Waypoint Generation Based on Sensor Aimpoint

Science.gov (United States)

2009-03-01

United States Government . AFIT/GAE/ENV/09-M01 WAYPOINT GENERATION BASED ON SENSOR AIMPOINT THESIS Presented to the Faculty Department of Aeronautical...BATCAM. Aviones physics parameters for the Procerus testbed, the Unicorn UAV, were provided by Procerus, which allowed another simulated MAV to 48 be...flown in the HIL tests. The AFIT Advanced Navigation Technologies (ANT) Center did not own a Unicorn UAV, so it could not be flown in flight tests

A Correction Method for UAV Helicopter Airborne Temperature and Humidity Sensor

Directory of Open Access Journals (Sweden)

Longqing Fan

2017-01-01

Full Text Available This paper presents a correction method for UAV helicopter airborne temperature and humidity including an error correction scheme and a bias-calibration scheme. As rotor downwash flow brings measurement error on helicopter airborne sensors inevitably, the error correction scheme constructs a model between the rotor induced velocity and temperature and humidity by building the heat balance equation for platinum resistor temperature sensor and the pressure correction term for humidity sensor. The induced velocity of a spatial point below the rotor disc plane can be calculated by the sum of the induced velocities excited by center line vortex, rotor disk vortex, and skew cylinder vortex based on the generalized vortex theory. In order to minimize the systematic biases, the bias-calibration scheme adopts a multiple linear regression to achieve a systematically consistent result with the tethered balloon profiles. Two temperature and humidity sensors were mounted on “Z-5” UAV helicopter in the field experiment. Overall, the result of applying the calibration method shows that the temperature and relative humidity obtained by UAV helicopter closely align with tethered balloon profiles in providing measurements of the temperature profiles and humidity profiles within marine atmospheric boundary layers.

UAV-Assisted Dynamic Clustering of Wireless Sensor Networks for Crop Health Monitoring.

Science.gov (United States)

Uddin, Mohammad Ammad; Mansour, Ali; Jeune, Denis Le; Ayaz, Mohammad; Aggoune, El-Hadi M

2018-02-11

In this study, a crop health monitoring system is developed by using state of the art technologies including wireless sensors and Unmanned Aerial Vehicles (UAVs). Conventionally data is collected from sensor nodes either by fixed base stations or mobile sinks. Mobile sinks are considered a better choice nowadays due to their improved network coverage and energy utilization. Usually, the mobile sink is used in two ways: either it goes for random walk to find the scattered nodes and collect data, or follows a pre-defined path established by the ground network/clusters. Neither of these options is suitable in our scenario due to the factors like dynamic data collection, the strict targeted area required to be scanned, unavailability of a large number of nodes, dynamic path of the UAV, and most importantly, none of these are known in advance. The contribution of this paper is the formation of dynamic runtime clusters of field sensors by considering the above mentioned factors. Furthermore a mechanism (Bayesian classifier) is defined to select best node as cluster head. The proposed system is validated through simulation results, lab and infield experiments using concept devices. The obtained results are encouraging, especially in terms of deployment time, energy, efficiency, throughput and ease of use.

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

Directory of Open Access Journals (Sweden)

Ramūnas Kikutis

2017-09-01

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

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

Science.gov (United States)

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

2017-09-28

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

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.

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.

A Benchmark and Simulator for UAV Tracking

KAUST Repository

Mueller, Matthias; Smith, Neil; Ghanem, Bernard

2016-01-01

In this paper, we propose a new aerial video dataset and benchmark for low altitude UAV target tracking, as well as, a photorealistic UAV simulator that can be coupled with tracking methods. Our benchmark provides the first evaluation of many state-of-the-art and popular trackers on 123 new and fully annotated HD video sequences captured from a low-altitude aerial perspective. Among the compared trackers, we determine which ones are the most suitable for UAV tracking both in terms of tracking accuracy and run-time. The simulator can be used to evaluate tracking algorithms in real-time scenarios before they are deployed on a UAV “in the field”, as well as, generate synthetic but photo-realistic tracking datasets with automatic ground truth annotations to easily extend existing real-world datasets. Both the benchmark and simulator are made publicly available to the vision community on our website to further research in the area of object tracking from UAVs. (https://ivul.kaust.edu.sa/Pages/pub-benchmark-simulator-uav.aspx.). © Springer International Publishing AG 2016.

A Benchmark and Simulator for UAV Tracking

KAUST Repository

Mueller, Matthias

2016-09-16

In this paper, we propose a new aerial video dataset and benchmark for low altitude UAV target tracking, as well as, a photorealistic UAV simulator that can be coupled with tracking methods. Our benchmark provides the first evaluation of many state-of-the-art and popular trackers on 123 new and fully annotated HD video sequences captured from a low-altitude aerial perspective. Among the compared trackers, we determine which ones are the most suitable for UAV tracking both in terms of tracking accuracy and run-time. The simulator can be used to evaluate tracking algorithms in real-time scenarios before they are deployed on a UAV “in the field”, as well as, generate synthetic but photo-realistic tracking datasets with automatic ground truth annotations to easily extend existing real-world datasets. Both the benchmark and simulator are made publicly available to the vision community on our website to further research in the area of object tracking from UAVs. (https://ivul.kaust.edu.sa/Pages/pub-benchmark-simulator-uav.aspx.). © Springer International Publishing AG 2016.

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.

PERFORMANCE CHARACTERISTIC MEMS-BASED IMUs FOR UAVs NAVIGATION

Directory of Open Access Journals (Sweden)

H. A. Mohamed

2015-08-01

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

Performance Characteristic Mems-Based IMUs for UAVs Navigation

Science.gov (United States)

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

2015-08-01

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

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

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

Science.gov (United States)

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

2017-08-30

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

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.

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

Science.gov (United States)

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

2016-06-01

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

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.

Single and Multiple UAV Cyber-Attack Simulation and Performance Evaluation

Directory of Open Access Journals (Sweden)

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.

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

OpenAIRE

Rui Sun; Qi Cheng; Guanyu Wang; Washington Yotto Ochieng

2017-01-01

The use of Unmanned Aerial Vehicles (UAVs) has increased significantly in recent years. On-board integrated navigation sensors are a key component of UAVs’ flight control systems and are essential for flight safety. In order to ensure flight safety, timely and effective navigation sensor fault detection capability is required. In this paper, a novel data-driven Adaptive Neuron Fuzzy Inference System (ANFIS)-based approach is presented for the detection of on-board navigation sensor faults in ...

Cloud Water Content Sensor for Sounding Balloons and Small UAVs

Science.gov (United States)

Bognar, John A.

2009-01-01

A lightweight, battery-powered sensor was developed for measuring cloud water content, which is the amount of liquid or solid water present in a cloud, generally expressed as grams of water per cubic meter. This sensor has near-zero power consumption and can be flown on standard sounding balloons and small, unmanned aerial vehicles (UAVs). The amount of solid or liquid water is important to the study of atmospheric processes and behavior. Previous sensing techniques relied on strongly heating the incoming air, which requires a major energy input that cannot be achieved on sounding balloons or small UAVs.

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.

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.

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.

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.

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

Directory of Open Access Journals (Sweden)

Seyed Mohammadreza Kasaei

2011-12-01

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

USING A MICRO-UAV FOR ULTRA-HIGH RESOLUTION MULTI-SENSOR OBSERVATIONS OF ANTARCTIC MOSS BEDS

Directory of Open Access Journals (Sweden)

A. Lucieer

2012-07-01

Full Text Available This study is the first to use an Unmanned Aerial Vehicle (UAV for mapping moss beds in Antarctica. Mosses can be used as indicators for the regional effects of climate change. Mapping and monitoring their extent and health is therefore important. UAV aerial photography provides ultra-high resolution spatial data for this purpose. We developed a technique to extract an extremely dense 3D point cloud from overlapping UAV aerial photography based on structure from motion (SfM algorithms. The combination of SfM and patch-based multi-view stereo image vision algorithms resulted in a 2 cm resolution digital terrain model (DTM. This detailed topographic information combined with vegetation indices derived from a 6-band multispectral sensor enabled the assessment of moss bed health. This novel UAV system has allowed us to map different environmental characteristics of the moss beds at ultra-high resolution providing us with a better understanding of these fragile Antarctic ecosystems. The paper provides details on the different UAV instruments and the image processing framework resulting in DEMs, vegetation indices, and terrain derivatives.

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.

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

Directory of Open Access Journals (Sweden)

D. Mader

2016-06-01

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

VISION BASED OBSTACLE DETECTION IN UAV IMAGING

Directory of Open Access Journals (Sweden)

S. Badrloo

2017-08-01

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

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.

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

Science.gov (United States)

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

2014-01-01

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

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.

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

Directory of Open Access Journals (Sweden)

Hamza Benzerrouk

2018-03-01

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

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.

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

Directory of Open Access Journals (Sweden)

Amedeo Rodi Vetrella

2016-12-01

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

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.

A performance study of unmanned aerial vehicle-based sensor networks under cyber attack

Science.gov (United States)

Puchaty, Ethan M.

In UAV-based sensor networks, an emerging area of interest is the performance of these networks under cyber attack. This study seeks to evaluate the performance trade-offs from a System-of-Systems (SoS) perspective between various UAV communications architecture options in the context two missions: tracking ballistic missiles and tracking insurgents. An agent-based discrete event simulation is used to model a sensor communication network consisting of UAVs, military communications satellites, ground relay stations, and a mission control center. Network susceptibility to cyber attack is modeled with probabilistic failures and induced data variability, with performance metrics focusing on information availability, latency, and trustworthiness. Results demonstrated that using UAVs as routers increased network availability with a minimal latency penalty and communications satellite networks were best for long distance operations. Redundancy in the number of links between communication nodes helped mitigate cyber-caused link failures and add robustness in cases of induced data variability by an adversary. However, when failures were not independent, redundancy and UAV routing were detrimental in some cases to network performance. Sensitivity studies indicated that long cyber-caused downtimes and increasing failure dependencies resulted in build-ups of failures and caused significant degradations in network performance.

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 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.

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.

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.

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,

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

Science.gov (United States)

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

2017-12-17

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

Open source software and low cost sensors for teaching UAV science

Science.gov (United States)

Kefauver, S. C.; Sanchez-Bragado, R.; El-Haddad, G.; Araus, J. L.

2016-12-01

Drones, also known as UASs (unmanned aerial systems), UAVs (Unmanned Aerial Vehicles) or RPAS (Remotely piloted aircraft systems), are both useful advanced scientific platforms and recreational toys that are appealing to younger generations. As such, they can make for excellent education tools as well as low-cost scientific research project alternatives. However, the process of taking pretty pictures to remote sensing science can be daunting if one is presented with only expensive software and sensor options. There are a number of open-source tools and low cost platform and sensor options available that can provide excellent scientific research results, and, by often requiring more user-involvement than commercial software and sensors, provide even greater educational benefits. Scale-invariant feature transform (SIFT) algorithm implementations, such as the Microsoft Image Composite Editor (ICE), which can create quality 2D image mosaics with some motion and terrain adjustments and VisualSFM (Structure from Motion), which can provide full image mosaicking with movement and orthorectification capacities. RGB image quantification using alternate color space transforms, such as the BreedPix indices, can be calculated via plugins in the open-source software Fiji (http://fiji.sc/Fiji; http://github.com/george-haddad/CIMMYT). Recent analyses of aerial images from UAVs over different vegetation types and environments have shown RGB metrics can outperform more costly commercial sensors. Specifically, Hue-based pixel counts, the Triangle Greenness Index (TGI), and the Normalized Green Red Difference Index (NGRDI) consistently outperformed NDVI in estimating abiotic and biotic stress impacts on crop health. Also, simple kits are available for NDVI camera conversions. Furthermore, suggestions for multivariate analyses of the different RGB indices in the "R program for statistical computing", such as classification and regression trees can allow for a more approachable

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....

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

Science.gov (United States)

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

2013-01-01

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

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

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

Science.gov (United States)

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

2017-12-01

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

Coupled sensor/platform control design for low-level chemical detection with position-adaptive micro-UAVs

Science.gov (United States)

Goodwin, Thomas; Carr, Ryan; Mitra, Atindra K.; Selmic, Rastko R.

2009-05-01

We discuss the development of Position-Adaptive Sensors [1] for purposes for detecting embedded chemical substances in challenging environments. This concept is a generalization of patented Position-Adaptive Radar Concepts developed at AFRL for challenging conditions such as urban environments. For purposes of investigating the detection of chemical substances using multiple MAV (Micro-UAV) platforms, we have designed and implemented an experimental testbed with sample structures such as wooden carts that contain controlled leakage points. Under this general concept, some of the members of a MAV swarm can serve as external position-adaptive "transmitters" by blowing air over the cart and some of the members of a MAV swarm can serve as external position-adaptive "receivers" that are equipped with chemical or biological (chem/bio) sensors that function as "electronic noses". The objective can be defined as improving the particle count of chem/bio concentrations that impinge on a MAV-based position-adaptive sensor that surrounds a chemical repository, such as a cart, via the development of intelligent position-adaptive control algorithms. The overall effect is to improve the detection and false-alarm statistics of the overall system. Within the major sections of this paper, we discuss a number of different aspects of developing our initial MAV-Based Sensor Testbed. This testbed includes blowers to simulate position-adaptive excitations and a MAV from Draganfly Innovations Inc. with stable design modifications to accommodate our chem/bio sensor boom design. We include details with respect to several critical phases of the development effort including development of the wireless sensor network and experimental apparatus, development of the stable sensor boom for the MAV, integration of chem/bio sensors and sensor node onto the MAV and boom, development of position-adaptive control algorithms and initial tests at IDCAST (Institute for the Development and

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

OpenAIRE

Soufiene Bouallègue; Rabii Fessi

2016-01-01

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

a Three-Dimensional Simulation and Visualization System for Uav Photogrammetry

Science.gov (United States)

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.

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

Science.gov (United States)

Mejia-Aguilar, Abraham

2016-04-01

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

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

Science.gov (United States)

Qiu, Huaxin; Duan, Haibin

2017-11-01

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

ARBRES: Light-Weight CW/FM SAR Sensors for Small UAVs

Directory of Open Access Journals (Sweden)

Xavier Fabregas

2013-03-01

Full Text Available This paper describes a pair of compact CW/FM airborne SAR systems for small UAV-based operation (wingspan of 3.5 m for low-cost testing of innovative SAR concepts. Two different SAR instruments, using the C and X bands, have been developed in the context of the ARBRES project, each of them achieving a payload weight below 5 Kg and a volume of 13.5 dm3 (sensor and controller. Every system has a dual receiving channel which allows operation in interferometric or polarimetric modes. Planar printed array antennas are used in both sensors for easy system integration and better isolation between transmitter and receiver subsystems. First experimental tests on board a 3.2 m wingspan commercial radio-controlled aircraft are presented. The SAR images of a field close to an urban area have been focused using a back-projection algorithm. Using the dual channel capability, a single pass interferogram and Digital Elevation Model (DEM has been obtained which agrees with the scene topography. A simple Motion Compensation (MoCo module, based on the information from an Inertial+GPS unit, has been included to compensate platform motion errors with respect to the nominal straight trajectory.

COMPARISON OF DIGITAL SURFACE MODELS FOR SNOW DEPTH MAPPING WITH UAV AND AERIAL CAMERAS

Directory of Open Access Journals (Sweden)

R. Boesch

2016-06-01

Full Text Available Photogrammetric workflows for aerial images have improved over the last years in a typically black-box fashion. Most parameters for building dense point cloud are either excessive or not explained and often the progress between software releases is poorly documented. On the other hand, development of better camera sensors and positional accuracy of image acquisition is significant by comparing product specifications. This study shows, that hardware evolutions over the last years have a much stronger impact on height measurements than photogrammetric software releases. Snow height measurements with airborne sensors like the ADS100 and UAV-based DSLR cameras can achieve accuracies close to GSD * 2 in comparison with ground-based GNSS reference measurements. Using a custom notch filter on the UAV camera sensor during image acquisition does not yield better height accuracies. UAV based digital surface models are very robust. Different workflow parameter variations for ADS100 and UAV camera workflows seem to have only random effects.

UAV-borne lidar with MEMS mirror-based scanning capability

Science.gov (United States)

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

2016-05-01

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

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.

