore remote areas. While these platforms are highly efficient, they cannot easily be equipped with air data sensors commonly found on their larger scale manned counterparts. Indeed, such sensors are bulky, expensive and severely reduce the payload capability of the UAVs. In consequence, UAV controllers (humans or autopilots) have little information on the actual mode of operation of the wing (normal, stalled, spin) which can cause catastrophic losses of control when flying in turbulent weather conditions. In this article, we propose a real-time air parameter estimation scheme that can run on commercial, low power autopilots in real-time. The computational method is based on a hybrid decomposition of the modes of operation of the UAV. A Bayesian approach is considered for estimation, in which the estimated airspeed, angle of attack and sideslip are described statistically. An implementation on a UAV is presented, and the performance and computational efficiency of this method are validated using hardware in the loop (HIL) simulation and experimental flight data and compared with classical Extended Kalman Filter estimation. Our benchmark tests shows that this method is faster than EKF by up to two orders of magnitude. © 2015 IEEE.

Detection of Sensor Faults in Small Helicopter UAVs Using Observer/Kalman Filter Identification

Directory of Open Access Journals (Sweden)

Guillermo Heredia

2011-01-01

Full Text Available Reliability is a critical issue in navigation of unmanned aerial vehicles (UAVs since there is no human pilot that can react to any abnormal situation. Due to size and cost limitations, redundant sensor schemes and aeronautical-grade navigation sensors used in large aircrafts cannot be installed in small UAVs. Therefore, other approaches like analytical redundancy should be used to detect faults in navigation sensors and increase reliability. This paper presents a sensor fault detection and diagnosis system for small autonomous helicopters based on analytical redundancy. Fault detection is accomplished by evaluating any significant change in the behaviour of the vehicle with respect to the fault-free behaviour, which is estimated by using an observer. The observer is obtained from input-output experimental data with the Observer/Kalman Filter Identification (OKID method. The OKID method is able to identify the system and an observer with properties similar to a Kalman filter, directly from input-output experimental data. Results are similar to the Kalman filter, but, with the proposed method, there is no need to estimate neither system matrices nor sensor and process noise covariance matrices. The system has been tested with real helicopter flight data, and the results compared with other methods.

Development of a variable stability, modular UAV airframe for local research purposes

CSIR Research Space (South Africa)

Monk, John S

2008-11-01

Full Text Available /DPSS Wind tunnel Test CAD Patterns &Moulds Future partners Manufacture XDM 1 Auto pilot spec. A/P design Univ. Stellenbosch A/P manufacture A/P update Manufacture UAVs 1&2 Integrate XM 2D Structural Design A/P integrate Iron Bird... Manufacture XDM 2 Slide 30 © CSIR 2008 www.csir.co.za UAV Systems Integration Laboratory Servos UAV Flight SimulatorIron Bird (XDM) Motors and Controllers Looms Wind Tunnel? Control algorithms Flight models Atmospheric...

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.

Optimizing the presentation of UAV images in an attack helicopter cockpit

NARCIS (Netherlands)

Jansen, C.; Vries, S.C. de; Duistermaat, M.

2006-01-01

Future Unmanned Aerial Vehicles (UAV) will collaborate more directly with military manned aircraft. TNO Defence, Security and Safety investigated how to present UAV sensor images in a fighter aircraft cockpit in order to maximize target identification and flying performance. Ten military pilots

Application Possibility of Smartphone as Payload for Photogrammetric Uav System

Science.gov (United States)

Yun, M. H.; Kim, J.; Seo, D.; Lee, J.; Choi, C.

2012-07-01

Smartphone can not only be operated under 3G network environment anytime and anyplace but also cost less than the existing photogrammetric UAV since it provides high-resolution image, 3D location and attitude data on a real-time basis from a variety of built-in sensors. This study is aimed to assess the possibility of smartphone as a payload for photogrammetric UAV system. Prior to such assessment, a smartphone-based photogrammetric UAV system application was developed, through which real-time image, location and attitude data was obtained using smartphone under both static and dynamic conditions. Subsequently the accuracy assessment on the location and attitude data obtained and sent by this system was conducted. The smartphone images were converted into ortho-images through image triangulation. The image triangulation was conducted in accordance with presence or absence of consideration of the interior orientation (IO) parameters determined by camera calibration. In case IO parameters were taken into account in the static experiment, the results from triangulation for any smartphone type were within 1.5 pixel (RMSE), which was improved at least by 35% compared to when IO parameters were not taken into account. On the contrary, the improvement effect of considering IO parameters on accuracy in triangulation for smartphone images in dynamic experiment was not significant compared to the static experiment. It was due to the significant impact of vibration and sudden attitude change of UAV on the actuator for automatic focus control within the camera built in smartphone under the dynamic condition. This cause appears to have a negative impact on the image-based DEM generation. Considering these study findings, it is suggested that smartphone is very feasible as a payload for UAV system. It is also expected that smartphone may be loaded onto existing UAV playing direct or indirect roles significantly.

An Ecological Approach to the Design of UAV Ground Control Station (GCS) Status Displays

Science.gov (United States)

Dowell, Susan; Morphew, Ephimia; Shively, Jay

2003-01-01

Use of UAVs in military and commercial applications will continue to increase. However, there has been limited research devoted to UAV GCS design. The current study employed an ecological approach to interfac e design. Ecological Interface Design (EID) can be characterized as r epresenting the properties of a system, such that an operator is enco uraged to use skill-based behavior when problem solving. When more ef fortful cognitive processes become necessary due to unfamiliar situations, the application of EID philosophy supports the application of kn owledge-based behavior. With advances toward multiple UAV command and control, operators need GCS interfaces designed to support understan ding of complex systems. We hypothesized that use of EID principles f or the display of UAV status information would result in better opera tor performance and situational awareness, while decreasing workload. Pilots flew a series of missions with three UAV GCS displays of statu s information (Alphanumeric, Ecological, and Hybrid display format). Measures of task performance, Situational Awareness, and workload dem onstrated the benefits of using an ecological approach to designing U AV GCS displays. The application of ecological principles to the design of UAV GCSs is a promising area for improving UAV operations.

Preliminary Study on Earthquake Surface Rupture Extraction from Uav Images

Science.gov (United States)

Yuan, X.; Wang, X.; Ding, X.; Wu, X.; Dou, A.; Wang, S.

2018-04-01

Because of the advantages of low-cost, lightweight and photography under the cloud, UAVs have been widely used in the field of seismic geomorphology research in recent years. Earthquake surface rupture is a typical seismic tectonic geomorphology that reflects the dynamic and kinematic characteristics of crustal movement. The quick identification of earthquake surface rupture is of great significance for understanding the mechanism of earthquake occurrence, disasters distribution and scale. Using integrated differential UAV platform, series images were acquired with accuracy POS around the former urban area (Qushan town) of Beichuan County as the area stricken seriously by the 2008 Wenchuan Ms8.0 earthquake. Based on the multi-view 3D reconstruction technique, the high resolution DSM and DOM are obtained from differential UAV images. Through the shade-relief map and aspect map derived from DSM, the earthquake surface rupture is extracted and analyzed. The results show that the surface rupture can still be identified by using the UAV images although the time of earthquake elapse is longer, whose middle segment is characterized by vertical movement caused by compression deformation from fault planes.

Multiple Event Localization in a Sparse Acoustic Sensor Network Using UAVs as Data Mules

Science.gov (United States)

2012-12-01

the events to arrive in different orders at the sensors. Consequently , simple rules to group the ToAs from an event at different sensors, such as...a Microhard radio to forward the ToAs to the mule-UAV. Two Procerus Unicorn UAVs were used with different payloads. The imaging- UAV was equipped

Integration of Multiple UAVs for Collaborative ISR Missions in an Urban Environment

OpenAIRE

Chua, Chee Nam

2012-01-01

Military conflicts are shifting from jungles and deserts to cities. This is because terrorists, insurgents, and guerillas find these areas provide a rich target environment and good hideouts. With the use of UAVs, urban threats can be tracked and targeted effectively. However, in an urban environment where there is little or no GPS signals and many obstacles, navigation of UAVs is a major challenge. Multiple UAVs can be employed to share sensor information to counter these challenges and to p...

UAV Deployment Exercise for Mapping Purposes: Evaluation of Emergency Response Applications

Directory of Open Access Journals (Sweden)

Piero Boccardo

2015-07-01

Full Text Available Exploiting the decrease of costs related to UAV technology, the humanitarian community started piloting the use of similar systems in humanitarian crises several years ago in different application fields, i.e., disaster mapping and information gathering, community capacity building, logistics and even transportation of goods. Part of the author’s group, composed of researchers in the field of applied geomatics, has been piloting the use of UAVs since 2006, with a specific focus on disaster management application. In the framework of such activities, a UAV deployment exercise was jointly organized with the Regional Civil Protection authority, mainly aimed at assessing the operational procedures to deploy UAVs for mapping purposes and the usability of the acquired data in an emergency response context. In the paper the technical features of the UAV platforms will be described, comparing the main advantages/disadvantages of fixed-wing versus rotor platforms. The main phases of the adopted operational procedure will be discussed and assessed especially in terms of time required to carry out each step, highlighting potential bottlenecks and in view of the national regulation framework, which is rapidly evolving. Different methodologies for the processing of the acquired data will be described and discussed, evaluating the fitness for emergency response applications.

UAV Deployment Exercise for Mapping Purposes: Evaluation of Emergency Response Applications.

Science.gov (United States)

Boccardo, Piero; Chiabrando, Filiberto; Dutto, Furio; Tonolo, Fabio Giulio; Lingua, Andrea

2015-07-02

Exploiting the decrease of costs related to UAV technology, the humanitarian community started piloting the use of similar systems in humanitarian crises several years ago in different application fields, i.e., disaster mapping and information gathering, community capacity building, logistics and even transportation of goods. Part of the author's group, composed of researchers in the field of applied geomatics, has been piloting the use of UAVs since 2006, with a specific focus on disaster management application. In the framework of such activities, a UAV deployment exercise was jointly organized with the Regional Civil Protection authority, mainly aimed at assessing the operational procedures to deploy UAVs for mapping purposes and the usability of the acquired data in an emergency response context. In the paper the technical features of the UAV platforms will be described, comparing the main advantages/disadvantages of fixed-wing versus rotor platforms. The main phases of the adopted operational procedure will be discussed and assessed especially in terms of time required to carry out each step, highlighting potential bottlenecks and in view of the national regulation framework, which is rapidly evolving. Different methodologies for the processing of the acquired data will be described and discussed, evaluating the fitness for emergency response applications.

Quality Analysis on 3d Buidling Models Reconstructed from Uav Imagery

Science.gov (United States)

Jarzabek-Rychard, M.; Karpina, M.

2016-06-01

Recent developments in UAV technology and structure from motion techniques have effected that UAVs are becoming standard platforms for 3D data collection. Because of their flexibility and ability to reach inaccessible urban parts, drones appear as optimal solution for urban applications. Building reconstruction from the data collected with UAV has the important potential to reduce labour cost for fast update of already reconstructed 3D cities. However, especially for updating of existing scenes derived from different sensors (e.g. airborne laser scanning), a proper quality assessment is necessary. The objective of this paper is thus to evaluate the potential of UAV imagery as an information source for automatic 3D building modeling at LOD2. The investigation process is conducted threefold: (1) comparing generated SfM point cloud to ALS data; (2) computing internal consistency measures of the reconstruction process; (3) analysing the deviation of Check Points identified on building roofs and measured with a tacheometer. In order to gain deep insight in the modeling performance, various quality indicators are computed and analysed. The assessment performed according to the ground truth shows that the building models acquired with UAV-photogrammetry have the accuracy of less than 18 cm for the plannimetric position and about 15 cm for the height component.

QUALITY ANALYSIS ON 3D BUIDLING MODELS RECONSTRUCTED FROM UAV IMAGERY

Directory of Open Access Journals (Sweden)

M. Jarzabek-Rychard

2016-06-01

Full Text Available Recent developments in UAV technology and structure from motion techniques have effected that UAVs are becoming standard platforms for 3D data collection. Because of their flexibility and ability to reach inaccessible urban parts, drones appear as optimal solution for urban applications. Building reconstruction from the data collected with UAV has the important potential to reduce labour cost for fast update of already reconstructed 3D cities. However, especially for updating of existing scenes derived from different sensors (e.g. airborne laser scanning, a proper quality assessment is necessary. The objective of this paper is thus to evaluate the potential of UAV imagery as an information source for automatic 3D building modeling at LOD2. The investigation process is conducted threefold: (1 comparing generated SfM point cloud to ALS data; (2 computing internal consistency measures of the reconstruction process; (3 analysing the deviation of Check Points identified on building roofs and measured with a tacheometer. In order to gain deep insight in the modeling performance, various quality indicators are computed and analysed. The assessment performed according to the ground truth shows that the building models acquired with UAV-photogrammetry have the accuracy of less than 18 cm for the plannimetric position and about 15 cm for the height component.