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

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

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

Science.gov (United States)

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

2018-01-17

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

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

Science.gov (United States)

Vanegas, Fernando; Weiss, John; Gonzalez, Felipe

2018-01-01

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

Contour Detection for UAV-Based Cadastral Mapping

Directory of Open Access Journals (Sweden)

Sophie Crommelinck

2017-02-01

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

Distributed Cooperative Search Control Method of Multiple UAVs for Moving Target

Directory of Open Access Journals (Sweden)

Chang-jian Ru

2015-01-01

Full Text Available To reduce the impact of uncertainties caused by unknown motion parameters on searching plan of moving targets and improve the efficiency of UAV’s searching, a novel distributed Multi-UAVs cooperative search control method for moving target is proposed in this paper. Based on detection results of onboard sensors, target probability map is updated using Bayesian theory. A Gaussian distribution of target transition probability density function is introduced to calculate prediction probability of moving target existence, and then target probability map can be further updated in real-time. A performance index function combining with target cost, environment cost, and cooperative cost is constructed, and the cooperative searching problem can be transformed into a central optimization problem. To improve computational efficiency, the distributed model predictive control method is presented, and thus the control command of each UAV can be obtained. The simulation results have verified that the proposed method can avoid the blindness of UAV searching better and improve overall efficiency of the team effectively.

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.

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.

Development of a bio-inspired UAV perching system

Science.gov (United States)

Xie, Pu

Although technologies of unmanned aerial vehicles (UAVs) including micro air vehicles (MAVs) have been greatly advanced in the recent years, it is still very difficult for a UAV to perform some very challenging tasks such as perching to any desired spot reliably and agilely like a bird. Unlike the UAVs, the biological control mechanism of birds has been optimized through millions of year evolution and hence, they can perform many extremely maneuverability tasks, such as perching or grasping accurately and robustly. Therefore, we have good reason to learn from the nature in order to significantly improve the capabilities of UAVs. The development of a UAV perching system is becoming feasible, especially after a lot of research contributions in ornithology which involve the analysis of the bird's functionalities. Meanwhile, as technology advances in many engineering fields, such as airframes, propulsion, sensors, batteries, micro-electromechanical-system (MEMS), and UAV technology is also advancing rapidly. All of these research efforts in ornithology and the fast growing development technologies in UAV applications are motivating further interests and development in the area of UAV perching and grasping research. During the last decade, the research contributions about UAV perching and grasping were mainly based on fixed-wing, flapping-wing, and rotorcraft UAVs. However, most of the current researches in UAV systems with perching and grasping capability are focusing on either active (powered) grasping and perching or passive (unpowered) perching. Although birds do have both active and passive perching capabilities depending on their needs, there is no UAV perching system with both capabilities. In this project, we focused on filling this gap. Inspired by the anatomy analysis of bird legs and feet, a novel perching system has been developed to implement the bionics action for both active grasping and passive perching. In addition, for developing a robust and

Bio-inspired UAV routing, source localization, and acoustic signature classification for persistent surveillance

Science.gov (United States)

Burman, Jerry; Hespanha, Joao; Madhow, Upamanyu; Pham, Tien

2011-06-01

A team consisting of Teledyne Scientific Company, the University of California at Santa Barbara and the Army Research Laboratory* is developing technologies in support of automated data exfiltration from heterogeneous battlefield sensor networks to enhance situational awareness for dismounts and command echelons. Unmanned aerial vehicles (UAV) provide an effective means to autonomously collect data from a sparse network of unattended ground sensors (UGSs) that cannot communicate with each other. UAVs are used to reduce the system reaction time by generating autonomous collection routes that are data-driven. Bio-inspired techniques for search provide a novel strategy to detect, capture and fuse data. A fast and accurate method has been developed to localize an event by fusing data from a sparse number of UGSs. This technique uses a bio-inspired algorithm based on chemotaxis or the motion of bacteria seeking nutrients in their environment. A unique acoustic event classification algorithm was also developed based on using swarm optimization. Additional studies addressed the problem of routing multiple UAVs, optimally placing sensors in the field and locating the source of gunfire at helicopters. A field test was conducted in November of 2009 at Camp Roberts, CA. The field test results showed that a system controlled by bio-inspired software algorithms can autonomously detect and locate the source of an acoustic event with very high accuracy and visually verify the event. In nine independent test runs of a UAV, the system autonomously located the position of an explosion nine times with an average accuracy of 3 meters. The time required to perform source localization using the UAV was on the order of a few minutes based on UAV flight times. In June 2011, additional field tests of the system will be performed and will include multiple acoustic events, optimal sensor placement based on acoustic phenomenology and the use of the International Technology Alliance (ITA

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.

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.

Hierarchical heuristic search using a Gaussian mixture model for UAV coverage planning.

Science.gov (United States)

Lin, Lanny; Goodrich, Michael A

2014-12-01

During unmanned aerial vehicle (UAV) search missions, efficient use of UAV flight time requires flight paths that maximize the probability of finding the desired subject. The probability of detecting the desired subject based on UAV sensor information can vary in different search areas due to environment elements like varying vegetation density or lighting conditions, making it likely that the UAV can only partially detect the subject. This adds another dimension of complexity to the already difficult (NP-Hard) problem of finding an optimal search path. We present a new class of algorithms that account for partial detection in the form of a task difficulty map and produce paths that approximate the payoff of optimal solutions. The algorithms use the mode goodness ratio heuristic that uses a Gaussian mixture model to prioritize search subregions. The algorithms search for effective paths through the parameter space at different levels of resolution. We compare the performance of the new algorithms against two published algorithms (Bourgault's algorithm and LHC-GW-CONV algorithm) in simulated searches with three real search and rescue scenarios, and show that the new algorithms outperform existing algorithms significantly and can yield efficient paths that yield payoffs near the optimal.

A mini-UAV VTOL Platform for Surveying Applications

Directory of Open Access Journals (Sweden)

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.

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.

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...

Health monitoring of unmanned aerial vehicle based on optical fiber sensor array

Science.gov (United States)

Luo, Yuxiang; Shen, Jingshi; Shao, Fei; Guo, Chunhui; Yang, Ning; Zhang, Jiande

2017-10-01

The unmanned aerial vehicle (UAV) in flight needs to face the complicated environment, especially to withstand harsh weather conditions, such as the temperature and pressure. Compared with conventional sensors, fiber Bragg grating (FBG) sensor has the advantages of small size, light weight, high reliability, high precision, anti-electromagnetic interference, long lift-span, moistureproof and good resistance to causticity. It's easy to be embedded in composite structural components of UAVs. In the paper, over 1000 FBG sensors distribute regularly on a wide range of UAVs body, combining wavelength division multiplexing (WDM), time division multiplexing (TDM) and multichannel parallel architecture. WDM has the advantage of high spatial resolution. TDM has the advantage of large capacity and wide range. It is worthful to constitute a sensor network by different technologies. For the signal demodulation of FBG sensor array, WDM works by means of wavelength scanning light sources and F-P etalon. TDM adopts the technology of optical time-domain reflectometry. In order to demodulate efficiently, the most proper sensor multiplex number with some reflectivity is given by the curves fitting. Due to the regular array arrangement of FBG sensors on the UAVs, we can acquire the health state of UAVs in the form of 3D visualization. It is helpful to master the information of health status rapidly and give a real-time health evaluation.

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

Science.gov (United States)

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

2017-01-01

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

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

Building a High-Precision 2D Hydrodynamic Flood Model Using UAV Photogrammetry and Sensor Network Monitoring

Directory of Open Access Journals (Sweden)

Jakub Langhammer

2017-11-01

Full Text Available This paper explores the potential of the joint application of unmanned aerial vehicle (UAV-based photogrammetry and an automated sensor network for building a hydrodynamic flood model of a montane stream. UAV-based imagery was used for three-dimensional (3D photogrammetric reconstruction of the stream channel, achieving a resolution of 1.5 cm/pixel. Automated ultrasonic water level gauges, operating with a 10 min interval, were used as a source of hydrological data for the model calibration, and the MIKE 21 hydrodynamic model was used for building the flood model. Three different horizontal schematizations of the channel—an orthogonal grid, curvilinear grid, and flexible mesh—were used to evaluate the effect of spatial discretization on the results. The research was performed on Javori Brook, a montane stream in the Sumava (Bohemian Forest Mountains, Czech Republic, Central Europe, featuring a fast runoff response to precipitation events and that is located in a core zone of frequent flooding. The studied catchments have been, since 2007, equipped with automated water level gauges and, since 2013, under repeated UAV monitoring. The study revealed the high potential of these data sources for applications in hydrodynamic modeling. In addition to the ultra-high levels of spatial and temporal resolution, the major contribution is in the method’s high operability, enabling the building of highly detailed flood models even in remote areas lacking conventional monitoring. The testing of the data sources and model setup indicated the limitations of the UAV reconstruction of the stream bathymetry, which was completed by the geodetic-grade global navigation satellite system (GNSS measurements. The testing of the different model domain schematizations did not indicate the substantial differences that are typical for conventional low-resolution data, proving the high reliability of the tested modeling workflow.

Introducing a Low-Cost Mini-Uav for - and Multispectral-Imaging

Science.gov (United States)

Bendig, J.; Bolten, A.; Bareth, G.

2012-07-01

The trend to minimize electronic devices also accounts for Unmanned Airborne Vehicles (UAVs) as well as for sensor technologies and imaging devices. Consequently, it is not surprising that UAVs are already part of our daily life and the current pace of development will increase civil applications. A well known and already wide spread example is the so called flying video game based on Parrot's AR.Drone which is remotely controlled by an iPod, iPhone, or iPad (http://ardrone.parrot.com). The latter can be considered as a low-weight and low-cost Mini-UAV. In this contribution a Mini-UAV is considered to weigh less than 5 kg and is being able to carry 0.2 kg to 1.5 kg of sensor payload. While up to now Mini-UAVs like Parrot's AR.Drone are mainly equipped with RGB cameras for videotaping or imaging, the development of such carriage systems clearly also goes to multi-sensor platforms like the ones introduced for larger UAVs (5 to 20 kg) by Jaakkolla et al. (2010) for forestry applications or by Berni et al. (2009) for agricultural applications. The problem when designing a Mini-UAV for multi-sensor imaging is the limitation of payload of up to 1.5 kg and a total weight of the whole system below 5 kg. Consequently, the Mini-UAV without sensors but including navigation system and GPS sensors must weigh less than 3.5 kg. A Mini-UAV system with these characteristics is HiSystems' MK-Okto (www.mikrokopter.de). Total weight including battery without sensors is less than 2.5 kg. Payload of a MK-Okto is approx. 1 kg and maximum speed is around 30 km/h. The MK-Okto can be operated up to a wind speed of less than 19 km/h which corresponds to Beaufort scale number 3 for wind speed. In our study, the MK-Okto is equipped with a handheld low-weight NEC F30IS thermal imaging system. The F30IS which was developed for veterinary applications, covers 8 to 13 μm, weighs only 300 g, and is capturing the temperature range between -20 °C and 100 °C. Flying at a height of 100 m, the camera

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

Science.gov (United States)

Nodland, David; Zargarzadeh, Hassan; Jagannathan, Sarangapani

2013-07-01

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

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.

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 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 State Estimation Modeling Techniques in AHRS

Science.gov (United States)

Razali, Shikin; Zhahir, Amzari

2017-11-01

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

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.

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.

INTRODUCING A LOW-COST MINI-UAV FOR THERMAL- AND MULTISPECTRAL-IMAGING

Directory of Open Access Journals (Sweden)

J. Bendig

2012-07-01

Full Text Available The trend to minimize electronic devices also accounts for Unmanned Airborne Vehicles (UAVs as well as for sensor technologies and imaging devices. Consequently, it is not surprising that UAVs are already part of our daily life and the current pace of development will increase civil applications. A well known and already wide spread example is the so called flying video game based on Parrot's AR.Drone which is remotely controlled by an iPod, iPhone, or iPad (http://ardrone.parrot.com. The latter can be considered as a low-weight and low-cost Mini-UAV. In this contribution a Mini-UAV is considered to weigh less than 5 kg and is being able to carry 0.2 kg to 1.5 kg of sensor payload. While up to now Mini-UAVs like Parrot's AR.Drone are mainly equipped with RGB cameras for videotaping or imaging, the development of such carriage systems clearly also goes to multi-sensor platforms like the ones introduced for larger UAVs (5 to 20 kg by Jaakkolla et al. (2010 for forestry applications or by Berni et al. (2009 for agricultural applications. The problem when designing a Mini-UAV for multi-sensor imaging is the limitation of payload of up to 1.5 kg and a total weight of the whole system below 5 kg. Consequently, the Mini-UAV without sensors but including navigation system and GPS sensors must weigh less than 3.5 kg. A Mini-UAV system with these characteristics is HiSystems' MK-Okto (www.mikrokopter.de. Total weight including battery without sensors is less than 2.5 kg. Payload of a MK-Okto is approx. 1 kg and maximum speed is around 30 km/h. The MK-Okto can be operated up to a wind speed of less than 19 km/h which corresponds to Beaufort scale number 3 for wind speed. In our study, the MK-Okto is equipped with a handheld low-weight NEC F30IS thermal imaging system. The F30IS which was developed for veterinary applications, covers 8 to 13 μm, weighs only 300 g, and is capturing the temperature range between −20 °C and 100 °C. Flying at a height of

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

Directory of Open Access Journals (Sweden)

Mohand Achour Touat

2008-04-01

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

Sensor-driven area coverage for an autonomous fixed-wing unmanned aerial vehicle.

Science.gov (United States)

Paull, Liam; Thibault, Carl; Nagaty, Amr; Seto, Mae; Li, Howard

2014-09-01

Area coverage with an onboard sensor is an important task for an unmanned aerial vehicle (UAV) with many applications. Autonomous fixed-wing UAVs are more appropriate for larger scale area surveying since they can cover ground more quickly. However, their non-holonomic dynamics and susceptibility to disturbances make sensor coverage a challenging task. Most previous approaches to area coverage planning are offline and assume that the UAV can follow the planned trajectory exactly. In this paper, this restriction is removed as the aircraft maintains a coverage map based on its actual pose trajectory and makes control decisions based on that map. The aircraft is able to plan paths in situ based on sensor data and an accurate model of the on-board camera used for coverage. An information theoretic approach is used that selects desired headings that maximize the expected information gain over the coverage map. In addition, the branch entropy concept previously developed for autonomous underwater vehicles is extended to UAVs and ensures that the vehicle is able to achieve its global coverage mission. The coverage map over the workspace uses the projective camera model and compares the expected area of the target on the ground and the actual area covered on the ground by each pixel in the image. The camera is mounted on a two-axis gimbal and can either be stabilized or optimized for maximal coverage. Hardware-in-the-loop simulation results and real hardware implementation on a fixed-wing UAV show the effectiveness of the approach. By including the already developed automatic takeoff and landing capabilities, we now have a fully automated and robust platform for performing aerial imagery surveys.

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...

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.

Multimodal UAV detection: study of various intrusion scenarios

Science.gov (United States)

Hengy, Sebastien; Laurenzis, Martin; Schertzer, Stéphane; Hommes, Alexander; Kloeppel, Franck; Shoykhetbrod, Alex; Geibig, Thomas; Johannes, Winfried; Rassy, Oussama; Christnacher, Frank

2017-10-01

Small unmanned aerial vehicles (UAVs) are becoming increasingly popular and affordable the last years for professional and private consumer market, with varied capacities and performances. Recent events showed that illicit or hostile uses constitute an emergent, quickly evolutionary threat. Recent developments in UAV technologies tend to bring autonomous, highly agile and capable unmanned aerial vehicles to the market. These UAVs can be used for spying operations as well as for transporting illicit or hazardous material (smuggling, flying improvised explosive devices). The scenario of interest concerns the protection of sensitive zones against the potential threat constituted by small drones. In the recent past, field trials were carried out to investigate the detection and tracking of multiple UAV flying at low altitude. Here, we present results which were achieved using a heterogeneous sensor network consisting of acoustic antennas, small FMCW RADAR systems and optical sensors. While acoustics and RADAR was applied to monitor a wide azimuthal area (360°), optical sensors were used for sequentially identification. The localization results have been compared to the ground truth data to estimate the efficiency of each detection system. Seven-microphone acoustic arrays allow single source localization. The mean azimuth and elevation estimation error has been measured equal to 1.5 and -2.5 degrees respectively. The FMCW radar allows tracking of multiple UAVs by estimating their range, azimuth and motion speed. Both technologies can be linked to the electro-optical system for final identification of the detected object.

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.

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

KAUST Repository

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

2016-01-01

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

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

KAUST Repository

Smith, Neil G.