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.

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.

Closing the Gap Between Research and Field Applications for Multi-UAV Cooperative Missions

Science.gov (United States)

2013-09-01

REPORT DATE September 2013 3. REPORT TYPE AND DATES COVERED Master’s Thesis 4. TITLE AND SUBTITLE CLOSING THE GAP BETWEEN RESEARCH AND FIELD...iii Approved for public release; distribution is unlimited CLOSING THE GAP BETWEEN RESEARCH AND FIELD APPLICATIONS FOR MULTI-UAV COOPERATIVE...the report is to lay the groundwork for future analysis in multi-UAV analysis to close the gap between existing research and efficient multi-UAV

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.

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.

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...

UAV FOR GEODATA ACQUISITION IN AGRICULTUREAL AND FORESTAL APPLICATIONS

Directory of Open Access Journals (Sweden)

P. Reidelstürz

2012-09-01

The airframe´s wingspan is about 3,45m weighting 4.2 kg, ready to fly. The hand launchable UAV can start from any place in agricultural regions. The wing is configured with flaps, allowing steep approaches and short landings using a „butterfly“ brake configuration. In spite of the lightweight configuration the UAV yet proves its worth under windy baltic wether situations by collecting regular sharp images of fields under wind speed up to 15m/s (Beaufort 6 –7. In further projects the development of further payload modules and a user friendly flight planning tool is scheduled considering different payload – and airframe requirements for different precision farming purposes and forest applications. Data processing and workflow will be optimized. Cooperation with further partners to establish UAV systems in agricultural, forest and geodata aquisition is desired.

Uav Photogrammetry: a Practical Solution for Challenging Mapping Projects

Science.gov (United States)

Saadatseresht, M.; Hashempour, A. H.; Hasanlou, M.

2015-12-01

We have observed huge attentions to application of unmanned aerial vehicle (UAV) in aerial mapping since a decade ago. Though, it has several advantages for handling time/cost/quality issues, there are a dozen of challenges in working with UAVs. In this paper, we; as the Robotic Photogrammetry Research Group (RPRG), will firstly review these challenges then show its advantages in three special practical projects. For each project, we will share our experiences through description of the UAV specifications, flight settings and processing steps. At the end, we will illustrate final result of each project and show how this technology could make unbelievable benefits to clients including 3D city realistic model in decimetre level, ultra high quality map production in several centimetre level, and accessing to a high risk and rough relief area for mapping aims.

Multisensor Equipped Uav/ugv for Automated Exploration

Science.gov (United States)

Batzdorfer, S.; Bobbe, M.; Becker, M.; Harms, H.; Bestmann, U.

2017-08-01

The usage of unmanned systems for exploring disaster scenarios has become more and more important in recent times as a supporting system for action forces. These systems have to offer a well-balanced relationship between the quality of support and additional workload. Therefore within the joint research project ANKommEn - german acronym for Automated Navigation and Communication for Exploration - a system for exploration of disaster scenarios is build-up using multiple UAV und UGV controlled via a central ground station. The ground station serves as user interface for defining missions and tasks conducted by the unmanned systems, equipped with different environmental sensors like cameras - RGB as well as IR - or LiDAR. Depending on the exploration task results, in form of pictures, 2D stitched orthophoto or LiDAR point clouds will be transmitted via datalinks and displayed online at the ground station or will be processed in short-term after a mission, e.g. 3D photogrammetry. For mission planning and its execution, UAV/UGV monitoring and georeferencing of environmental sensor data, reliable positioning and attitude information is required. This is gathered using an integrated GNSS/IMU positioning system. In order to increase availability of positioning information in GNSS challenging scenarios, a GNSS-Multiconstellation based approach is used, amongst others. The present paper focuses on the overall system design including the ground station and sensor setups on the UAVs and UGVs, the underlying positioning techniques as well as 2D and 3D exploration based on a RGB camera mounted on board the UAV and its evaluation based on real world field tests.

MULTISENSOR EQUIPPED UAV/UGV FOR AUTOMATED EXPLORATION

Directory of Open Access Journals (Sweden)

S. Batzdorfer

2017-08-01

Full Text Available The usage of unmanned systems for exploring disaster scenarios has become more and more important in recent times as a supporting system for action forces. These systems have to offer a well-balanced relationship between the quality of support and additional workload. Therefore within the joint research project ANKommEn – german acronym for Automated Navigation and Communication for Exploration – a system for exploration of disaster scenarios is build-up using multiple UAV und UGV controlled via a central ground station. The ground station serves as user interface for defining missions and tasks conducted by the unmanned systems, equipped with different environmental sensors like cameras – RGB as well as IR – or LiDAR. Depending on the exploration task results, in form of pictures, 2D stitched orthophoto or LiDAR point clouds will be transmitted via datalinks and displayed online at the ground station or will be processed in short-term after a mission, e.g. 3D photogrammetry. For mission planning and its execution, UAV/UGV monitoring and georeferencing of environmental sensor data, reliable positioning and attitude information is required. This is gathered using an integrated GNSS/IMU positioning system. In order to increase availability of positioning information in GNSS challenging scenarios, a GNSS-Multiconstellation based approach is used, amongst others. The present paper focuses on the overall system design including the ground station and sensor setups on the UAVs and UGVs, the underlying positioning techniques as well as 2D and 3D exploration based on a RGB camera mounted on board the UAV and its evaluation based on real world field tests.

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.

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.

A REDUNDANT GNSS-INS LOW-COST UAV NAVIGATION SOLUTION FOR PROFESSIONAL APPLICATIONS

Directory of Open Access Journals (Sweden)

J. Navarro

2015-08-01

Full Text Available This paper presents the current results for the FP7 GINSEC project. Its goal is to build a pre-commercial prototype of a low-cost, accurate and reliable system for the professional UAV market. Low-cost, in this context, stands for the use of sensors in the most affordable segment of the market, especially MEMS IMUs and GNSS receivers. Reliability applies to the ability of the autopilot to cope with situations where unfavourable GNSS reception conditions or strong electromagnetic fields make the computation of the position and / or attitude of the UAV difficult. Professional and accurate mean that, at least using post-processing techniques as PPP, it will be possible to reach cm-level precisions that open the door to a range of applications demanding high levels of quality in positioning, as precision agriculture or mapping. To achieve such goal, a rigorous sensor error modelling approach, the use of redundant IMUs and a dual-GNSS receiver setup, together with close-coupling techniques and an extended Kalman filter with self-analysis capabilities have been used. Although the project is not yet complete, the results obtained up to now prove the feasibility of the aforementioned goal, especially in those aspects related to position determination. Research work is still undergoing to estimate the heading using a dual-GNNS receiver setup; preliminary results prove the validity of this approach for relatively long baselines, although positive results are expected when these are shorter than 1 m – which is a necessary requisite for small-sized UAVs.

a Redundant Gnss-Ins Low-Cost Uav Navigation Solution for Professional Applications

Science.gov (United States)

Navarro, J.; Parés, M. E.; Colomina, I.; Bianchi, G.; Pluchino, S.; Baddour, R.; Consoli, A.; Ayadi, J.; Gameiro, A.; Sekkas, O.; Tsetsos, V.; Gatsos, T.; Navoni, R.

2015-08-01

This paper presents the current results for the FP7 GINSEC project. Its goal is to build a pre-commercial prototype of a low-cost, accurate and reliable system for the professional UAV market. Low-cost, in this context, stands for the use of sensors in the most affordable segment of the market, especially MEMS IMUs and GNSS receivers. Reliability applies to the ability of the autopilot to cope with situations where unfavourable GNSS reception conditions or strong electromagnetic fields make the computation of the position and / or attitude of the UAV difficult. Professional and accurate mean that, at least using post-processing techniques as PPP, it will be possible to reach cm-level precisions that open the door to a range of applications demanding high levels of quality in positioning, as precision agriculture or mapping. To achieve such goal, a rigorous sensor error modelling approach, the use of redundant IMUs and a dual-GNSS receiver setup, together with close-coupling techniques and an extended Kalman filter with self-analysis capabilities have been used. Although the project is not yet complete, the results obtained up to now prove the feasibility of the aforementioned goal, especially in those aspects related to position determination. Research work is still undergoing to estimate the heading using a dual-GNNS receiver setup; preliminary results prove the validity of this approach for relatively long baselines, although positive results are expected when these are shorter than 1 m - which is a necessary requisite for small-sized UAVs.

Estimation of 557.7 nm Emission Altitude using Co-located Lidars and Photometers over Arecibo

Science.gov (United States)

Franco, E.; Raizada, S.; Lautenbach, J.; Brum, C. G. M.

2017-12-01

Airglow at 557.7 nm (green line emission) is generated through the Barth mechanism in the E-region altitude and is sometimes associated with red line (630.0 nm) originating at F-region altitudes. Photons at 557.7 nm are produced through the quenching of excited atomic oxygen atoms, O(1S), while 630.0 nm results through the de-excitation of O(1D) atoms. Even though, the contribution of the green line from F-region is negligible and the significant component comes from the mesosphere, this uncertainty gives rise to a question related to its precise altitude. Previous studies have shown that perturbations generated by atmospheric gravity Waves (GWs) alter the airglow intensity and can be used for studying dynamics of the region where it originates. The uncertainty in the emission altitude of green line can be resolved by using co-located lidars, which provide altitude resolved metal densities. At Arecibo, the resonance lidars tuned to Na and K resonance wavelengths at 589 nm and 770 nm can be used in conjunction with simultaneous measurements from green line photometer to resolve this issue. Both photometer and lidars have narrow field of view as compared to airglow imagers, and hence provide an added advantage that these instruments sample same GW spectrum. Hence, correlation between density perturbations inferred from lidars and airglow intensity perturbations can shed light on the exact altitude of green line emission.

Spatial Quality Evaluation of Resampled Unmanned Aerial Vehicle-Imagery for Weed Mapping.

Science.gov (United States)

Borra-Serrano, Irene; Peña, José Manuel; Torres-Sánchez, Jorge; Mesas-Carrascosa, Francisco Javier; López-Granados, Francisca

2015-08-12

Unmanned aerial vehicles (UAVs) combined with different spectral range sensors are an emerging technology for providing early weed maps for optimizing herbicide applications. Considering that weeds, at very early phenological stages, are similar spectrally and in appearance, three major components are relevant: spatial resolution, type of sensor and classification algorithm. Resampling is a technique to create a new version of an image with a different width and/or height in pixels, and it has been used in satellite imagery with different spatial and temporal resolutions. In this paper, the efficiency of resampled-images (RS-images) created from real UAV-images (UAV-images; the UAVs were equipped with two types of sensors, i.e., visible and visible plus near-infrared spectra) captured at different altitudes is examined to test the quality of the RS-image output. The performance of the object-based-image-analysis (OBIA) implemented for the early weed mapping using different weed thresholds was also evaluated. Our results showed that resampling accurately extracted the spectral values from high spatial resolution UAV-images at an altitude of 30 m and the RS-image data at altitudes of 60 and 100 m, was able to provide accurate weed cover and herbicide application maps compared with UAV-images from real flights.

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

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

Altitude Registration of Limb-Scattered Radiation

Science.gov (United States)

Moy, Leslie; Bhartia, Pawan K.; Jaross, Glen; Loughman, Robert; Kramarova, Natalya; Chen, Zhong; Taha, Ghassan; Chen, Grace; Xu, Philippe

2017-01-01

One of the largest constraints to the retrieval of accurate ozone profiles from UV backscatter limb sounding sensors is altitude registration. Two methods, the Rayleigh scattering attitude sensing (RSAS) and absolute radiance residual method (ARRM), are able to determine altitude registration to the accuracy necessary for long-term ozone monitoring. The methods compare model calculations of radiances to measured radiances and are independent of onboard tracking devices. RSAS determines absolute altitude errors, but, because the method is susceptible to aerosol interference, it is limited to latitudes and time periods with minimal aerosol contamination. ARRM, a new technique introduced in this paper, can be applied across all seasons and altitudes. However, it is only appropriate for relative altitude error estimates. The application of RSAS to Limb Profiler (LP) measurements from the Ozone Mapping and Profiler Suite (OMPS) on board the Suomi NPP (SNPP) satellite indicates tangent height (TH) errors greater than 1 km with an absolute accuracy of +/-200 m. Results using ARRM indicate a approx. 300 to 400m intra-orbital TH change varying seasonally +/-100 m, likely due to either errors in the spacecraft pointing or in the geopotential height (GPH) data that we use in our analysis. ARRM shows a change of approx. 200m over 5 years with a relative accuracy (a long-term accuracy) of 100m outside the polar regions.