2016-04-07

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

Spatial Co-Registration of Ultra-High Resolution Visible, Multispectral and Thermal Images Acquired with a Micro-UAV over Antarctic Moss Beds

Directory of Open Access Journals (Sweden)

Darren Turner

2014-05-01

Full Text Available In recent times, the use of Unmanned Aerial Vehicles (UAVs as tools for environmental remote sensing has become more commonplace. Compared to traditional airborne remote sensing, UAVs can provide finer spatial resolution data (up to 1 cm/pixel and higher temporal resolution data. For the purposes of vegetation monitoring, the use of multiple sensors such as near infrared and thermal infrared cameras are of benefit. Collecting data with multiple sensors, however, requires an accurate spatial co-registration of the various UAV image datasets. In this study, we used an Oktokopter UAV to investigate the physiological state of Antarctic moss ecosystems using three sensors: (i a visible camera (1 cm/pixel, (ii a 6 band multispectral camera (3 cm/pixel, and (iii a thermal infrared camera (10 cm/pixel. Imagery from each sensor was geo-referenced and mosaicked with a combination of commercially available software and our own algorithms based on the Scale Invariant Feature Transform (SIFT. The validation of the mosaic’s spatial co-registration revealed a mean root mean squared error (RMSE of 1.78 pixels. A thematic map of moss health, derived from the multispectral mosaic using a Modified Triangular Vegetation Index (MTVI2, and an indicative map of moss surface temperature were then combined to demonstrate sufficient accuracy of our co-registration methodology for UAV-based monitoring of Antarctic moss beds.

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.

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

Directory of Open Access Journals (Sweden)

T. K. Kohoutek

2012-07-01

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

Simulated minimum detectable activity concentration (MDAC) for a real-time UAV airborne radioactivity monitoring system with HPGe and LaBr_3 detectors

International Nuclear Information System (INIS)

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

2016-01-01

An automatic real-time UAV airborne radioactivity monitoring system with high-purity germanium (HPGe) and lanthanum bromide (LaBr_3) detectors (NH-UAV) was developed to precisely obtain small-scope nuclide information in major nuclear accidents. The specific minimum detectable activity concentration (MDAC) calculation method for NH-UAV in the atmospheric environment was deduced in this study for a priori evaluation and quantification of the suitability of NH-UAV in the Fukushima nuclear accident, where the MDAC values of this new equipment were calculated based on Monte Carlo simulation. The effects of radioactive source term size and activity concentration on the MDAC values were analyzed to assess the detection performance of NH-UAV in more realistic environments. Finally, the MDAC values were calculated at different shielding thicknesses of the HPGe detector to improve the detection capabilities of the HPGe detector, and the relationship between the MDAC and the acquisition time of the system was deduced. The MDAC calculation method and data results in this study may be used as a reference for in-situ radioactivity measurement of NH-UAV. - Highlights: • A real-time UAV airborne radioactivity monitoring system (NH-UAV) was developed. • The efficiency calculations and MDAC values are given. • NH-UAV is able to monitor major nuclear accidents, such as the Fukushima accident. • The source term size can influence the detection sensitivity of the system. • The HPGe detector possesses measurement thresholds on activity concentration.

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

sensing capability of a novel airborne UV detector was verified with a standard ground-based instrument. Flights with this sensor showed that UAV measurement operations and recording methods are viable. With improved sensor range, UAVs equipped with compact UV sensors could serve as the detection elements in a self-diagnosing power grid. (3) Simplification of rich lidar maps to polyhedral obstacle maps reduces data volume by orders of magnitude, so that computation with the resultant maps in real time is possible. This enables real-time obstacle avoidance autonomy. Stable navigation may be feasible in the GPS-deprived environment near transmission lines by a UAV that senses ground structures and compares them to these simplified maps. (4) A new, formally verified path conformance software system that runs onboard a UAV was demonstrated in flight for the first time. It successfully maneuvered the aircraft after a sudden lateral perturbation that models a gust of wind, and processed lidar-derived polyhedral obstacle maps in real time. (5) Tracking of the UAV in the national airspace using the NASA UTM technology was a key safety component of this reference mission, since the flights were conducted beneath the landing approach to a heavily used runway. Comparison to autopilot tracking showed that UTM tracking accurately records the UAV position throughout the flight path.

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

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

Directory of Open Access Journals (Sweden)

Andreas Burkart

2015-01-01

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

DEVELOP Chesapeake Bay Watershed Hydrology - UAV Sensor Web

Science.gov (United States)

Holley, S. D.; Baruah, A.

2008-12-01

The Chesapeake Bay is the largest estuary in the United States, with a watershed extending through six states and the nation's capital. Urbanization and agriculture practices have led to an excess runoff of nutrients and sediment into the bay. Nutrients and sediment loading stimulate the growth of algal blooms associated with various problems including localized dissolved oxygen deficiencies, toxic algal blooms and death of marine life. The Chesapeake Bay Program, among other stakeholder organizations, contributes greatly to the restoration efforts of the Chesapeake Bay. These stakeholders contribute in many ways such as monitoring the water quality, leading clean-up projects, and actively restoring native habitats. The first stage of the DEVELOP Chesapeake Bay Coastal Management project, relating to water quality, contributed to the restoration efforts by introducing NASA satellite-based water quality data products to the stakeholders as a complement to their current monitoring methods. The second stage, to be initiated in the fall 2008 internship term, will focus on the impacts of land cover variability within the Chesapeake Bay Watershed. Multiple student led discussions with members of the Land Cover team at the Chesapeake Bay Program Office in the DEVELOP GSFC 2008 summer term uncovered the need for remote sensing data for hydrological mapping in the watershed. The Chesapeake Bay Program expressed in repeated discussions on Land Cover mapping that significant portions of upper river areas, streams, and the land directly interfacing those waters are not accurately depicted in the watershed model. Without such hydrological mapping correlated with land cover data the model will not be useful in depicting source areas of nutrient loading which has an ecological and economic impact in and around the Chesapeake Bay. The fall 2008 DEVELOP team will examine the use of UAV flown sensors in connection with in-situ and Earth Observation satellite data. To maximize the

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.

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

Directory of Open Access Journals (Sweden)

Ali Moltajaei Farid

2013-01-01

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

Real-time Collision Avoidance and Path Optimizer for Semi-autonomous UAVs.

Science.gov (United States)

Hawary, A. F.; Razak, N. A.

2018-05-01

Whilst UAV offers a potentially cheaper and more localized observation platform than current satellite or land-based approaches, it requires an advance path planner to reveal its true potential, particularly in real-time missions. Manual control by human will have limited line-of-sights and prone to errors due to careless and fatigue. A good alternative solution is to equip the UAV with semi-autonomous capabilities that able to navigate via a pre-planned route in real-time fashion. In this paper, we propose an easy-and-practical path optimizer based on the classical Travelling Salesman Problem and adopts a brute force search method to re-optimize the route in the event of collisions using range finder sensor. The former utilizes a Simple Genetic Algorithm and the latter uses Nearest Neighbour algorithm. Both algorithms are combined to optimize the route and avoid collision at once. Although many researchers proposed various path planning algorithms, we find that it is difficult to integrate on a basic UAV model and often lacks of real-time collision detection optimizer. Therefore, we explore a practical benefit from this approach using on-board Arduino and Ardupilot controllers by manually emulating the motion of an actual UAV model prior to test on the flying site. The result showed that the range finder sensor provides a real-time data to the algorithm to find a collision-free path and eventually optimized the route successfully.

Flocking of quad-rotor UAVs with fuzzy control.

Science.gov (United States)

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.

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.

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.

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.

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.

Modeling and simulation of dynamic ant colony's labor division for task allocation of UAV swarm

Science.gov (United States)

Wu, Husheng; Li, Hao; Xiao, Renbin; Liu, Jie

2018-02-01

The problem of unmanned aerial vehicle (UAV) task allocation not only has the intrinsic attribute of complexity, such as highly nonlinear, dynamic, highly adversarial and multi-modal, but also has a better practicability in various multi-agent systems, which makes it more and more attractive recently. In this paper, based on the classic fixed response threshold model (FRTM), under the idea of "problem centered + evolutionary solution" and by a bottom-up way, the new dynamic environmental stimulus, response threshold and transition probability are designed, and a dynamic ant colony's labor division (DACLD) model is proposed. DACLD allows a swarm of agents with a relatively low-level of intelligence to perform complex tasks, and has the characteristic of distributed framework, multi-tasks with execution order, multi-state, adaptive response threshold and multi-individual response. With the proposed model, numerical simulations are performed to illustrate the effectiveness of the distributed task allocation scheme in two situations of UAV swarm combat (dynamic task allocation with a certain number of enemy targets and task re-allocation due to unexpected threats). Results show that our model can get both the heterogeneous UAVs' real-time positions and states at the same time, and has high degree of self-organization, flexibility and real-time response to dynamic environments.

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

Wetland Vegetation Integrity Assessment with Low Altitude Multispectral Uav Imagery

Science.gov (United States)

Boon, M. A.; Tesfamichael, S.

2017-08-01

The use of multispectral sensors on Unmanned Aerial Vehicles (UAVs) was until recently too heavy and bulky although this changed in recent times and they are now commercially available. The focus on the usage of these sensors is mostly directed towards the agricultural sector where the focus is on precision farming. Applications of these sensors for mapping of wetland ecosystems are rare. Here, we evaluate the performance of low altitude multispectral UAV imagery to determine the state of wetland vegetation in a localised spatial area. Specifically, NDVI derived from multispectral UAV imagery was used to inform the determination of the integrity of the wetland vegetation. Furthermore, we tested different software applications for the processing of the imagery. The advantages and disadvantages we experienced of these applications are also shortly presented in this paper. A JAG-M fixed-wing imaging system equipped with a MicaScene RedEdge multispectral camera were utilised for the survey. A single surveying campaign was undertaken in early autumn of a 17 ha study area at the Kameelzynkraal farm, Gauteng Province, South Africa. Structure-from-motion photogrammetry software was used to reconstruct the camera position's and terrain features to derive a high resolution orthoretified mosaic. MicaSense Atlas cloud-based data platform, Pix4D and PhotoScan were utilised for the processing. The WET-Health level one methodology was followed for the vegetation assessment, where wetland health is a measure of the deviation of a wetland's structure and function from its natural reference condition. An on-site evaluation of the vegetation integrity was first completed. Disturbance classes were then mapped using the high resolution multispectral orthoimages and NDVI. The WET-Health vegetation module completed with the aid of the multispectral UAV products indicated that the vegetation of the wetland is largely modified ("D" PES Category) and that the condition is expected to

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.

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.

UAV-based Radar Sounding of Antarctic Ice

Science.gov (United States)

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

2014-05-01

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

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.

Dual-Stack Single-Radio Communication Architecture for UAV Acting As a Mobile Node to Collect Data in WSNs.

Science.gov (United States)

Sayyed, Ali; de Araújo, Gustavo Medeiros; Bodanese, João Paulo; Becker, Leandro Buss

2015-09-16

The use of mobile nodes to collect data in a Wireless Sensor Network (WSN) has gained special attention over the last years. Some researchers explore the use of Unmanned Aerial Vehicles (UAVs) as mobile node for such data-collection purposes. Analyzing these works, it is apparent that mobile nodes used in such scenarios are typically equipped with at least two different radio interfaces. The present work presents a Dual-Stack Single-Radio Communication Architecture (DSSRCA), which allows a UAV to communicate in a bidirectional manner with a WSN and a Sink node. The proposed architecture was specifically designed to support different network QoS requirements, such as best-effort and more reliable communications, attending both UAV-to-WSN and UAV-to-Sink communications needs. DSSRCA was implemented and tested on a real UAV, as detailed in this paper. This paper also includes a simulation analysis that addresses bandwidth consumption in an environmental monitoring application scenario. It includes an analysis of the data gathering rate that can be achieved considering different UAV flight speeds. Obtained results show the viability of using a single radio transmitter for collecting data from the WSN and forwarding such data to the Sink node.

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

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

Science.gov (United States)

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

2018-05-01

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

Supervisory Fault Tolerant Control of the GTM UAV Using LPV Methods

Directory of Open Access Journals (Sweden)

Péni Tamás

2015-03-01

Full Text Available A multi-level reconfiguration framework is proposed for fault tolerant control of over-actuated aerial vehicles, where the levels indicate how much authority is given to the reconfiguration task. On the lowest, first level the fault is accommodated by modifying only the actuator/sensor configuration, so the fault remains hidden from the baseline controller. A dynamic reallocation scheme is applied on this level. The allocation mechanism exploits the actuator/sensor redundancy available on the aircraft. When the fault cannot be managed at the actuator/sensor level, the reconfiguration process has access to the baseline controller. Based on the LPV control framework, this is done by introducing fault-specific scheduling parameters. The baseline controller is designed to provide an acceptable performance level along all fault scenarios coded in these scheduling variables. The decision on which reconfiguration level has to be initiated in response to a fault is determined by a supervisor unit. The method is demonstrated on a full six-degrees-of-freedom nonlinear simulation model of the GTM UAV.

Simulation to Flight Test for a UAV Controls Testbed

Science.gov (United States)

Motter, Mark A.; Logan, Michael J.; French, Michael L.; Guerreiro, Nelson M.

2006-01-01

The NASA Flying Controls Testbed (FLiC) is a relatively small and inexpensive unmanned aerial vehicle developed specifically to test highly experimental flight control approaches. The most recent version of the FLiC is configured with 16 independent aileron segments, supports the implementation of C-coded experimental controllers, and is capable of fully autonomous flight from takeoff roll to landing, including flight test maneuvers. The test vehicle is basically a modified Army target drone, AN/FQM-117B, developed as part of a collaboration between the Aviation Applied Technology Directorate (AATD) at Fort Eustis, Virginia and NASA Langley Research Center. Several vehicles have been constructed and collectively have flown over 600 successful test flights, including a fully autonomous demonstration at the Association of Unmanned Vehicle Systems International (AUVSI) UAV Demo 2005. Simulations based on wind tunnel data are being used to further develop advanced controllers for implementation and flight test.

Pilot Dependence on Imperfect Diagnostic Automation in Simulated UAV Flights: An Attentional Visual Scanning Analysis

National Research Council Canada - National Science Library

Wickens, Christopher; Dixon, Stephen; Goh, Juliana; Hammer, Ben

2005-01-01

An unmanned air vehicle (UAV) simulation was designed to reveal the effects of imperfectly reliable diagnostic automation a monitor of system health parameters on pilot attention, as the latter was assessed via visual scanning...

Simulation and characterization of silicon nanopillar-based nanoparticle sensors

Science.gov (United States)

Wasisto, Hutomo Suryo; Merzsch, Stephan; Huang, Kai; Stranz, Andrej; Waag, Andreas; Peiner, Erwin

2013-05-01

Nanopillar-based structures hold promise as highly sensitive resonant mass sensors for a new generation of aerosol nanoparticle (NP) detecting devices because of their very small masses. In this work, the possible use of a silicon nanopillar (SiNPL) array as a nanoparticle sensor is investigated. The sensor structures are created and simulated using a finite element modeling (FEM) tool of COMSOL Multiphysics 4.3 to study the resonant characteristics and the sensitivity of the SiNPL for femtogram NP mass detection. Instead of using 2D plate models or simple single 3D cylindrical pillar models, FEM is performed with SiNPLs in 3D structures based on the real geometry of experimental SiNPL arrays employing a piezoelectric stack for resonant excitation. In order to achieve an optimal structure and investigate the etching effect on the fabricated resonators, SiNPLs with different designs of meshes, sidewall profiles, lengths, and diameters are simulated and analyzed. To validate the FEM results, fabricated SiNPLs with a high aspect ratio of ~60 are employed and characterized in resonant frequency measurements. SiNPLs are mounted onto a piezoactuator inside a scanning electron microscope (SEM) chamber which can excite SiNPLs into lateral vibration. The measured resonant frequencies of the SiNPLs with diameters about 650 nm and heights about 40 μm range from 434.63 kHz to 458.21 kHz, which agree well with those simulated by FEM. Furthermore, the deflection of a SiNPL can be enhanced by increasing the applied piezoactuator voltage. By depositing different NPs (i.e., carbon, TiO2, SiO2, Ag, and Au NPs) on the SiNPLs, the decrease of the resonant frequency is clearly shown confirming their potential to be used as airborne NP mass sensor with femtogram resolution level.

Optimal trajectory planning for a UAV glider using atmospheric thermals

Science.gov (United States)

Kagabo, Wilson B.

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

LIGHT-WEIGHT SENSOR PACKAGE FOR PRECISION 3D MEASUREMENT WITH MICRO UAVS E.G. POWER-LINE MONITORING

Directory of Open Access Journals (Sweden)

K.-D. Kuhnert

2013-08-01

Full Text Available The paper describes a new sensor package for micro or mini UAVs and one application that has been successfully implemented with this sensor package. It is intended for 3D measurement of landscape or large outdoor structures for mapping or monitoring purposes. The package can be composed modularly into several configurations. It may contain a laser-scanner, camera, IMU, GPS and other sensors as required by the application. Also different products of the same sensor type have been integrated. Always it contains its own computing infrastructure and may be used for intelligent navigation, too. It can be operated in cooperation with different drones but also completely independent of the type of drone it is attached to. To show the usability of the system, an application in monitoring high-voltage power lines that has been successfully realised with the package is described in detail.

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.

The use of UAVs for monitoring land degradation

Science.gov (United States)

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.