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.

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

[Physiological aspects of altitude training and the use of altitude simulators].

Science.gov (United States)

Ranković, Goran; Radovanović, Dragan

2005-01-01

Altitude training in various forms is widely practiced by athletes and coaches in an attempt to improve sea level endurance. Training at high altitude may improve performance at sea level through altitude acclimatisation, which improves oxygen transport and/or utilisation, or through hypoxia, which intensifies the training stimulus. This basic physiological aspect allows three training modalities: live high and train high (classic high-altitude training), live low and train high (training through hypoxia), and live high and train low (the new trend). In an effort to reduce the financial and logistical challenges of travelling to high-altitude training sites, scientists and manufactures have developed artificial high-altitude environments, which simulate the hypoxic conditions of moderate altitude (2000-3000 meters). Endurance athletes from many sports have recently started using nitrogen environments, or hypoxic rooms and tents as part of their altitude training programmes. The results of controlled studies on these modalities of high-altitude training, their practical approach, and ethics are summarised.

Physiological aspects of altitude training and the use of altitude simulators

Directory of Open Access Journals (Sweden)

Ranković Goran

2005-01-01

Full Text Available Altitude training in various forms is widely practiced by athletes and coaches in an attempt to improve sea level endurance. Training at high altitude may improve performance at sea level through altitude acclimatization, which improves oxygen transport and/or utilization, or through hypoxia, which intensifies the training stimulus. This basic physiological aspect allows three training modalities: live high and train high (classic high-altitude training, live low and train high (training through hypoxia, and live high and train low (the new trend. In an effort to reduce the financial and logistical challenges of traveling to high-altitude training sites, scientists and manufactures have developed artificial high-altitude environments, which simulate the hypoxic conditions of moderate altitude (2000-3000 meters. Endurance athletes from many sports have recently started using nitrogen environments, or hypoxic rooms and tents as part of their altitude training programmes. The results of controlled studies on these modalities of high-altitude training, their practical approach, and ethics are summarized.

Evaluation of resampling applied to UAV imagery for weed detection using OBIA

OpenAIRE

Borra, I.; Peña Barragán, José Manuel; Torres Sánchez, Jorge; López Granados, Francisca

2015-01-01

Los vehículos aéreos no tripulados (UAVs) son una tecnología emergente en el estudio de parámetros agrícolas por sus características y por portar sensores en diferente rango espectral. En este trabajo se ha detectado y cartografiado rodales de malas hierbas en fase temprana mediante análisis OBIA para elaborar mapas que optimicen el tratamiento herbicida localizado. Se ha aplicado resampling (resampleo) sobre imágenes tomadas en campo desde un UAV (UAV-I) para crear una nueva imagen con disti...

Design and First Results of an UAV-Borne L-Band Radiometer for Multiple Monitoring Purposes

Directory of Open Access Journals (Sweden)

Rene Acevo-Herrera

2010-06-01

Full Text Available UAV (unmanned Aerial Vehicle platforms represent a challenging opportunity for the deployment of a number of remote sensors. These vehicles are a cost-effective option in front of manned aerial vehicles (planes and helicopters, are easy to deploy due to the short runways needed, and they allow users to meet the critical requirements of the spatial and temporal resolutions imposed by the instruments. L-band radiometers are an interesting option for obtaining soil moisture maps over local areas with relatively high spatial resolution for precision agriculture, coastal monitoring, estimation of the risk of fires, flood prevention, etc. This paper presents the design of a light-weight, airborne L-band radiometer for deployment in a small UAV, including the hardware and specific software developed for calibration, geo-referencing, and soil moisture retrieval. First results and soil moisture retrievals from different field experiments are presented.

Detection of a Moving Gas Source and Estimation of its Concentration Field with a Sensing Aerial Vehicle Integration of Theoretical Controls and Computational Fluids

Science.gov (United States)

2016-07-21

Unmanned Aircraft Vehicles ( UAVs ) have evolved rapidly over the past decade driven primarily by military uses, and have begun finding application among...vehicle dynamics and guidance, and the onboard sensor modeling. 15. SUBJECT TERMS State estimation; UAVs , mobile sensors; grid adaptationj; plume...onboard the UAVs to spatial areas of higher concentration (i.e. a local maximum concentration), but to send the UAVs with the onboard concentration

Secure Utilization of Beacons and UAVs in Emergency Response Systems for Building Fire Hazard.

Science.gov (United States)

Seo, Seung-Hyun; Choi, Jung-In; Song, Jinseok

2017-09-25

An intelligent emergency system for hazard monitoring and building evacuation is a very important application area in Internet of Things (IoT) technology. Through the use of smart sensors, such a system can provide more vital and reliable information to first-responders and also reduce the incidents of false alarms. Several smart monitoring and warning systems do already exist, though they exhibit key weaknesses such as a limited monitoring coverage and security, which have not yet been sufficiently addressed. In this paper, we propose a monitoring and emergency response method for buildings by utilizing beacons and Unmanned Aerial Vehicles (UAVs) on an IoT security platform. In order to demonstrate the practicability of our method, we also implement a proof of concept prototype, which we call the UAV-EMOR (UAV-assisted Emergency Monitoring and Response) system. Our UAV-EMOR system provides the following novel features: (1) secure communications between UAVs, smart sensors, the control server and a smartphone app for security managers; (2) enhanced coordination between smart sensors and indoor/outdoor UAVs to expand real-time monitoring coverage; and (3) beacon-aided rescue and building evacuation.

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.

Roving UAV IED Interdiction System

Science.gov (United States)

2011-03-01

UAVs (Raven, Wasp, and Puma) do not advertise any payload capability, the Tier I operators that Team Bravo contacted claimed small payload...www.ncca.navy.mil/services/inflation.cfm (accessed February 2011). Net Resources International. "Javelin Anti- Armour Missile." Army-Technology.com. 2011. http

Cycloidal Propulsion for UAV VTOL Applications

National Research Council Canada - National Science Library

Boschma, James

1998-01-01

.... This propulsion concept holds significant promise for adaptation to UAV VTOL operations. Thrust levels demonstrated were substantially higher than achievable by the best screw type propellers, and approximately equal to those of high end helicopters...

Estimating distribution of hidden objects with drones: from tennis balls to manatees.