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.

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

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

Science.gov (United States)

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.

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.

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.

Planar location of the simulative acoustic source based on fiber optic sensor array

Science.gov (United States)

Liang, Yi-Jun; Liu, Jun-feng; Zhang, Qiao-ping; Mu, Lin-lin

2010-06-01

A fiber optic sensor array which is structured by four Sagnac fiber optic sensors is proposed to detect and locate a simulative source of acoustic emission (AE). The sensing loops of Sagnac interferometer (SI) are regarded as point sensors as their small size. Based on the derived output light intensity expression of SI, the optimum work condition of the Sagnac fiber optic sensor is discussed through the simulation of MATLAB. Four sensors are respectively placed on a steel plate to structure the sensor array and the location algorithms are expatiated. When an impact is generated by an artificial AE source at any position of the plate, the AE signal will be detected by four sensors at different times. With the help of a single chip microcomputer (SCM) which can calculate the position of the AE source and display it on LED, we have implemented an intelligent detection and location.

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...

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.

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

Directory of Open Access Journals (Sweden)

S. Briechle

2018-05-01

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

Dual-Stack Single-Radio Communication Architecture for UAV Acting As a Mobile Node to Collect Data in WSNs

Directory of Open Access Journals (Sweden)

Ali Sayyed

2015-09-01

Full Text Available The use of mobile nodes to collect data in a Wireless Sensor Network (WSN has gained special attention over the last years. Some researchers explore the use of Unmanned Aerial Vehicles (UAVs as mobile node for such data-collection purposes. Analyzing these works, it is apparent that mobile nodes used in such scenarios are typically equipped with at least two different radio interfaces. The present work presents a Dual-Stack Single-Radio Communication Architecture (DSSRCA, which allows a UAV to communicate in a bidirectional manner with a WSN and a Sink node. The proposed architecture was specifically designed to support different network QoS requirements, such as best-effort and more reliable communications, attending both UAV-to-WSN and UAV-to-Sink communications needs. DSSRCA was implemented and tested on a real UAV, as detailed in this paper. This paper also includes a simulation analysis that addresses bandwidth consumption in an environmental monitoring application scenario. It includes an analysis of the data gathering rate that can be achieved considering different UAV flight speeds. Obtained results show the viability of using a single radio transmitter for collecting data from the WSN and forwarding such data to the Sink node.

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.

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...

UAV VISUAL AUTOLOCALIZATON BASED ON AUTOMATIC LANDMARK RECOGNITION

Directory of Open Access Journals (Sweden)

P. Silva Filho

2017-08-01

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

Laser-based sensors on UAVs for quantifying local emissions of greenhouse gases

Science.gov (United States)

Zondlo, Mark; Tao, Lei; O'Brien, Anthony; Ross, Kevin; Khan, Amir; Pan, Da; Golston, Levi; Sun, Kang; DiGangi, Josh

2015-04-01

Small unmanned aerial systems (UAS) provide an ideal platform to sample both locally near an emission source as well as within the atmospheric boundary layer. However, small UAS (those with wingspans or rotors on the order of a meter) place severe constraints on sensor size (~ liter volume), mass (~ kg), and power (10s W). Laser-based sensors employing absorption techniques are ideally suited for such platforms due to their high sensitivity, high selectivity, and compact footprint. We have developed and flown compact sensors for water vapor, carbon dioxide and methane using new advances in open-path, laser-based spectroscopy on a variety of platforms ranging from remote control helicopters to long-duration UAS. Open-path spectroscopy allows for high frequency sampling (10-25 Hz) while avoiding the size/mass/power of sample delays, inlet lines, and pumps. To address the challenges of in-flight stability in changing environmental conditions and any associated flight artifacts on the measurement itself (e.g. vibrations), we use an in-line reference cell at a reduced pressure (10 hPa) to account for systematic drift continuously while in flight. Wavelength modulation spectroscopy is used at different harmonics to isolate the narrow linewidth of the in-line reference signal from the ambient, pressure-broadened absorption lineshape of the trace gas of interest. As a result, a metric of in-flight performance is achieved in real-time on the same optical pathlength as the ambient signal. To demonstrate the great potential of laser-based sensors on UAS, we deployed a 1.65 micron-based methane sensor (4 kg, 50 W, 100 ppbv precision at 10 Hz) on a UT-Dallas remote control aircraft for two weeks around gas/oil extraction activities as part of the EDF Barnett Coordinated Campaign in October 2013. We conducted thirty-four flights around a compressor station to examine the spatial and temporal characteristics of its emissions. Leaks of methane were typically lofted to altitudes

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.

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.

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.

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

Science.gov (United States)

Rashid., Z. A.; Dardin, A. S. F. Syed.; Azid, A. A.; Ahmad, K. A.

2018-02-01

The development of an autonomous Unmanned Aerial Vehicle (UAV) requires a fundamentals studies of the UAV's flight characteristic. The aim of this study is to identify and model the flight characteristic of a conventional fixed-wing type UAV. Subsequence to this, the mode of flight of the UAV can be investigated. One technique to identify the characteristic of a UAV is a flight test where it required specific maneuvering to be executed while measuring the attitude sensor. In this study, a simple shock flyer type UAV was used as the aircraft. The result shows that the modeled flight characteristic has a significant relation with actual values but the fitting value is rather small. It is suggested that the future study is conducted with an improvement of the physical UAV, data filtering and better system identification methods.

SIMULATION OF INERTIAL NAVIGATION SYSTEM ERRORS AT AERIAL PHOTOGRAPHY FROM UAV

Directory of Open Access Journals (Sweden)

R. Shults

2017-05-01

Full Text Available The problem of accuracy determination of the UAV position using INS at aerial photography can be resolved in two different ways: modelling of measurement errors or in-field calibration for INS. The paper presents the results of INS errors research by mathematical modelling. In paper were considered the following steps: developing of INS computer model; carrying out INS simulation; using reference data without errors, estimation of errors and their influence on maps creation accuracy by UAV data. It must be remembered that the values of orientation angles and the coordinates of the projection centre may change abruptly due to the influence of the atmosphere (different air density, wind, etc.. Therefore, the mathematical model of the INS was constructed taking into account the use of different models of wind gusts. For simulation were used typical characteristics of micro electromechanical (MEMS INS and parameters of standard atmosphere. According to the simulation established domination of INS systematic errors that accumulate during the execution of photographing and require compensation mechanism, especially for orientation angles. MEMS INS have a high level of noise at the system input. Thanks to the developed model, we are able to investigate separately the impact of noise in the absence of systematic errors. According to the research was found that on the interval of observations in 5 seconds the impact of random and systematic component is almost the same. The developed model of INS errors studies was implemented in Matlab software environment and without problems can be improved and enhanced with new blocks.

Multimodel Predictive Control Approach for UAV Formation Flight

Directory of Open Access Journals (Sweden)

Chang-jian Ru

2014-01-01

Full Text Available Formation flight problem is the most important and interesting problem of multiple UAVs (unmanned aerial vehicles cooperative control. In this paper, a novel approach for UAV formation flight based on multimodel predictive control is designed. Firstly, the state equation of relative motion is obtained and then discretized. By the geometrical method, the characteristic points of state are determined. Afterwards, based on the linearization technique, the standard linear discrete model is obtained at each characteristic state point. Then, weighted model set is proposed using the idea of T-S (Takagi-Sugeno fuzzy control and the predictive control is carried out based on the multimodel method. Finally, to verify the performance of the proposed method, two different simulation scenarios are performed.

UAVs Use for the Support of Emergency Response Teams Specific Missions

Directory of Open Access Journals (Sweden)

Sorin-Gabriel CONSTANTINESCU

2013-03-01

Full Text Available This article presents various methods of implementation for a new technology concerning the assessment and coordination of emergency situations, which is based upon the usage of Unmanned Aerial Vehicles (UAVs. The UAV platform is equipped with optical electronic sensors and other types of sensors, being an aerial surveillance device as efficient as any other classically piloted platform. While currently being in service as military operations support for various operation theaters, they can also be used for assisting emergency response teams, providing full national coverage. For these special response teams, the ability to carry out overview, surveillance or information gathering activities and locating fixed or mobile targets are key components for the successful accomplishment of their missions, which have the purpose of saving lives and properties and of limiting the damage done to the surrounding environment. More concretely, the presented scenarios are: response in emergency situations, extinguishing of large-scale fires, testing of chemically, biologically or radioactively polluted areas and assessment of natural disasters.

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.

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...

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.

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...

System Considerations and Challendes in 3d Mapping and Modeling Using Low-Cost Uav Systems

Science.gov (United States)

Lari, Z.; El-Sheimy, N.

2015-08-01

In the last few years, low-cost UAV systems have been acknowledged as an affordable technology for geospatial data acquisition that can meet the needs of a variety of traditional and non-traditional mapping applications. In spite of its proven potential, UAV-based mapping is still lacking in terms of what is needed for it to become an acceptable mapping tool. In other words, a well-designed system architecture that considers payload restrictions as well as the specifications of the utilized direct geo-referencing component and the imaging systems in light of the required mapping accuracy and intended application is still required. Moreover, efficient data processing workflows, which are capable of delivering the mapping products with the specified quality while considering the synergistic characteristics of the sensors onboard, the wide range of potential users who might lack deep knowledge in mapping activities, and time constraints of emerging applications, are still needed to be adopted. Therefore, the introduced challenges by having low-cost imaging and georeferencing sensors onboard UAVs with limited payload capability, the necessity of efficient data processing techniques for delivering required products for intended applications, and the diversity of potential users with insufficient mapping-related expertise needs to be fully investigated and addressed by UAV-based mapping research efforts. This paper addresses these challenges and reviews system considerations, adaptive processing techniques, and quality assurance/quality control procedures for achievement of accurate mapping products from these systems.

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

Directory of Open Access Journals (Sweden)

Micaela Troglia Gamba

2015-11-01

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

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.

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.

REAL-TIME MONITORING SYSTEM USING UNMANNED AERIAL VEHICLE INTEGRATED WITH SENSOR OBSERVATION SERVICE

Directory of Open Access Journals (Sweden)

A. Witayangkurn

2012-09-01

Full Text Available The Unmanned Aerial Vehicle (UAV is an emerging technology being adapted for a wide range of applications. Real-time monitoring is essential to enhance the effectiveness of UAV applications. Sensor networks are networks constructed from various sensor nodes. International standard such as OGC's SOS (Sensor Observation Service makes it possible to share sensor data with other systems as well as to provide accessibility to globally distributed users. In this paper, we propose a system combining UAV technology and sensor network technology to use an UAV as a mobile node of sensor network so that the sensor data from UAV is published and shared real-time. A UAV can extend the observation range of a sensor network to remote areas where it is usually difficult to access such as disaster area. We constructed a UAV system using remote-controlled helicopter and various sensors such as GPS, gyrocompass, laser range finder, Digital camera and Thermometer. Furthermore, we extended the Sensor Observation Service (SOS and Sensor Service Grid (SSG to support mobile sensor nodes. Then, we conducted experiments of flying the helicopter over an area of the interest. During the flight, the system measured environmental data using its sensors and captured images of the ground. The data was sent to a SOS node as the ground station via Wi-Fi which was published using SSG to give real- time access to globally distributed users.

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

Directory of Open Access Journals (Sweden)

Luo Delin

2014-08-01

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

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.

Low Power Greenhouse Gas Sensors for Unmanned Aerial Vehicles

Directory of Open Access Journals (Sweden)

David J. Lary

2012-05-01

Full Text Available We demonstrate compact, low power, lightweight laser-based sensors for measuring trace gas species in the atmosphere designed specifically for electronic unmanned aerial vehicle (UAV platforms. The sensors utilize non-intrusive optical sensing techniques to measure atmospheric greenhouse gas concentrations with unprecedented vertical and horizontal resolution (~1 m within the planetary boundary layer. The sensors are developed to measure greenhouse gas species including carbon dioxide, water vapor and methane in the atmosphere. Key innovations are the coupling of very low power vertical cavity surface emitting lasers (VCSELs to low power drive electronics and sensitive multi-harmonic wavelength modulation spectroscopic techniques. The overall mass of each sensor is between 1–2 kg including batteries and each one consumes less than 2 W of electrical power. In the initial field testing, the sensors flew successfully onboard a T-Rex Align 700E robotic helicopter and showed a precision of 1% or less for all three trace gas species. The sensors are battery operated and capable of fully automated operation for long periods of time in diverse sensing environments. Laser-based trace gas sensors for UAVs allow for high spatial mapping of local greenhouse gas concentrations in the atmospheric boundary layer where land/atmosphere fluxes occur. The high-precision sensors, coupled to the ease-of-deployment and cost effectiveness of UAVs, provide unprecedented measurement capabilities that are not possible with existing satellite-based and suborbital aircraft platforms.

Research on the attitude of small UAV based on MEMS devices

Science.gov (United States)

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

2017-05-01

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

Aerial Mapping of Forests Affected by Pathogens Using UAVs, Hyperspectral Sensors, and Artificial Intelligence.

Science.gov (United States)

Sandino, Juan; Pegg, Geoff; Gonzalez, Felipe; Smith, Grant

2018-03-22

The environmental and economic impacts of exotic fungal species on natural and plantation forests have been historically catastrophic. Recorded surveillance and control actions are challenging because they are costly, time-consuming, and hazardous in remote areas. Prolonged periods of testing and observation of site-based tests have limitations in verifying the rapid proliferation of exotic pathogens and deterioration rates in hosts. Recent remote sensing approaches have offered fast, broad-scale, and affordable surveys as well as additional indicators that can complement on-ground tests. This paper proposes a framework that consolidates site-based insights and remote sensing capabilities to detect and segment deteriorations by fungal pathogens in natural and plantation forests. This approach is illustrated with an experimentation case of myrtle rust ( Austropuccinia psidii ) on paperbark tea trees ( Melaleuca quinquenervia ) in New South Wales (NSW), Australia. The method integrates unmanned aerial vehicles (UAVs), hyperspectral image sensors, and data processing algorithms using machine learning. Imagery is acquired using a Headwall Nano-Hyperspec ® camera, orthorectified in Headwall SpectralView ® , and processed in Python programming language using eXtreme Gradient Boosting (XGBoost), Geospatial Data Abstraction Library (GDAL), and Scikit-learn third-party libraries. In total, 11,385 samples were extracted and labelled into five classes: two classes for deterioration status and three classes for background objects. Insights reveal individual detection rates of 95% for healthy trees, 97% for deteriorated trees, and a global multiclass detection rate of 97%. The methodology is versatile to be applied to additional datasets taken with different image sensors, and the processing of large datasets with freeware tools.

Distortion correction algorithm for UAV remote sensing image based on CUDA

International Nuclear Information System (INIS)

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

2014-01-01

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

CO-REGISTRATION OF DSMs GENERATED BY UAV AND TERRESTRIAL LASER SCANNING SYSTEMS

Directory of Open Access Journals (Sweden)

R. A. Persad

2016-06-01

Full Text Available An approach for the co-registration of Digital Surface Models (DSMs derived from Unmanned Aerial Vehicles (UAVs and Terrestrial Laser Scanners (TLS is proposed. Specifically, a wavelet-based feature descriptor for matching surface keypoints on the 2.5D DSMs is developed. DSMs are useful in wide-scope of various applications such as 3D building modelling and reconstruction, cultural heritage, urban and environmental planning, aircraft navigation/path routing, accident and crime scene reconstruction, mining as well as, topographic map revision and change detection. For these listed applications, it is not uncommon that there will be a need for automatically aligning multi-temporal DSMs which may have been acquired from multiple sensors, with different specifications over a period of time, and may have various overlaps. Terrestrial laser scanners usually capture urban facades in an accurate manner; however this is not the case for building roof structures. On the other hand, vertical photography from UAVs can capture the roofs. Therefore, the automatic fusion of UAV and laser-scanning based DSMs is addressed here as it serves various geospatial applications.

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...

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.

Big data; sensor networks and remotely-sensed data for mapping; feature extraction from lidar

Science.gov (United States)

Tlhabano, Lorato

2018-05-01

Unmanned aerial vehicles (UAVs) can be used for mapping in the close range domain, combining aerial and terrestrial photogrammetry and now the emergence of affordable platforms to carry these technologies has opened up new opportunities for mapping and modeling cadastral boundaries. At the current state mainly low cost UAVs fitted with sensors are used in mapping projects with low budgets, the amount of data produced by the UAVs can be enormous hence the need for big data techniques' and concepts. The past couple of years have witnessed the dramatic rise of low-cost UAVs fitted with high tech Lidar sensors and as such the UAVS have now reached a level of practical reliability and professionalism which allow the use of these systems as mapping platforms. UAV based mapping provides not only the required accuracy with respect to cadastral laws and policies as well as requirements for feature extraction from the data sets and maps produced, UAVs are also competitive to other measurement technologies in terms of economic aspects. In the following an overview on how the various technologies of UAVs, big data concepts and lidar sensor technologies can work together to revolutionize cadastral mapping particularly in Africa and as a test case Botswana in particular will be used to investigate these technologies. These technologies can be combined to efficiently provide cadastral mapping in difficult to reach areas and over large areas of land similar to the Land Administration Procedures, Capacity and Systems (LAPCAS) exercise which was recently undertaken by the Botswana government, we will show how the uses of UAVS fitted with lidar sensor and utilizing big data concepts could have reduced not only costs and time for our government but also how UAVS could have provided more detailed cadastral maps.