Directory of Open Access Journals (Sweden)

Julien Martin

Full Text Available Unmanned aerial vehicles (UAV, or drones, have been used widely in military applications, but more recently civilian applications have emerged (e.g., wildlife population monitoring, traffic monitoring, law enforcement, oil and gas pipeline threat detection. UAV can have several advantages over manned aircraft for wildlife surveys, including reduced ecological footprint, increased safety, and the ability to collect high-resolution geo-referenced imagery that can document the presence of species without the use of a human observer. We illustrate how geo-referenced data collected with UAV technology in combination with recently developed statistical models can improve our ability to estimate the distribution of organisms. To demonstrate the efficacy of this methodology, we conducted an experiment in which tennis balls were used as surrogates of organisms to be surveyed. We used a UAV to collect images of an experimental field with a known number of tennis balls, each of which had a certain probability of being hidden. We then applied spatially explicit occupancy models to estimate the number of balls and created precise distribution maps. We conducted three consecutive surveys over the experimental field and estimated the total number of balls to be 328 (95%CI: 312, 348. The true number was 329 balls, but simple counts based on the UAV pictures would have led to a total maximum count of 284. The distribution of the balls in the field followed a simulated environmental gradient. We also were able to accurately estimate the relationship between the gradient and the distribution of balls. Our experiment demonstrates how this technology can be used to create precise distribution maps in which discrete regions of the study area are assigned a probability of presence of an object. Finally, we discuss the applicability and relevance of this experimental study to the case study of Florida manatee distribution at power plants.

Estimating distribution of hidden objects with drones: from tennis balls to manatees.

Science.gov (United States)

Martin, Julien; Edwards, Holly H; Burgess, Matthew A; Percival, H Franklin; Fagan, Daniel E; Gardner, Beth E; Ortega-Ortiz, Joel G; Ifju, Peter G; Evers, Brandon S; Rambo, Thomas J

2012-01-01

Unmanned aerial vehicles (UAV), or drones, have been used widely in military applications, but more recently civilian applications have emerged (e.g., wildlife population monitoring, traffic monitoring, law enforcement, oil and gas pipeline threat detection). UAV can have several advantages over manned aircraft for wildlife surveys, including reduced ecological footprint, increased safety, and the ability to collect high-resolution geo-referenced imagery that can document the presence of species without the use of a human observer. We illustrate how geo-referenced data collected with UAV technology in combination with recently developed statistical models can improve our ability to estimate the distribution of organisms. To demonstrate the efficacy of this methodology, we conducted an experiment in which tennis balls were used as surrogates of organisms to be surveyed. We used a UAV to collect images of an experimental field with a known number of tennis balls, each of which had a certain probability of being hidden. We then applied spatially explicit occupancy models to estimate the number of balls and created precise distribution maps. We conducted three consecutive surveys over the experimental field and estimated the total number of balls to be 328 (95%CI: 312, 348). The true number was 329 balls, but simple counts based on the UAV pictures would have led to a total maximum count of 284. The distribution of the balls in the field followed a simulated environmental gradient. We also were able to accurately estimate the relationship between the gradient and the distribution of balls. Our experiment demonstrates how this technology can be used to create precise distribution maps in which discrete regions of the study area are assigned a probability of presence of an object. Finally, we discuss the applicability and relevance of this experimental study to the case study of Florida manatee distribution at power plants.

Vision Aided State Estimation for Helicopter Slung Load System

DEFF Research Database (Denmark)

Bisgaard, Morten; Bendtsen, Jan Dimon; la Cour-Harbo, Anders

2007-01-01

This paper presents the design and verification of a state estimator for a helicopter based slung load system. The estimator is designed to augment the IMU driven estimator found in many helicopter UAV s and uses vision based updates only. The process model used for the estimator is a simple 4...

A High Resolution, Light-Weight, Synthetic Aperture Radar for UAV Application

International Nuclear Information System (INIS)

Doerry, A.W.; Hensley, W.H.; Stence, J.; Tsunoda, S.I.; Pace, F.; Walker, B.C.; Woodring, M.

1999-06-01

(U) Sandia National Laboratories in collaboration with General Atomics (GA) has designed and built a high resolution, light-weight, Ku-band Synthetic Aperture Radar (SAR) known as ''Lynx''. Although Lynx can be operated on a wide variety of manned and unmanned platforms, its design is optimized for use on medium altitude Unmanned Aerial Vehicles (UAVS). In particular, it can be operated on the Predator, I-GNAT, and Prowler II platforms manufactured by GA. (U) The radar production weight is less than 120 lb and operates within a 3 GHz band from 15.2 GHz to 18.2 GHz with a peak output power of 320 W. Operating range is resolution and mode dependent but can exceed 45 km in adverse weather (4 mm/hr rain). Lynx has operator selectable resolution and is capable of 0.1 m resolution in spotlight mode and 0.3 m resolution in strip map mode, over substantial depression angles (5 to 60 deg) and squint angles (broadside and ±45 deg). Real-time Motion Compensation is implemented to allow high-quality image formation even during vehicle turns and other maneuvers

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

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.

Comparing RIEGL RiCOPTER UAV LiDAR Derived Canopy Height and DBH with Terrestrial LiDAR.

Science.gov (United States)

Brede, Benjamin; Lau, Alvaro; Bartholomeus, Harm M; Kooistra, Lammert

2017-10-17

In recent years, LIght Detection And Ranging (LiDAR) and especially Terrestrial Laser Scanning (TLS) systems have shown the potential to revolutionise forest structural characterisation by providing unprecedented 3D data. However, manned Airborne Laser Scanning (ALS) requires costly campaigns and produces relatively low point density, while TLS is labour intense and time demanding. Unmanned Aerial Vehicle (UAV)-borne laser scanning can be the way in between. In this study, we present first results and experiences with the RIEGL RiCOPTER with VUX ® -1UAV ALS system and compare it with the well tested RIEGL VZ-400 TLS system. We scanned the same forest plots with both systems over the course of two days. We derived Digital Terrain Model (DTMs), Digital Surface Model (DSMs) and finally Canopy Height Model (CHMs) from the resulting point clouds. ALS CHMs were on average 11.5 c m higher in five plots with different canopy conditions. This showed that TLS could not always detect the top of canopy. Moreover, we extracted trunk segments of 58 trees for ALS and TLS simultaneously, of which 39 could be used to model Diameter at Breast Height (DBH). ALS DBH showed a high agreement with TLS DBH with a correlation coefficient of 0.98 and root mean square error of 4.24 c m . We conclude that RiCOPTER has the potential to perform comparable to TLS for estimating forest canopy height and DBH under the studied forest conditions. Further research should be directed to testing UAV-borne LiDAR for explicit 3D modelling of whole trees to estimate tree volume and subsequently Above-Ground Biomass (AGB).