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

Science.gov (United States)

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

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...

Increasing the UAV data value by an OBIA methodology

Science.gov (United States)

García-Pedrero, Angel; Lillo-Saavedra, Mario; Rodriguez-Esparragon, Dionisio; Rodriguez-Gonzalez, Alejandro; Gonzalo-Martin, Consuelo

2017-10-01

Recently, there has been a noteworthy increment of using images registered by unmanned aerial vehicles (UAV) in different remote sensing applications. Sensors boarded on UAVs has lower operational costs and complexity than other remote sensing platforms, quicker turnaround times as well as higher spatial resolution. Concerning this last aspect, particular attention has to be paid on the limitations of classical algorithms based on pixels when they are applied to high resolution images. The objective of this study is to investigate the capability of an OBIA methodology developed for the automatic generation of a digital terrain model of an agricultural area from Digital Elevation Model (DEM) and multispectral images registered by a Parrot Sequoia multispectral sensor board on a eBee SQ agricultural drone. The proposed methodology uses a superpixel approach for obtaining context and elevation information used for merging superpixels and at the same time eliminating objects such as trees in order to generate a Digital Terrain Model (DTM) of the analyzed area. Obtained results show the potential of the approach, in terms of accuracy, when it is compared with a DTM generated by manually eliminating objects.

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.

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.

Geometric processing workflow for vertical and oblique hyperspectral frame images collected using UAV

Science.gov (United States)

Markelin, L.; Honkavaara, E.; Näsi, R.; Nurminen, K.; Hakala, T.

2014-08-01

Remote sensing based on unmanned airborne vehicles (UAVs) is a rapidly developing field of technology. UAVs enable accurate, flexible, low-cost and multiangular measurements of 3D geometric, radiometric, and temporal properties of land and vegetation using various sensors. In this paper we present a geometric processing chain for multiangular measurement system that is designed for measuring object directional reflectance characteristics in a wavelength range of 400-900 nm. The technique is based on a novel, lightweight spectral camera designed for UAV use. The multiangular measurement is conducted by collecting vertical and oblique area-format spectral images. End products of the geometric processing are image exterior orientations, 3D point clouds and digital surface models (DSM). This data is needed for the radiometric processing chain that produces reflectance image mosaics and multiangular bidirectional reflectance factor (BRF) observations. The geometric processing workflow consists of the following three steps: (1) determining approximate image orientations using Visual Structure from Motion (VisualSFM) software, (2) calculating improved orientations and sensor calibration using a method based on self-calibrating bundle block adjustment (standard photogrammetric software) (this step is optional), and finally (3) creating dense 3D point clouds and DSMs using Photogrammetric Surface Reconstruction from Imagery (SURE) software that is based on semi-global-matching algorithm and it is capable of providing a point density corresponding to the pixel size of the image. We have tested the geometric processing workflow over various targets, including test fields, agricultural fields, lakes and complex 3D structures like forests.

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.

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

Science.gov (United States)

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

2014-06-01

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

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.

Positional quality assessment of orthophotos obtained from sensors onboard multi-rotor UAV platforms.

Science.gov (United States)

Mesas-Carrascosa, Francisco Javier; Rumbao, Inmaculada Clavero; Berrocal, Juan Alberto Barrera; Porras, Alfonso García-Ferrer

2014-11-26

In this study we explored the positional quality of orthophotos obtained by an unmanned aerial vehicle (UAV). A multi-rotor UAV was used to obtain images using a vertically mounted digital camera. The flight was processed taking into account the photogrammetry workflow: perform the aerial triangulation, generate a digital surface model, orthorectify individual images and finally obtain a mosaic image or final orthophoto. The UAV orthophotos were assessed with various spatial quality tests used by national mapping agencies (NMAs). Results showed that the orthophotos satisfactorily passed the spatial quality tests and are therefore a useful tool for NMAs in their production flowchart.

Detection of Nuclear Sources by UAV Teleoperation Using a Visuo-Haptic Augmented Reality Interface.

Science.gov (United States)

Aleotti, Jacopo; Micconi, Giorgio; Caselli, Stefano; Benassi, Giacomo; Zambelli, Nicola; Bettelli, Manuele; Zappettini, Andrea

2017-09-29

A visuo-haptic augmented reality (VHAR) interface is presented enabling an operator to teleoperate an unmanned aerial vehicle (UAV) equipped with a custom CdZnTe-based spectroscopic gamma-ray detector in outdoor environments. The task is to localize nuclear radiation sources, whose location is unknown to the user, without the close exposure of the operator. The developed detector also enables identification of the localized nuclear sources. The aim of the VHAR interface is to increase the situation awareness of the operator. The user teleoperates the UAV using a 3DOF haptic device that provides an attractive force feedback around the location of the most intense detected radiation source. Moreover, a fixed camera on the ground observes the environment where the UAV is flying. A 3D augmented reality scene is displayed on a computer screen accessible to the operator. Multiple types of graphical overlays are shown, including sensor data acquired by the nuclear radiation detector, a virtual cursor that tracks the UAV and geographical information, such as buildings. Experiments performed in a real environment are reported using an intense nuclear source.

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

Modeling and Flocking Consensus Analysis for Large-Scale UAV Swarms

Directory of Open Access Journals (Sweden)

Li Bing

2013-01-01

Full Text Available Recently, distributed coordination control of the unmanned aerial vehicle (UAV swarms has been a particularly active topic in intelligent system field. In this paper, through understanding the emergent mechanism of the complex system, further research on the flocking and the dynamic characteristic of UAV swarms will be given. Firstly, this paper analyzes the current researches and existent problems of UAV swarms. Afterwards, by the theory of stochastic process and supplemented variables, a differential-integral model is established, converting the system model into Volterra integral equation. The existence and uniqueness of the solution of the system are discussed. Then the flocking control law is given based on artificial potential with system consensus. At last, we analyze the stability of the proposed flocking control algorithm based on the Lyapunov approach and prove that the system in a limited time can converge to the consensus direction of the velocity. Simulation results are provided to verify the conclusion.

Mini-UAV based sensory system for measuring environmental variables in greenhouses.

Science.gov (United States)

Roldán, Juan Jesús; Joossen, Guillaume; Sanz, David; del Cerro, Jaime; Barrientos, Antonio

2015-02-02

This paper describes the design, construction and validation of a mobile sensory platform for greenhouse monitoring. The complete system consists of a sensory system on board a small quadrotor (i.e., a four rotor mini-UAV). The goals of this system include taking measures of temperature, humidity, luminosity and CO2 concentration and plotting maps of these variables. These features could potentially allow for climate control, crop monitoring or failure detection (e.g., a break in a plastic cover). The sensors have been selected by considering the climate and plant growth models and the requirements for their integration onboard the quadrotor. The sensors layout and placement have been determined through a study of quadrotor aerodynamics and the influence of the airflows from its rotors. All components of the system have been developed, integrated and tested through a set of field experiments in a real greenhouse. The primary contributions of this paper are the validation of the quadrotor as a platform for measuring environmental variables and the determination of the optimal location of sensors on a quadrotor.

Mini-UAV Based Sensory System for Measuring Environmental Variables in Greenhouses

Directory of Open Access Journals (Sweden)

Juan Jesús Roldán

2015-02-01

Full Text Available This paper describes the design, construction and validation of a mobile sensory platform for greenhouse monitoring. The complete system consists of a sensory system on board a small quadrotor (i.e., a four rotor mini-UAV. The goals of this system include taking measures of temperature, humidity, luminosity and CO2 concentration and plotting maps of these variables. These features could potentially allow for climate control, crop monitoring or failure detection (e.g., a break in a plastic cover. The sensors have been selected by considering the climate and plant growth models and the requirements for their integration onboard the quadrotor. The sensors layout and placement have been determined through a study of quadrotor aerodynamics and the influence of the airflows from its rotors. All components of the system have been developed, integrated and tested through a set of field experiments in a real greenhouse. The primary contributions of this paper are the validation of the quadrotor as a platform for measuring environmental variables and the determination of the optimal location of sensors on a quadrotor.

Derivation of High Spatial Resolution Albedo from UAV Digital Imagery: Application over the Greenland Ice Sheet

Directory of Open Access Journals (Sweden)

Jonathan C. Ryan

2017-05-01

Full Text Available Measurements of albedo are a prerequisite for modeling surface melt across the Earth's cryosphere, yet available satellite products are limited in spatial and/or temporal resolution. Here, we present a practical methodology to obtain centimeter resolution albedo products with accuracies of ±5% using consumer-grade digital camera and unmanned aerial vehicle (UAV technologies. Our method comprises a workflow for processing, correcting and calibrating raw digital images using a white reference target, and upward and downward shortwave radiation measurements from broadband silicon pyranometers. We demonstrate the method with a set of UAV sorties over the western, K-sector of the Greenland Ice Sheet. The resulting albedo product, UAV10A1, covers 280 km2, at a resolution of 20 cm per pixel and has a root-mean-square difference of 3.7% compared to MOD10A1 and 4.9% compared to ground-based broadband pyranometer measurements. By continuously measuring downward solar irradiance, the technique overcomes previous limitations due to variable illumination conditions during and between surveys over glaciated terrain. The current miniaturization of multispectral sensors and incorporation of upward facing radiation sensors on UAV packages means that this technique could become increasingly common in field studies and used for a wide range of applications. These include the mapping of debris, dust, cryoconite and bioalbedo, and directly constraining surface energy balance models.

Derivation of high spatial resolution albedo from UAV digital imagery: application over the Greenland Ice Sheet

Science.gov (United States)

Ryan, Jonathan C.; Hubbard, Alun; Box, Jason E.; Brough, Stephen; Cameron, Karen; Cook, Joseph M.; Cooper, Matthew; Doyle, Samuel H.; Edwards, Arwyn; Holt, Tom; Irvine-Fynn, Tristram; Jones, Christine; Pitcher, Lincoln H.; Rennermalm, Asa K.; Smith, Laurence C.; Stibal, Marek; Snooke, Neal

2017-05-01

Measurements of albedo are a prerequisite for modelling surface melt across the Earth's cryosphere, yet available satellite products are limited in spatial and/or temporal resolution. Here, we present a practical methodology to obtain centimetre resolution albedo products with accuracies of 5% using consumer-grade digital camera and unmanned aerial vehicle (UAV) technologies. Our method comprises a workflow for processing, correcting and calibrating raw digital images using a white reference target, and upward and downward shortwave radiation measurements from broadband silicon pyranometers. We demonstrate the method with a set of UAV sorties over the western, K-sector of the Greenland Ice Sheet. The resulting albedo product, UAV10A1, covers 280 km2, at a resolution of 20 cm per pixel and has a root-mean-square difference of 3.7% compared to MOD10A1 and 4.9% compared to ground-based broadband pyranometer measurements. By continuously measuring downward solar irradiance, the technique overcomes previous limitations due to variable illumination conditions during and between surveys over glaciated terrain. The current miniaturization of multispectral sensors and incorporation of upward facing radiation sensors on UAV packages means that this technique will likely become increasingly attractive in field studies and used in a wide range of applications for high temporal and spatial resolution surface mapping of debris, dust, cryoconite and bioalbedo and for directly constraining surface energy balance models.

Development of a compact light weight DELRAD probe and its integration with UAV NETRA for aerial radiation surveillance

International Nuclear Information System (INIS)

Prasad, Mahaveer; Yadav, Ashok Kumar; Gupta, D.K.; Bhatnagar, Vivek; Singh, Chiman; Mishrilal

2018-01-01

The DEfence Laboratory RAdiation Detector - 'DELRAD' is an indigenously developed Hybrid Micro Circuit Module employing Si PIN diodes for detection of gamma radiation. Using this as a detector, the 'DELRAD Probe' has been designed and developed specifically for the UAV, NETRA for aerial surveillance of the nuclear affected areas. The critical requirement of very light weight radiation sensor as payload (<50gm) for the UAV NETRA is met by designing this Probe weighing approx. 40gm. The sensor is capable of measuring gamma radiation levels from 1mR/h to 1000R/h. The Probe has been tested, calibrated and integrated with the UAV NETRA. In addition to this, the radiation testing during flight of UAV NETRA integrated with DELRAD probe has also been carried out and results have been recorded. The work carried out proves the capability of Defence Laboratory, Jodhpur, (DRDO) in the area of 'Aerial Surveillance of Nuclear Radiation Affected Area' using Unmanned Aerial Vehicles (UAVs)

Flight safety measurements of UAVs in congested airspace

Directory of Open Access Journals (Sweden)

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.

Reputation-based secure sensor localization in wireless sensor networks.

Science.gov (United States)

He, Jingsha; Xu, Jing; Zhu, Xingye; Zhang, Yuqiang; Zhang, Ting; Fu, Wanqing

2014-01-01

Location information of sensor nodes in wireless sensor networks (WSNs) is very important, for it makes information that is collected and reported by the sensor nodes spatially meaningful for applications. Since most current sensor localization schemes rely on location information that is provided by beacon nodes for the regular sensor nodes to locate themselves, the accuracy of localization depends on the accuracy of location information from the beacon nodes. Therefore, the security and reliability of the beacon nodes become critical in the localization of regular sensor nodes. In this paper, we propose a reputation-based security scheme for sensor localization to improve the security and the accuracy of sensor localization in hostile or untrusted environments. In our proposed scheme, the reputation of each beacon node is evaluated based on a reputation evaluation model so that regular sensor nodes can get credible location information from highly reputable beacon nodes to accomplish localization. We also perform a set of simulation experiments to demonstrate the effectiveness of the proposed reputation-based security scheme. And our simulation results show that the proposed security scheme can enhance the security and, hence, improve the accuracy of sensor localization in hostile or untrusted environments.

An Indoor Localization Strategy for a Mini-UAV in the Presence of Obstacles

Directory of Open Access Journals (Sweden)

Long Cheng

2012-10-01

Full Text Available In this paper, we propose a novel approach to mini-UAV localization in a wireless sensor network. We firstly employ the environment adaptive RSS parameters' estimation method to estimate the parameters of range estimation model. However, the direct path from the target to a beacon is blocked by obstacles in a complicated indoor environment. So the proposed method, which employs a sequential probability ratio test to identify whether the measurement contains non-line of sight (NLOS errors, is tolerant to parameter fluctuations. Finally, a particle swarm optimization-based method is proposed to solve the established objective function. Simulation results show that the proposed method achieved relatively higher localization accuracy. In addition, the performance analyses, carried out for a realistic indoor environment, shows that the proposed method still preserves the same localization accuracy.

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

Science.gov (United States)

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.

Analysis of nanowire transistor based nitrogen dioxide gas sensor – A simulation study

Directory of Open Access Journals (Sweden)

Gaurav Saxena

2015-06-01

Full Text Available Sensors sensitivity, selectivity and stability has always been a prime design concern for gas sensors designers. Modeling and simulation of gas sensors aids the designers in improving their performance. In this paper, different routes for the modeling and simulation of a semiconducting gas sensor is presented. Subsequently, by employing one of the route, the response of Zinc Oxide nanowire transistor towards nitrogen dioxide ambient is simulated. In addition to the sensing mechanism, simulation study of gas species desorption by applying a recovery voltage is also presented.

Development of Hardware-in-the-Loop Simulation Based on Gazebo and Pixhawk for Unmanned Aerial Vehicles

Science.gov (United States)

Nguyen, Khoa Dang; Ha, Cheolkeun

2018-04-01

Hardware-in-the-loop simulation (HILS) is well known as an effective approach in the design of unmanned aerial vehicles (UAV) systems, enabling engineers to test the control algorithm on a hardware board with a UAV model on the software. Performance of HILS is determined by performances of the control algorithm, the developed model, and the signal transfer between the hardware and software. The result of HILS is degraded if any signal could not be transferred to the correct destination. Therefore, this paper aims to develop a middleware software to secure communications in HILS system for testing the operation of a quad-rotor UAV. In our HILS, the Gazebo software is used to generate a nonlinear six-degrees-of-freedom (6DOF) model, sensor model, and 3D visualization for the quad-rotor UAV. Meanwhile, the flight control algorithm is designed and implemented on the Pixhawk hardware. New middleware software, referred to as the control application software (CAS), is proposed to ensure the connection and data transfer between Gazebo and Pixhawk using the multithread structure in Qt Creator. The CAS provides a graphical user interface (GUI), allowing the user to monitor the status of packet transfer, and perform the flight control commands and the real-time tuning parameters for the quad-rotor UAV. Numerical implementations have been performed to prove the effectiveness of the middleware software CAS suggested in this paper.