Depth Estimation of Submerged Aquatic Vegetation in Clear Water Streams Using Low-Altitude Optical Remote Sensing.

Science.gov (United States)

Visser, Fleur; Buis, Kerst; Verschoren, Veerle; Meire, Patrick

2015-09-30

UAVs and other low-altitude remote sensing platforms are proving very useful tools for remote sensing of river systems. Currently consumer grade cameras are still the most commonly used sensors for this purpose. In particular, progress is being made to obtain river bathymetry from the optical image data collected with such cameras, using the strong attenuation of light in water. No studies have yet applied this method to map submergence depth of aquatic vegetation, which has rather different reflectance characteristics from river bed substrate. This study therefore looked at the possibilities to use the optical image data to map submerged aquatic vegetation (SAV) depth in shallow clear water streams. We first applied the Optimal Band Ratio Analysis method (OBRA) of Legleiter et al. (2009) to a dataset of spectral signatures from three macrophyte species in a clear water stream. The results showed that for each species the ratio of certain wavelengths were strongly associated with depth. A combined assessment of all species resulted in equally strong associations, indicating that the effect of spectral variation in vegetation is subsidiary to spectral variation due to depth changes. Strongest associations (R²-values ranging from 0.67 to 0.90 for different species) were found for combinations including one band in the near infrared (NIR) region between 825 and 925 nm and one band in the visible light region. Currently data of both high spatial and spectral resolution is not commonly available to apply the OBRA results directly to image data for SAV depth mapping. Instead a novel, low-cost data acquisition method was used to obtain six-band high spatial resolution image composites using a NIR sensitive DSLR camera. A field dataset of SAV submergence depths was used to develop regression models for the mapping of submergence depth from image pixel values. Band (combinations) providing the best performing models (R²-values up to 0.77) corresponded with the OBRA

UAV telemetry communications using ZigBee protocol

Science.gov (United States)

Nasution, T. H.; Siregar, I.; Yasir, M.

2017-10-01

Wireless communication has been widely used in various fields or disciplines such as agriculture, health, engineering, military, and aerospace so as to support the work in that field. The communication technology is typically used for controlling devices and data monitoring. One development of wireless communication is the widely used telemetry system used to reach areas that cannot be reached by humans using UAV (Unmanned Aerial Vehicle) or unmanned aircraft. In this paper we discuss the design of telemetry system in UAV using ZigBee protocol. From the test obtained the system can work well with visualization displays without pause is 20 data per second with a maximum data length of 120 characters.

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.

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.

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.

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.

Rapid 3D Reconstruction for Image Sequence Acquired from UAV Camera

Directory of Open Access Journals (Sweden)

Yufu Qu

2018-01-01

Full Text Available In order to reconstruct three-dimensional (3D structures from an image sequence captured by unmanned aerial vehicles’ camera (UAVs and improve the processing speed, we propose a rapid 3D reconstruction method that is based on an image queue, considering the continuity and relevance of UAV camera images. The proposed approach first compresses the feature points of each image into three principal component points by using the principal component analysis method. In order to select the key images suitable for 3D reconstruction, the principal component points are used to estimate the interrelationships between images. Second, these key images are inserted into a fixed-length image queue. The positions and orientations of the images are calculated, and the 3D coordinates of the feature points are estimated using weighted bundle adjustment. With this structural information, the depth maps of these images can be calculated. Next, we update the image queue by deleting some of the old images and inserting some new images into the queue, and a structural calculation of all the images can be performed by repeating the previous steps. Finally, a dense 3D point cloud can be obtained using the depth–map fusion method. The experimental results indicate that when the texture of the images is complex and the number of images exceeds 100, the proposed method can improve the calculation speed by more than a factor of four with almost no loss of precision. Furthermore, as the number of images increases, the improvement in the calculation speed will become more noticeable.

Rapid 3D Reconstruction for Image Sequence Acquired from UAV Camera.

Science.gov (United States)

Qu, Yufu; Huang, Jianyu; Zhang, Xuan

2018-01-14

In order to reconstruct three-dimensional (3D) structures from an image sequence captured by unmanned aerial vehicles' camera (UAVs) and improve the processing speed, we propose a rapid 3D reconstruction method that is based on an image queue, considering the continuity and relevance of UAV camera images. The proposed approach first compresses the feature points of each image into three principal component points by using the principal component analysis method. In order to select the key images suitable for 3D reconstruction, the principal component points are used to estimate the interrelationships between images. Second, these key images are inserted into a fixed-length image queue. The positions and orientations of the images are calculated, and the 3D coordinates of the feature points are estimated using weighted bundle adjustment. With this structural information, the depth maps of these images can be calculated. Next, we update the image queue by deleting some of the old images and inserting some new images into the queue, and a structural calculation of all the images can be performed by repeating the previous steps. Finally, a dense 3D point cloud can be obtained using the depth-map fusion method. The experimental results indicate that when the texture of the images is complex and the number of images exceeds 100, the proposed method can improve the calculation speed by more than a factor of four with almost no loss of precision. Furthermore, as the number of images increases, the improvement in the calculation speed will become more noticeable.

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...

HIGH-ALTITUDE ILLNESS

Directory of Open Access Journals (Sweden)