Design of Power Cable UAV Intelligent Patrol System Based on Adaptive Kalman Filter Fuzzy PID Control

Directory of Open Access Journals (Sweden)

Chen Siyu

2017-01-01

Full Text Available Patrol UAV has poor aerial posture stability and is largely affected by anthropic factors, which lead to some shortages such as low power cable tracking precision, captured image loss and inconvenient temperature measurement, etc. In order to solve these disadvantages, this article puts forward a power cable intelligent patrol system. The core innovation of the system is a 360° platform. This collects the position information of power cables by using far infrared sensors and carries out real-time all-direction adjustment of UAV lifting platform through the adaptive Kalman filter fuzzy PID control algorithm, so that the precise tracking of power cables is achieved. An intelligent patrol system is established to detect the faults more accurately, so that a high intelligence degree of power cable patrol system is realized.

Development of autonomous controller system of high speed UAV from simulation to ready to fly condition

Science.gov (United States)

Yudhi Irwanto, Herma

2018-02-01

The development of autonomous controller system that is specially used in our high speed UAV, it’s call RKX-200EDF/TJ controlled vehicle needs to be continued as a step to mastery and to developt control system of LAPAN’s satellite launching rocket. The weakness of the existing control system in this high speed UAV needs to be repaired and replaced using the autonomous controller system. Conversion steps for ready-to-fly system involved controlling X tail fin, adjusting auto take off procedure by adding X axis sensor, procedure of way points reading and process of measuring distance and heading to the nearest way point, developing user-friendly ground station, and adding tools for safety landing. The development of this autonomous controller system also covered a real flying test in Pandanwangi, Lumajang in November 2016. Unfortunately, the flying test was not successful because the booster rocket was blown right after burning. However, the system could record the event and demonstrated that the controller system had worked according to plan.

Shigaraki UAV-Radar Experiment (ShUREX): overview of the campaign with some preliminary results

Science.gov (United States)

Kantha, Lakshmi; Lawrence, Dale; Luce, Hubert; Hashiguchi, Hiroyuki; Tsuda, Toshitaka; Wilson, Richard; Mixa, Tyler; Yabuki, Masanori

2017-12-01

The Shigaraki unmanned aerial vehicle (UAV)-Radar Experiment (ShUREX) is an international (USA-Japan-France) observational campaign, whose overarching goal is to demonstrate the utility of small, lightweight, inexpensive, autonomous UAVs in probing and monitoring the lower troposphere and to promote synergistic use of UAVs and very high frequency (VHF) radars. The 2-week campaign lasting from June 1 to June 14, 2015, was carried out at the Middle and Upper Atmosphere (MU) Observatory in Shigaraki, Japan. During the campaign, the DataHawk UAV, developed at the University of Colorado, Boulder, and equipped with high-frequency response cold wire and pitot tube sensors (as well as an iMET radiosonde), was flown near and over the VHF-band MU radar. Measurements in the atmospheric column in the immediate vicinity of the radar were obtained. Simultaneous and continuous operation of the radar in range imaging mode enabled fine-scale structures in the atmosphere to be visualized by the radar. It also permitted the UAV to be commanded to sample interesting structures, guided in near real time by the radar images. This overview provides a description of the ShUREX campaign and some interesting but preliminary results of the very first simultaneous and intensive probing of turbulent structures by UAVs and the MU radar. The campaign demonstrated the validity and utility of the radar range imaging technique in obtaining very high vertical resolution ( 20 m) images of echo power in the atmospheric column, which display evolving fine-scale atmospheric structures in unprecedented detail. The campaign also permitted for the very first time the evaluation of the consistency of turbulent kinetic energy dissipation rates in turbulent structures inferred from the spectral broadening of the backscattered radar signal and direct, in situ measurements by the high-frequency response velocity sensor on the UAV. The data also enabled other turbulence parameters such as the temperature

Autonomous Control of a Quadrotor UAV Using Fuzzy Logic

Science.gov (United States)

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 Sensor Based Applications for the Android Platform: an Approach Based on Realistic Simulation

Directory of Open Access Journals (Sweden)

Pablo CAMPILLO-SÁNCHEZ

2013-05-01

Full Text Available Smart phones are equipped with a wide range of sensors (such as GPS, light, accelerometer, gyroscope, etc. and allow users to be connected everywhere. These characteristics offer a rich information source for creating context-aware applications. However, testing these applications in the lab, before their deployment, could become a hard task or impossible because of sensors correlation, too wide testing area or an excessive number of people involved. This work aims to solve these problems carrying out the testing in a simulator, simulating the world in which the application user is immersed into. Tester controls her avatar and the avatar has a simulated smart phone that is connected with the user’s smart phone. Applications under test are installed on the real smart phone and are compiled with a library that replaces standard services of the sensors by others that offer data sensor from the simulator (depending on the simulated smart phone context instead of real world.

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

Multi-UAV joint target recognizing based on binocular vision theory

Directory of Open Access Journals (Sweden)

Yuan Zhang

2017-01-01

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

Simulations of Propane and Butane Gas Sensor Based on Pristine Armchair Graphene Nanoribbon

Science.gov (United States)

Rashid, Haroon; Koel, Ants; Rang, Toomas

2018-05-01

Over the last decade graphene and its derivatives have gained a remarkable place in research field. As silicon technology is approaching to its geometrical limits so there is a need of alternate that can replace it. Graphene has emerged as a potential candidate for future nano-electronics applications due to its exceptional and extraordinary chemical, optical, electrical and mechanical properties. Graphene based sensors have gained significance for a wide range of sensing applications like detection of biomolecules, chemicals and gas molecules. It can be easily used to make electrical contacts and manipulate them according to the requirements as compared to the other nanomaterials. The intention of the work presented in this article is to contribute in this field by simulating a novel and cheap graphene nanoribbon sensor for the household gas leakage detection. QuantumWise Atomistix (ATK) software is used for the simulations of propane and butane gas sensor. Projected device density of the states (PDDOS) and the transmission spectrum of the device in the proximity of gas molecules are calculated and discussed. The change in the electric current through the device in the presence of the gas molecules is used as a gas detection mechanism for the simulated sensor.

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

Directory of Open Access Journals (Sweden)

Ei Ei Nyein

2017-04-01

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

UAV PHOTOGRAMMETRY: BLOCK TRIANGULATION COMPARISONS

Directory of Open Access Journals (Sweden)

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.

Detection of Nuclear Sources by UAV Teleoperation Using a Visuo-Haptic Augmented Reality Interface

Directory of Open Access Journals (Sweden)

Jacopo Aleotti

2017-09-01

Full Text Available A visuo-haptic augmented reality (VHAR interface is presented enabling an operator to teleoperate an unmanned aerial vehicle (UAV equipped with a custom CdZnTe-based spectroscopic gamma-ray detector in outdoor environments. The task is to localize nuclear radiation sources, whose location is unknown to the user, without the close exposure of the operator. The developed detector also enables identification of the localized nuclear sources. The aim of the VHAR interface is to increase the situation awareness of the operator. The user teleoperates the UAV using a 3DOF haptic device that provides an attractive force feedback around the location of the most intense detected radiation source. Moreover, a fixed camera on the ground observes the environment where the UAV is flying. A 3D augmented reality scene is displayed on a computer screen accessible to the operator. Multiple types of graphical overlays are shown, including sensor data acquired by the nuclear radiation detector, a virtual cursor that tracks the UAV and geographical information, such as buildings. Experiments performed in a real environment are reported using an intense nuclear source.

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.

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

Directory of Open Access Journals (Sweden)

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.

Assessing UAVs in Monitoring Crop Evapotranspiration within a Heterogeneous Soil

Science.gov (United States)

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

2017-12-01

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

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

Science.gov (United States)

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

2014-08-01

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

Research on detection method of UAV obstruction based on binocular vision

Science.gov (United States)

Zhu, Xiongwei; Lei, Xusheng; Sui, Zhehao

2018-04-01

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

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.

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

Radar sensing via a Micro-UAV-borne system

Science.gov (United States)

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

2017-04-01

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

Determination of UAV position using high accuracy navigation platform

Directory of Open Access Journals (Sweden)

Ireneusz Kubicki

2016-07-01

Full Text Available The choice of navigation system for mini UAV is very important because of its application and exploitation, particularly when the installed on it a synthetic aperture radar requires highly precise information about an object’s position. The presented exemplary solution of such a system draws attention to the possible problems associated with the use of appropriate technology, sensors, and devices or with a complete navigation system. The position and spatial orientation errors of the measurement platform influence on the obtained SAR imaging. Both, turbulences and maneuvers performed during flight cause the changes in the position of the airborne object resulting in deterioration or lack of images from SAR. Consequently, it is necessary to perform operations for reducing or eliminating the impact of the sensors’ errors on the UAV position accuracy. You need to look for compromise solutions between newer better technologies and in the field of software. Keywords: navigation systems, unmanned aerial vehicles, sensors integration

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%.

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.

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 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

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

Directory of Open Access Journals (Sweden)

Arko Lucieer

2012-05-01

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

Acquisition and Processing Protocols for Uav Images: 3d Modeling of Historical Buildings Using Photogrammetry

Science.gov (United States)

Murtiyoso, A.; Koehl, M.; Grussenmeyer, P.; Freville, T.

2017-08-01

Photogrammetry has seen an increase in the use of UAVs (Unmanned Aerial Vehicles) for both large and smaller scale cartography. The use of UAVs is also advantageous because it may be used for tasks requiring quick response, including in the case of the inspection and monitoring of buildings. The objective of the project is to study the acquisition and processing protocols which exist in the literature and to adapt them for UAV projects. This implies a study on the calibration of the sensors, flight planning, comparison of software solutions, data management, and analysis on the different products of a UAV project. Two historical buildings of the city of Strasbourg were used as case studies: a part of the Rohan Palace façade and the St-Pierre-le-Jeune Catholic church. In addition, a preliminary test was performed on the Josephine Pavilion. Two UAVs were used in this research; namely the Sensefly Albris and the DJI Phantom 3 Professional. The experiments have shown that the calibration parameters tend to be unstable for small sensors. Furthermore, the dense matching of images remains a particular problem to address in a close range photogrammetry project, more so in the presence of noise on the images. Data management in cases where the number of images is high is also very important. The UAV is nevertheless a suitable solution for the surveying and recording of historical buildings because it is able to take images from points of view which are normally inaccessible to classical terrestrial techniques.

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

Directory of Open Access Journals (Sweden)

Byeong Hak Kim

2017-12-01

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

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

Science.gov (United States)

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

2017-01-01

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

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

Science.gov (United States)

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

2017-12-27

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

Analysis of Simulated Output Characteristics of Gas Sensor Based on Graphene Nanoribbon

Directory of Open Access Journals (Sweden)

A. Mahmoudi

2016-01-01

Full Text Available This work presents simulated output characteristics of gas sensor transistors based on graphene nanoribbon (GNRFET. The device studied in this work is a new generation of gas sensing devices, which are easy to use, ultracompact, ultrasensitive, and highly selective. We will explain how the exposure to the gas changes the conductivity of graphene nanoribbon. The equations of the GNRFET gas sensor model include the Poisson equation in the weak nonlocality approximation with proposed sensing parameters. As we have developed this model as a platform for a gas detection sensor, we will analyze the current-voltage characteristics after exposure of the GNRFET nanosensor device to NH3 gas. A sensitivity of nearly 2.7% was indicated in our sensor device after exposure of 1 ppm of NH3. The given results make GNRFET the right candidate for use in gas sensing/measuring appliances. Thus, we will investigate the effect of the channel length on the ON- and OFF-current.

A Novel Approach to Selecting Contractor in Agent-based Multi-sensor Battlefield Reconnaissance Simulation

Directory of Open Access Journals (Sweden)

Xiong Li

2012-11-01

Full Text Available This paper presents a novel approach towards showing how contractor in agent-based simulation for complex warfare system such as multi-sensor battlefield reconnaissance system can be selected in Contract Net Protocol (CNP with high efficiency. We first analyze agent and agent-based simulation framework, CNP and collaborators, and present agents interaction chain used to actualize CNP and establish agents trust network. We then obtain contractor's importance weight and dynamic trust by presenting fuzzy similarity-based algorithm and trust modifying algorithm, thus we propose contractor selecting approach based on maximum dynamic integrative trust. We validate the feasibility and capability of this approach by implementing simulation, analyzing compared results and checking the model.

Colour-based Object Detection and Tracking for Autonomous Quadrotor UAV

International Nuclear Information System (INIS)

Kadouf, Hani Hunud A; Mustafah, Yasir Mohd

2013-01-01

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

A Technology Analysis to Support Acquisition of UAVs for Gulf Coalition Forces Operations

Science.gov (United States)

2017-06-01

stamina .  UAV detection range is a sensor related factor that defines the maximum distance at which the sensor can detect targets.  Time between...columns; then, we divide each entry cell in the matrix by its column sum value (Bodin & Gass 2003). The average value in each row of the normalized

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.

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

Science.gov (United States)

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

2017-08-01

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

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

Directory of Open Access Journals (Sweden)

D. Kim

2017-08-01

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

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.

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.

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

Science.gov (United States)

Rokhmana, Catur Aries; Andaru, Ruli

2017-07-01

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

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%.

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

DEFF Research Database (Denmark)

Midtiby, Henrik Skov

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

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

International Nuclear Information System (INIS)

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

2005-01-01

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

FDTD-based optical simulations methodology for CMOS image sensors pixels architecture and process optimization

Science.gov (United States)

Hirigoyen, Flavien; Crocherie, Axel; Vaillant, Jérôme M.; Cazaux, Yvon

2008-02-01

This paper presents a new FDTD-based optical simulation model dedicated to describe the optical performances of CMOS image sensors taking into account diffraction effects. Following market trend and industrialization constraints, CMOS image sensors must be easily embedded into even smaller packages, which are now equipped with auto-focus and short-term coming zoom system. Due to miniaturization, the ray-tracing models used to evaluate pixels optical performances are not accurate anymore to describe the light propagation inside the sensor, because of diffraction effects. Thus we adopt a more fundamental description to take into account these diffraction effects: we chose to use Maxwell-Boltzmann based modeling to compute the propagation of light, and to use a software with an FDTD-based (Finite Difference Time Domain) engine to solve this propagation. We present in this article the complete methodology of this modeling: on one hand incoherent plane waves are propagated to approximate a product-use diffuse-like source, on the other hand we use periodic conditions to limit the size of the simulated model and both memory and computation time. After having presented the correlation of the model with measurements we will illustrate its use in the case of the optimization of a 1.75μm pixel.

BENCHMARKING THE OPTICAL RESOLVING POWER OF UAV BASED CAMERA SYSTEMS

Directory of Open Access Journals (Sweden)

H. Meißner

2017-08-01

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

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

Compact, self-contained enhanced-vision system (EVS) sensor simulator

Science.gov (United States)

Tiana, Carlo

2007-04-01

We describe the model SIM-100 PC-based simulator, for imaging sensors used, or planned for use, in Enhanced Vision System (EVS) applications. Typically housed in a small-form-factor PC, it can be easily integrated into existing out-the-window visual simulators for fixed-wing or rotorcraft, to add realistic sensor imagery to the simulator cockpit. Multiple bands of infrared (short-wave, midwave, extended-midwave and longwave) as well as active millimeter-wave RADAR systems can all be simulated in real time. Various aspects of physical and electronic image formation and processing in the sensor are accurately (and optionally) simulated, including sensor random and fixed pattern noise, dead pixels, blooming, B-C scope transformation (MMWR). The effects of various obscurants (fog, rain, etc.) on the sensor imagery are faithfully represented and can be selected by an operator remotely and in real-time. The images generated by the system are ideally suited for many applications, ranging from sensor development engineering tradeoffs (Field Of View, resolution, etc.), to pilot familiarization and operational training, and certification support. The realistic appearance of the simulated images goes well beyond that of currently deployed systems, and beyond that required by certification authorities; this level of realism will become necessary as operational experience with EVS systems grows.

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.

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.

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.

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.

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

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...

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

, which are all tightly linked to the UAV flight controller hardware and software. The lack of standardization of flight controller architectures and the use of proprietary closed-source flight controllers on many UAV platforms, however, complicates this work: solutions developed for one flight controller...... may be difficult to port to another without substantial extra development and testing. Using open-source flight controllers mitigates some of these challenges and enables other researchers to validate and build upon existing research. This paper presents a survey of the publicly available open...

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

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

Directory of Open Access Journals (Sweden)

Jesus Garza

2016-01-01

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

Automatic Hotspot and Sun Glint Detection in UAV Multispectral Images.

Science.gov (United States)

Ortega-Terol, Damian; Hernandez-Lopez, David; Ballesteros, Rocio; Gonzalez-Aguilera, Diego

2017-10-15

Last advances in sensors, photogrammetry and computer vision have led to high-automation levels of 3D reconstruction processes for generating dense models and multispectral orthoimages from Unmanned Aerial Vehicle (UAV) images. However, these cartographic products are sometimes blurred and degraded due to sun reflection effects which reduce the image contrast and colour fidelity in photogrammetry and the quality of radiometric values in remote sensing applications. This paper proposes an automatic approach for detecting sun reflections problems (hotspot and sun glint) in multispectral images acquired with an Unmanned Aerial Vehicle (UAV), based on a photogrammetric strategy included in a flight planning and control software developed by the authors. In particular, two main consequences are derived from the approach developed: (i) different areas of the images can be excluded since they contain sun reflection problems; (ii) the cartographic products obtained (e.g., digital terrain model, orthoimages) and the agronomical parameters computed (e.g., normalized vegetation index-NVDI) are improved since radiometric defects in pixels are not considered. Finally, an accuracy assessment was performed in order to analyse the error in the detection process, getting errors around 10 pixels for a ground sample distance (GSD) of 5 cm which is perfectly valid for agricultural applications. This error confirms that the precision in the detection of sun reflections can be guaranteed using this approach and the current low-cost UAV technology.

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.

Vision and Control for UAVs: A Survey of General Methods andof Inexpensive Platforms for Infrastructure Inspection

Directory of Open Access Journals (Sweden)

Koppány Máthé

2015-06-01

Full Text Available Unmanned aerial vehicles (UAVs have gained significant attention in recent years. Low-cost platforms using inexpensive sensor payloads have been shown to provide satisfactory flight and navigation capabilities. In this report, we survey vision and control methods that can be applied to low-cost UAVs, and we list some popular inexpensive platforms and application fields where they are useful. We also highlight the sensor suites used where this information is available. We overview, among others, feature detection and tracking, optical flow and visual servoing, low-level stabilization and high-level planning methods. We then list popular low-cost UAVs, selecting mainly quadrotors. We discuss applications, restricting our focus to the field of infrastructure inspection. Finally, as an example, we formulate two use-cases for railway inspection, a less explored application field, and illustrate the usage of the vision and control techniques reviewed by selecting appropriate ones to tackle these use-cases. To select vision methods, we run a thorough set of experimental evaluations.

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

Science.gov (United States)

2015-05-18

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

Use of UAVs for Remote Measurement of Vegetation Canopy Variables

Science.gov (United States)

Rango, A.; Laliberte, A.; Herrick, J.; Steele, C.; Bestelmeyer, B.; Chopping, M. J.

2006-12-01

Remote sensing with different sensors has proven useful for measuring vegetation canopy variables at scales ranging from landscapes down to individual plants. For use at landscape scales, such as desert grasslands invaded by shrubs, it is possible to use multi-angle imagery from satellite sensors, such as MISR and CHRIS/Proba, with geometric optical models to retrieve fractional woody plant cover. Vegetation community states can be mapped using visible and near infrared ASTER imagery at 15 m resolution. At finer scales, QuickBird satellite imagery with approximately 60 cm resolution and piloted aircraft photography with 25-80 cm resolution can be used to measure shrubs above a critical size. Tests conducted with the QuickBird data in the Jornada basin of southern New Mexico have shown that 87% of all shrubs greater than 2 m2 were detected whereas only about 29% of all shrubs less than 2 m2 were detected, even at these high resolutions. Because there is an observational gap between satellite/aircraft measurements and ground observations, we have experimented with Unmanned Aerial Vehicles (UAVs) producing digital photography with approximately 5 cm resolution. We were able to detect all shrubs greater than 2 m2, and we were able to map small subshrubs indicative of rangeland deterioration, as well as remnant grass patches, for the first time. None of these could be identified on the 60 cm resolution data. Additionally, we were able to measure canopy gaps, shrub patterns, percent bare soil, and vegetation cover over mixed rangeland vegetation. This approach is directly applicable to rangeland health monitoring, and it provides a quantitative way to assess shrub invasion over time and to detect the depletion or recovery of grass patches. Further, if the UAV images have sufficient overlap, it may be possible to exploit the stereo viewing capabilities to develop a digital elevation model from the orthophotos, with a potential for extracting canopy height. We envision two

POTENTIAL OF UAV BASED CONVERGENT PHOTOGRAMMETRY IN MONITORING REGENERATION STANDARDS

Directory of Open Access Journals (Sweden)

U. Vepakomma

2015-08-01

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

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

Science.gov (United States)

Lear, Donald Joseph

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

SUSI 62 A ROBUST AND SAFE PARACHUTE UAV WITH LONG FLIGHT TIME AND GOOD PAYLOAD

Directory of Open Access Journals (Sweden)

H. P. Thamm

2012-09-01

Full Text Available In many research areas in the geo-sciences (erosion, land use, land cover change, etc. or applications (e.g. forest management, mining, land management etc. there is a demand for remote sensing images of a very high spatial and temporal resolution. Due to the high costs of classic aerial photo campaigns, the use of a UAV is a promising option for obtaining the desired remote sensed information at the time it is needed. However, the UAV must be easy to operate, safe, robust and should have a high payload and long flight time. For that purpose, the parachute UAV SUSI 62 was developed. It consists of a steel frame with a powerful 62 cm3 2- stroke engine and a parachute wing. The frame can be easily disassembled for transportation or to replace parts. On the frame there is a gimbal mounted sensor carrier where different sensors, standard SLR cameras and/or multi-spectral and thermal sensors can be mounted. Due to the design of the parachute, the SUSI 62 is very easy to control. Two different parachute sizes are available for different wind speed conditions. The SUSI 62 has a payload of up to 8 kg providing options to use different sensors at the same time or to extend flight duration. The SUSI 62 needs a runway of between 10 m and 50 m, depending on the wind conditions. The maximum flight speed is approximately 50 km/h. It can be operated in a wind speed of up to 6 m/s. The design of the system utilising a parachute UAV makes it comparatively safe as a failure of the electronics or the remote control only results in the UAV coming to the ground at a slow speed. The video signal from the camera, the GPS coordinates and other flight parameters are transmitted to the ground station in real time. An autopilot is available, which guarantees that the area of investigation is covered at the desired resolution and overlap. The robustly designed SUSI 62 has been used successfully in Europe, Africa and Australia for scientific projects and also for

Assessing the Utility of Uav-Borne Hyperspectral Image and Photogrammetry Derived 3d Data for Wetland Species Distribution Quick Mapping

Science.gov (United States)

Li, Q. S.; Wong, F. K. K.; Fung, T.

2017-08-01

Lightweight unmanned aerial vehicle (UAV) loaded with novel sensors offers a low cost and minimum risk solution for data acquisition in complex environment. This study assessed the performance of UAV-based hyperspectral image and digital surface model (DSM) derived from photogrammetric point clouds for 13 species classification in wetland area of Hong Kong. Multiple feature reduction methods and different classifiers were compared. The best result was obtained when transformed components from minimum noise fraction (MNF) and DSM were combined in support vector machine (SVM) classifier. Wavelength regions at chlorophyll absorption green peak, red, red edge and Oxygen absorption at near infrared were identified for better species discrimination. In addition, input of DSM data reduces overestimation of low plant species and misclassification due to the shadow effect and inter-species morphological variation. This study establishes a framework for quick survey and update on wetland environment using UAV system. The findings indicate that the utility of UAV-borne hyperspectral and derived tree height information provides a solid foundation for further researches such as biological invasion monitoring and bio-parameters modelling in wetland.

Optimized UAV Communication Protocol Based on Prior Locations

OpenAIRE

Sboui, Lokman; Rabah, Abdullatif

2015-01-01

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

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.

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.

Power Aware Simulation Framework for Wireless Sensor Networks and Nodes

Directory of Open Access Journals (Sweden)

Daniel Weber

2008-07-01

Full Text Available The constrained resources of sensor nodes limit analytical techniques and cost-time factors limit test beds to study wireless sensor networks (WSNs. Consequently, simulation becomes an essential tool to evaluate such systems.We present the power aware wireless sensors (PAWiS simulation framework that supports design and simulation of wireless sensor networks and nodes. The framework emphasizes power consumption capturing and hence the identification of inefficiencies in various hardware and software modules of the systems. These modules include all layers of the communication system, the targeted class of application itself, the power supply and energy management, the central processing unit (CPU, and the sensor-actuator interface. The modular design makes it possible to simulate heterogeneous systems. PAWiS is an OMNeT++ based discrete event simulator written in C++. It captures the node internals (modules as well as the node surroundings (network, environment and provides specific features critical to WSNs like capturing power consumption at various levels of granularity, support for mobility, and environmental dynamics as well as the simulation of timing effects. A module library with standardized interfaces and a power analysis tool have been developed to support the design and analysis of simulation models. The performance of the PAWiS simulator is comparable with other simulation environments.

Simulations of depleted CMOS sensors for high-radiation environments

CERN Document Server

Liu, J.; Bhat, S.; Breugnon, P.; Caicedo, I.; Chen, Z.; Degerli, Y.; Godiot-Basolo, S.; Guilloux, F.; Hemperek, T.; Hirono, T.; Hügging, F.; Krüger, H.; Moustakas, K.; Pangaud, P.; Rozanov, A.; Rymaszewski, P.; Schwemling, P.; Wang, M.; Wang, T.; Wermes, N.; Zhang, L.

2017-01-01

After the Phase II upgrade for the Large Hadron Collider (LHC), the increased luminosity requests a new upgraded Inner Tracker (ITk) for the ATLAS experiment. As a possible option for the ATLAS ITk, a new pixel detector based on High Voltage/High Resistivity CMOS (HV/HR CMOS) technology is under study. Meanwhile, a new CMOS pixel sensor is also under development for the tracker of Circular Electron Position Collider (CEPC). In order to explore the sensor electric properties, such as the breakdown voltage and charge collection efficiency, 2D/3D Technology Computer Aided Design (TCAD) simulations have been performed carefully for the above mentioned both of prototypes. In this paper, the guard-ring simulation for a HV/HR CMOS sensor developed for the ATLAS ITk and the charge collection efficiency simulation for a CMOS sensor explored for the CEPC tracker will be discussed in details. Some comparisons between the simulations and the latest measurements will also be addressed.

SMA-Based System for Environmental Sensors Released from an Unmanned Aerial Vehicle

Directory of Open Access Journals (Sweden)

Lorenzo Pellone

2017-01-01

Full Text Available In the work at hand, a shape memory alloy (SMA-based system is presented. The system, conceived for releasing environmental sensors from ground or small unmanned aerial vehicles, UAV (often named UAS, unmanned aerial system, is made of a door, integrated into the bottom of the fuselage, a device distributor, operated by a couple of antagonistic SMA springs, and a kinematic chain, to synchronize the deployment operation with the system movement. On the basis of the specifications (weight, available space, energy supply, sensors size, etc., the system design was addressed. After having identified the main system characteristics, a representative mock-up was manufactured, featuring the bottom part of the reference fuselage. Functionality tests were performed to prove the system capability to release the sensors; a detailed characterization was finally carried out, mainly finalized at correlating the kinematic chain displacement with the SMA spring temperature and the supplied electrical power. A comparison between theoretical predictions and experimental outcomes showed good agreement.

Development of an Effective System Identification and Control Capability for Quad-copter UAVs

Science.gov (United States)

Wei, Wei

In recent years, with the promise of extensive commercial applications, the popularity of Unmanned Aerial Vehicles (UAVs) has dramatically increased as witnessed by publications and mushrooming research and educational programs. Over the years, multi-copter aircraft have been chosen as a viable configuration for small-scale VTOL UAVs in the form of quad-copters, hexa-copters and octo-copters. Compared to the single main rotor configuration such as the conventional helicopter, multi-copter airframes require a simpler feedback control system and fewer mechanical parts. These characteristics make these UAV platforms, such as quad-copter which is the main emphasis in this dissertation, a rugged and competitive candidate for many applications in both military and civil areas. Because of its configuration and relative size, the small-scale quad-copter UAV system is inherently very unstable. In order to develop an effective control system through simulation techniques, obtaining an accurate dynamic model of a given quad-copter is imperative. Moreover, given the anticipated stringent safety requirements, fault tolerance will be a crucial component of UAV certification. Accurate dynamic modeling and control of this class of UAV is an enabling technology and is imperative for future commercial applications. In this work, the dynamic model of a quad-copter system in hover flight was identified using frequency-domain system identification techniques. A new and unique experimental system, data acquisition and processing procedure was developed catering specifically to the class of electric powered multi-copter UAV systems. The Comprehensive Identification from FrEquency Responses (CIFER RTM) software package, developed by US Army Aviation Development Directorate -- AFDD, was utilized along with flight tests to develop dynamic models of the quad-copter system. A new set of flight tests were conducted and the predictive capability of the dynamic models were successfully validated

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.

UAV-based NDVI calculation over grassland: An alternative approach

Science.gov (United States)

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

2016-04-01

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

Control system design for UAV trajectory tracking

Science.gov (United States)

Wang, Haitao; Gao, Jinyuan

2006-11-01

In recent years, because of the emerging requirements for increasing autonomy, the controller of uninhabited air vehicles must be augmented with a very sophisticated autopilot design which is capable of tracking complex and agile maneuvering trajectory. This paper provides a simplified control system framework to solve UAV maneuvering trajectory tracking problem. The flight control system is divided into three subsystems including command generation, transformation and allocation. According to the kinematics equations of the aircraft, flight path angle commands can be generated by desired 3D position from path planning. These commands are transformed to body angular rates through direct nonlinear mapping, which is simpler than common multi-loop method based on time scale separation assumption. Then, by using weighted pseudo-inverse method, the control surface deflections are allocated to follow body angular rates from the previous step. In order to improve the robustness, a nonlinear disturbance observer-based approach is used to compensate the uncertainty of system. A 6DOF nonlinear UAV model is controlled to demonstrate the performance of the trajectory tracking control system. Simulation results show that the control strategy is easy to be realized and the precision of tracking is satisfying.

Extracting Objects for Aerial Manipulation on UAVs Using Low Cost Stereo Sensors

Directory of Open Access Journals (Sweden)

Pablo Ramon Soria

2016-05-01

Full Text Available Giving unmanned aerial vehicles (UAVs the possibility to manipulate objects vastly extends the range of possible applications. This applies to rotary wing UAVs in particular, where their capability of hovering enables a suitable position for in-flight manipulation. Their manipulation skills must be suitable for primarily natural, partially known environments, where UAVs mostly operate. We have developed an on-board object extraction method that calculates information necessary for autonomous grasping of objects, without the need to provide the model of the object’s shape. A local map of the work-zone is generated using depth information, where object candidates are extracted by detecting areas different to our floor model. Their image projections are then evaluated using support vector machine (SVM classification to recognize specific objects or reject bad candidates. Our method builds a sparse cloud representation of each object and calculates the object’s centroid and the dominant axis. This information is then passed to a grasping module. Our method works under the assumption that objects are static and not clustered, have visual features and the floor shape of the work-zone area is known. We used low cost cameras for creating depth information that cause noisy point clouds, but our method has proved robust enough to process this data and return accurate results.

Flexible Structure Control Scheme of a UAVs Formation to Improve the Formation Stability During Maneuvers

Directory of Open Access Journals (Sweden)

Kownacki Cezary

2017-09-01

Full Text Available One of the issues related to formation flights, which requires to be still discussed, is the stability of formation flight in turns, where the aerodynamic conditions can be substantially different for outer vehicles due to varying bank angles. Therefore, this paper proposes a decentralized control algorithm based on a leader as the reference point for followers, i.e. other UAVs and two flocking behaviors responsible for local position control, i.e. cohesion and repulsion. But opposite to other research in this area, the structure of the formation becomes flexible (structure is being reshaped and bent according to actual turn radius of the leader. During turns the structure is bent basing on concentred circles with different radiuses corresponding to relative locations of vehicles in the structure. Simultaneously, UAVs' air-speeds must be modified according to the length of turn radius to achieve the stability of the structure. The effectiveness of the algorithm is verified by the results of simulated flights of five UAVs.

Design and simulation analysis of a novel pressure sensor based on graphene film

Science.gov (United States)

Nie, M.; Xia, Y. H.; Guo, A. Q.