Dwitya Elvira

2015-05-01

Full Text Available AbstrakHigh-altitude illness (HAI merupakan sekumpulan gejala paru dan otak yang terjadi pada orang yang baru pertama kali mendaki ke ketinggian. HAI terdiri dari acute mountain sickness (AMS, high-altitude cerebral edema (HACE dan high-altitude pulmonary edema (HAPE. Tujuan tinjauan pustaka ini adalah agar dokter dan wisatawan memahami risiko, tanda, gejala, dan pengobatan high-altitude illness. Perhatian banyak diberikan terhadap penyakit ini seiring dengan meningkatnya popularitas olahraga ekstrim (mendaki gunung tinggi, ski dan snowboarding dan adanya kemudahan serta ketersediaan perjalanan sehingga jutaan orang dapat terpapar bahaya HAI. Di Pherice, Nepal (ketinggian 4343 m, 43% pendaki mengalami gejala AMS. Pada studi yang dilakukan pada tempat wisata di resort ski Colorado, Honigman menggambarkan kejadian AMS 22% pada ketinggian 1850 m sampai 2750 m, sementara Dean menunjukkan 42% memiliki gejala pada ketinggian 3000 m. Aklimatisasi merupakan salah satu tindakan pencegahan yang dapat dilakukan sebelum pendakian, selain beberapa pengobatan seperti asetazolamid, dexamethasone, phosopodiestrase inhibitor, dan ginko biloba.Kata kunci: high-altitude illness, acute mountain sickness, edema cerebral, pulmonary edema AbstractHigh-altitude illness (HAI is symptoms of lung and brain that occurs in people who first climb to altitude. HAI includes acute mountain sickness (AMS, high-altitude cerebral edema (HACE and high altitude pulmonary edema (HAPE. The objective of this review was to understand the risks, signs, symptoms, and treatment of high-altitude illness. The attention was given to this disease due to the rising popularity of extreme sports (high mountain climbing, skiing and snowboarding and the ease and availability of the current travelling, almost each year, millions of people could be exposed to the danger of HAI. In Pherice, Nepal (altitude 4343 m, 43% of climbers have symptoms of AMS. Furthermore, in a study conducted at sites in

Study on the aerodynamic behavior of a UAV with an applied seeder for agricultural practices

Science.gov (United States)

Felismina, Raimundo; Silva, Miguel; Mateus, Artur; Malça, Cândida

2017-06-01

It is irrefutable that the use of Unmanned Airborne Vehicle Systems (UAVs) in agricultural tasks and on the analysis of health and vegetative conditions represents a powerful tool in modern agriculture. To contribute to the growth of the agriculture economic sector a seeder to be coupled to any type of UAV was previously developed and designed by the authors. This seeder allows for the deposition of seeds with positional accuracy, i.e., seeds are accurately deposited at pre-established distances between plants [1]. This work aims at analyzing the aerodynamic behavior of UAV/Seeder assembly to determine the suitable inclination - among 0°, 15° and 30° - for its takeoff and for its motion during the seeding operation and, in turn, to define the suitable flight plan that increases the batteries autonomy. For this the ANSYS® FLUENT computational tool was used to simulate a wind tunnel which has as principle the Navier-Stokes differential equations, that designates the fluid flow around the UAV/Seeder assembly. The aerodynamic results demonstrated that for take-off the UAV inclination of 30° is the aerodynamically most favorable position due to the lower aerodynamic drag during the climb. Concerning flying motion during the seeding procedure the UAV inclination of 0° is that which leads to lower UAV/Seeder frontal area and drag coefficient.

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.

Utilizing Monte-Carlo radiation transport and spallation cross sections to estimate nuclide dependent scaling with altitude

Science.gov (United States)

Argento, D.; Reedy, R. C.; Stone, J.

2010-12-01

Cosmogenic Nuclides (CNs) are a critical new tool for geomorphology, allowing researchers to date Earth surface events and measure process rates [1]. Prior to CNs, many of these events and processes had no absolute method for measurement and relied entirely on relative methods [2]. Continued improvements in CN methods are necessary for expanding analytic capability in geomorphology. In the last two decades, significant progress has been made in refining these methods and reducing analytic uncertainties [1,3]. Calibration data and scaling methods are being developed to provide a self consistent platform for use in interpreting nuclide concentration values into geologic data [4]. However, nuclide dependent scaling has been difficult to address due to analytic uncertainty and sparseness in altitude transects. Artificial target experiments are underway, but these experiments take considerable time for nuclide buildup in lower altitudes. In this study, a Monte Carlo method radiation transport code, MCNPX, is used to model the galactic cosmic-ray radiation impinging on the upper atmosphere and track the resulting secondary particles through a model of the Earth’s atmosphere and lithosphere. To address the issue of nuclide dependent scaling, the neutron flux values determined by the MCNPX simulation are folded in with estimated cross-section values [5,6]. Preliminary calculations indicate that scaling of nuclide production potential in free air seems to be a function of both altitude and nuclide production pathway. At 0 g/cm2 (sea-level) all neutron spallation pathways have attenuation lengths within 1% of 130 g/cm2. However, the differences in attenuation length are exacerbated with increasing altitude. At 530 g/cm2 atmospheric height (~5,500 m), the apparent attenuation lengths for aggregate SiO2(n,x)10Be, aggregate SiO2(n,x)14C and K(n,x)36Cl become 149.5 g/cm2, 151 g/cm2 and 148 g/cm2 respectively. At 700 g/cm2 atmospheric height (~8,400m - close to the highest

OMNIDIRECTIONAL PERCEPTION FOR LIGHTWEIGHT UAVS USING A CONTINUOUSLY ROTATING 3D LASER SCANNER

Directory of Open Access Journals (Sweden)

D. Droeschel

2013-08-01

Full Text Available Many popular unmanned aerial vehicles (UAV are restricted in their size and weight, making the design of sensory systems for these robots challenging. We designed a small and lightweight continuously rotating 3D laser scanner – allowing for environment perception in a range of 30 m in almost all directions. This sensor it well suited for applications such as 3D obstacle detection, 6D motion estimation, localization, and mapping. We aggregate the distance measurements in a robot-centric grid-based map. To estimate the motion of our multicopter, we register 3D laser scans towards this local map. In experiments, we compare the laser-based ego-motion estimate with ground-truth from a motion capture system. Overall, we can build an accurate 3D obstacle map and can estimate the vehicle's trajectory by 3D scan registration.

The Quality of Quantity: Mini-UAVS As An Alternative UAV Acquisition Strategy at the Army Brigade Level

National Research Council Canada - National Science Library

Weed, Shawn

2002-01-01

This monograph asks should the U.S. Army alter its current UAV acquisition strategy for maneuver brigades from one in which limited numbers of high capability systems are acquired, in favor of another that fields a large quantity...

Distributed Flight Controls for UAVs, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — Two novel flight control actuation concepts for UAV applications are proposed for research and development, both of which incorporate shape memory alloy (SMA) wires...

Impact of Prior Flight Experience on Learning Predator UAV Operator Skills

Science.gov (United States)

2002-02-01

UAVs are becoming a mainstay of intelligence , surveillance, and reconnaissance (ISR) information gathering, with the capability of supplying, in...indicators of UAV pilot skill, namely frequency and type of videogame playing, and experience with remote-controlled hobby aircraft. Experience with...indicator, artificial horizon, heading rate indicator, and engine revolutions per minute. The right monitor displays other useful information, such as a

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