2018-02-01

A novel pressure sensor structure based on graphene film as the sensitive membrane was proposed in this paper, which solved the problem to measure low and minor pressure with high sensitivity. Moreover, the fabrication process was designed which can be compatible with CMOS IC fabrication technology. Finite element analysis has been used to simulate the displacement distribution of the thin movable graphene film of the designed pressure sensor under the different pressures with different dimensions. From the simulation results, the optimized structure has been obtained which can be applied in the low measurement range from 10hPa to 60hPa. The length and thickness of the graphene film could be designed as 100μm and 0.2μm, respectively. The maximum mechanical stress on the edge of the sensitive membrane was 1.84kPa, which was far below the breaking strength of the silicon nitride and graphene film.

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.

AirSTAR: A UAV Platform for Flight Dynamics and Control System Testing

Science.gov (United States)

Jordan, Thomas L.; Foster, John V.; Bailey, Roger M.; Belcastro, Christine M.

2006-01-01

As part of the NASA Aviation Safety Program at Langley Research Center, a dynamically scaled unmanned aerial vehicle (UAV) and associated ground based control system are being developed to investigate dynamics modeling and control of large transport vehicles in upset conditions. The UAV is a 5.5% (seven foot wingspan), twin turbine, generic transport aircraft with a sophisticated instrumentation and telemetry package. A ground based, real-time control system is located inside an operations vehicle for the research pilot and associated support personnel. The telemetry system supports over 70 channels of data plus video for the downlink and 30 channels for the control uplink. Data rates are in excess of 200 Hz. Dynamic scaling of the UAV, which includes dimensional, weight, inertial, actuation, and control system scaling, is required so that the sub-scale vehicle will realistically simulate the flight characteristics of the full-scale aircraft. This testbed will be utilized to validate modeling methods, flight dynamics characteristics, and control system designs for large transport aircraft, with the end goal being the development of technologies to reduce the fatal accident rate due to loss-of-control.

Simulations of piezoelectric pressure sensor for radial artery pulse measurement

Energy Technology Data Exchange (ETDEWEB)

Joshi, Abhay B. [Department of Electronic Science, University of Pune, Pune 411 007 (India); Kalange, Ashok E. [Department of Electronic Science, University of Pune, Pune 411 007 (India); Tuljaram Chaturchand College, Baramati 413 102 (India); Bodas, Dhananjay, E-mail: dhananjay.bodas@gmail.co [Center for Nanobio Sciences, Agharkar Research Institute, Pune 411 004 (India); Gangal, S.A. [Department of Electronic Science, University of Pune, Pune 411 007 (India)

2010-04-15

A radial artery pulse is used to diagnose human body constitution (Prakruti) in Ayurveda. A system consisting of piezoelectric sensor (22 mm x 12 mm), data acquisition card and LabView software was used to record the pulse data. The pulse obtained from the sensor was noisy, even though signal processing was done. Moreover due to large sized senor accurate measurements were not possible. Hence, a need was felt to develop a sensor of the size of the order of finger tip with a resonant frequency of the order of 1 Hz. A micromachined pressure sensor based on piezoelectric sensing mechanism was designed and simulated using CoventorWare. Simulations were carried out by varying dimensions of the sensor to optimize the resonant frequency, stresses and voltage generated as a function of applied pressure. All simulations were done with pressure ranging of 1-30 kPa, which is the range used by Ayurvedic practitioners for diagnosis. Preliminary work on fabrication of such a sensor was carried out successfully.

Simulations of piezoelectric pressure sensor for radial artery pulse measurement

International Nuclear Information System (INIS)

Joshi, Abhay B.; Kalange, Ashok E.; Bodas, Dhananjay; Gangal, S.A.

2010-01-01

A radial artery pulse is used to diagnose human body constitution (Prakruti) in Ayurveda. A system consisting of piezoelectric sensor (22 mm x 12 mm), data acquisition card and LabView software was used to record the pulse data. The pulse obtained from the sensor was noisy, even though signal processing was done. Moreover due to large sized senor accurate measurements were not possible. Hence, a need was felt to develop a sensor of the size of the order of finger tip with a resonant frequency of the order of 1 Hz. A micromachined pressure sensor based on piezoelectric sensing mechanism was designed and simulated using CoventorWare. Simulations were carried out by varying dimensions of the sensor to optimize the resonant frequency, stresses and voltage generated as a function of applied pressure. All simulations were done with pressure ranging of 1-30 kPa, which is the range used by Ayurvedic practitioners for diagnosis. Preliminary work on fabrication of such a sensor was carried out successfully.

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

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.

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.

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.

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

Science.gov (United States)

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

2018-04-01

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

Magnetic profiling of the San Andreas Fault using a dual magnetometer UAV aerial survey system.

Science.gov (United States)

Abbate, J. A.; Angelopoulos, V.; Masongsong, E. V.; Yang, J.; Medina, H. R.; Moon, S.; Davis, P. M.

2017-12-01

Aeromagnetic survey methods using planes are more time-effective than hand-held methods, but can be far more expensive per unit area unless large areas are covered. The availability of low cost UAVs and low cost, lightweight fluxgate magnetometers (FGMs) allows, with proper offset determination and stray fields correction, for low-cost magnetic surveys. Towards that end, we have developed a custom multicopter UAV for magnetic mapping using a dual 3-axis fluxgate magnetometer system: the GEOphysical Drone Enhanced Survey Instrument (GEODESI). A high precision sensor measures the UAV's position and attitude (roll, pitch, and yaw) and is recorded using a custom Arduino data processing system. The two FGMs (in-board and out-board) are placed on two ends of a vertical 1m boom attached to the base of the UAV. The in-board FGM is most sensitive to stray fields from the UAV and its signal is used, after scaling, to clean the signal of the out-board FGM from the vehicle noise. The FGMs record three orthogonal components of the magnetic field in the UAV body coordinates which are then transformed into a north-east-down coordinate system using a rotation matrix determined from the roll-pitch-yaw attitude data. This ensures knowledge of the direction of all three field components enabling us to perform inverse modeling of magnetic anomalies with greater accuracy than total or vertical field measurements used in the past. Field tests were performed at Dragon's Back Pressure Ridge in the Carrizo Plain of California, where there is a known crossing of the San Andreas Fault. Our data and models were compared to previously acquired LiDAR and hand-held magnetometer measurements. Further tests will be carried out to solidify our results and streamline our processing for educational use in the classroom and student field training.

Simulation of novel intensity modulated cascaded coated LPFG sensor based on PMTP

Science.gov (United States)

Feng, Wenbin; Gu, Zhengtian; Lin, Qiang; Sang, Jiangang

2017-12-01

This paper presents a novel intensity modulated cascaded long-period fiber grating (CLPFG) sensor which is cascaded by two same coated long-period fiber gratings (LPFGs) operating at the phase-matching turning point (PMTP). The sensor combines the high sensitivity of LPFG operating at PMTP and the narrow bandwidth of interference attenuation band of CLPFG, so a higher response to small change of the surrounding refractive index (SRI) can be obtained by intensity modulation. Based on the coupled-mode theory, the grating parameters of the PMTP of a middle odd order cladding mode of a single LPFG are calculated. Then this two same LPFGs are cascaded into a CLPFG, and the optical transmission spectrum of the CLPFG is calculated by transfer matrix method. A resonant wavelength of a special interference attenuation band whose intensity has the highest response to SRI, is selected form CLPFG’s spectrum, and setting the resonant wavelength as the operating wavelength of the sensor. Furthermore, the simulation results show that the resolution of SRI of this CLPFG is available to 1.97 × 10-9 by optimizing the film optical parameters, which is about three orders of magnitude higher than coated dual-peak LPFG and cascaded LPFG sensors. It is noteworthy that the sensor is also sensitive to the refractive index of coat, so that the sensor is expected to be applied to detections of gas, PH value, humidity and so on, in the future.

An Integrative Object-Based Image Analysis Workflow for Uav Images

Science.gov (United States)

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

2016-06-01

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

AN INTEGRATIVE OBJECT-BASED IMAGE ANALYSIS WORKFLOW FOR UAV IMAGES

Directory of Open Access Journals (Sweden)

H. Yu

2016-06-01

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

An accelerated image matching technique for UAV orthoimage registration

Science.gov (United States)

Tsai, Chung-Hsien; Lin, Yu-Ching

2017-06-01

Using an Unmanned Aerial Vehicle (UAV) drone with an attached non-metric camera has become a popular low-cost approach for collecting geospatial data. A well-georeferenced orthoimage is a fundamental product for geomatics professionals. To achieve high positioning accuracy of orthoimages, precise sensor position and orientation data, or a number of ground control points (GCPs), are often required. Alternatively, image registration is a solution for improving the accuracy of a UAV orthoimage, as long as a historical reference image is available. This study proposes a registration scheme, including an Accelerated Binary Robust Invariant Scalable Keypoints (ABRISK) algorithm and spatial analysis of corresponding control points for image registration. To determine a match between two input images, feature descriptors from one image are compared with those from another image. A "Sorting Ring" is used to filter out uncorrected feature pairs as early as possible in the stage of matching feature points, to speed up the matching process. The results demonstrate that the proposed ABRISK approach outperforms the vector-based Scale Invariant Feature Transform (SIFT) approach where radiometric variations exist. ABRISK is 19.2 times and 312 times faster than SIFT for image sizes of 1000 × 1000 pixels and 4000 × 4000 pixels, respectively. ABRISK is 4.7 times faster than Binary Robust Invariant Scalable Keypoints (BRISK). Furthermore, the positional accuracy of the UAV orthoimage after applying the proposed image registration scheme is improved by an average of root mean square error (RMSE) of 2.58 m for six test orthoimages whose spatial resolutions vary from 6.7 cm to 10.7 cm.

Device Simulation of Monolithic Active Pixel Sensors: Radiation Damage Effects

International Nuclear Information System (INIS)

Fourches, N.T.

2009-01-01

Vertexing for the future International Linear Collider represents a challenging goal because of the high spatial resolution required with low material budget and high ionizing radiation tolerance. CMOS Monolithic Active Pixel Sensors (MAPS) represent a good potential solution for this purpose. Up to now many MAPS sensors have been developed. They are based on various architectures and manufactured in different processes. However, up so far, the sensor diode has not been the subject of extensive modelization and simulation. Published simulation studies of sensor-signal formation have been less numerous than measurements on real sensors. This is a cause for concern because such sensor is physically based on the partially depleted diode, in the vicinity of which the electric field collects the minority carriers generated by an incident MIP (minimum ionizing particle). Although the microscopic mechanisms are well known and modelled, the global physical mechanisms for signal formation are not very rigorously established. This is partly due to the presence of a predominant diffusion component in the charge transport. We present here simulations mainly based on the S-PISCES code, in which physical mechanisms affecting transport are taken into account. Diffusion, influence of residual carrier concentration due to the doping level in the sensitive volume, and more importantly charge trapping due to deep levels in the active (detecting) layer are studied together with geometric aspects. The effect of neutron irradiation is studied to assess the effects of deep traps. A comparison with available experimental data, obtained on processed MAPS before or after neutron irradiation will be introduced. Simulated reconstruction of the Minimum Ionizing Particle (MIP) point of impact in two dimensions is also investigated. For further steps, guidelines for process choices of next Monolithic Active Pixel Sensors are introduced. (authors)

Sim4CV: A Photo-Realistic Simulator for Computer Vision Applications

KAUST Repository

Mü ller, Matthias; Casser, Vincent; Lahoud, Jean; Smith, Neil; Ghanem, Bernard

2018-01-01

based cars, unmanned aerial vehicles (UAVs), and animated human actors in diverse urban and suburban 3D environments. We demonstrate the versatility of the simulator with two case studies: autonomous UAV-based tracking of moving objects and autonomous

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.

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.

TopSPICE Simulations for Temperature Compensation of ISFET/MEMFET Micro-Sensor

Directory of Open Access Journals (Sweden)

Sawsen AZZOUZI

2014-05-01

Full Text Available In this work, an ISFET (Ion Sensitive Field Effect Transistor/MEMFET (Membrane Field Effect Transistor interface circuit with temperature compensation has been successfully designed and simulated. In each interface, we used the macro-model of ISFET/MEMFET based chemical sensors simulated in TopSPICE. The simulation results of the different sensing circuits of ISFET/MEMFETs for temperature compensation show that the readout configuration for ISFET/MEMFET sensors based on Wheatstone-Bridge connection is the most effective with a temperature drift 5´10-6 mV/°C.

Fuzzy-Based Sensor Fusion for Cognitive Radio-Based Vehicular Ad Hoc and Sensor Networks

Directory of Open Access Journals (Sweden)

Mohammad Jalil Piran

2015-01-01

Full Text Available In wireless sensor networks, sensor fusion is employed to integrate the acquired data from diverse sensors to provide a unified interpretation. The best and most salient advantage of sensor fusion is to obtain high-level information in both statistical and definitive aspects, which cannot be attained by a single sensor. In this paper, we propose a novel sensor fusion technique based on fuzzy theory for our earlier proposed Cognitive Radio-based Vehicular Ad Hoc and Sensor Networks (CR-VASNET. In the proposed technique, we considered four input sensor readings (antecedents and one output (consequent. The employed mobile nodes in CR-VASNET are supposed to be equipped with diverse sensors, which cater to our antecedent variables, for example, The Jerk, Collision Intensity, and Temperature and Inclination Degree. Crash_Severity is considered as the consequent variable. The processing and fusion of the diverse sensory signals are carried out by fuzzy logic scenario. Accuracy and reliability of the proposed protocol, demonstrated by the simulation results, introduce it as an applicable system to be employed to reduce the causalities rate of the vehicles’ crashes.

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.

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

Directory of Open Access Journals (Sweden)

Rahmad Hidayat

2017-01-01

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

Observability-Based Guidance and Sensor Placement

Science.gov (United States)

Hinson, Brian T.

Control system performance is highly dependent on the quality of sensor information available. In a growing number of applications, however, the control task must be accomplished with limited sensing capabilities. This thesis addresses these types of problems from a control-theoretic point-of-view, leveraging system nonlinearities to improve sensing performance. Using measures of observability as an information quality metric, guidance trajectories and sensor distributions are designed to improve the quality of sensor information. An observability-based sensor placement algorithm is developed to compute optimal sensor configurations for a general nonlinear system. The algorithm utilizes a simulation of the nonlinear system as the source of input data, and convex optimization provides a scalable solution method. The sensor placement algorithm is applied to a study of gyroscopic sensing in insect wings. The sensor placement algorithm reveals information-rich areas on flexible insect wings, and a comparison to biological data suggests that insect wings are capable of acting as gyroscopic sensors. An observability-based guidance framework is developed for robotic navigation with limited inertial sensing. Guidance trajectories and algorithms are developed for range-only and bearing-only navigation that improve navigation accuracy. Simulations and experiments with an underwater vehicle demonstrate that the observability measure allows tuning of the navigation uncertainty.

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.

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.

Human-Interaction Challenges in UAV-Based Autonomous Surveillance

Science.gov (United States)

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

2004-01-01

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

Modelling multi-rotor UAVs swarm deployment using virtual pheromones

Science.gov (United States)

Pujol, Mar; Rizo, Ramón; Rizo, Carlos

2018-01-01

In this work, a swarm behaviour for multi-rotor Unmanned Aerial Vehicles (UAVs) deployment will be presented. The main contribution of this behaviour is the use of a virtual device for quantitative sematectonic stigmergy providing more adaptable behaviours in complex environments. It is a fault tolerant highly robust behaviour that does not require prior information of the area to be covered, or to assume the existence of any kind of information signals (GPS, mobile communication networks …), taking into account the specific features of UAVs. This behaviour will be oriented towards emergency tasks. Their main goal will be to cover an area of the environment for later creating an ad-hoc communication network, that can be used to establish communications inside this zone. Although there are several papers on robotic deployment it is more difficult to find applications with UAV systems, mainly because of the existence of various problems that must be overcome including limitations in available sensory and on-board processing capabilities and low flight endurance. In addition, those behaviours designed for UAVs often have significant limitations on their ability to be used in real tasks, because they assume specific features, not easily applicable in a general way. Firstly, in this article the characteristics of the simulation environment will be presented. Secondly, a microscopic model for deployment and creation of ad-hoc networks, that implicitly includes stigmergy features, will be shown. Then, the overall swarm behaviour will be modeled, providing a macroscopic model of this behaviour. This model can accurately predict the number of agents needed to cover an area as well as the time required for the deployment process. An experimental analysis through simulation will be carried out in order to verify our models. In this analysis the influence of both the complexity of the environment and the stigmergy system will be discussed, given the data obtained in the

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.

Analysis of specification of an electrode type sensor equivalent circuit on the base of impedance spectroscopy simulation

International Nuclear Information System (INIS)

Ogurtsov, V I; Mathewson, A; Sheehan, M M

2005-01-01

Simulation of electrochemical impedance spectroscopy (EIS) based on a LabVIEW model of a complex impedance measuring system in the frequency domain has been investigated to specify parameters of Randle's equivalent circuit, which is ordinarily used for electrode sensors. The model was based on a standard system for EIS instrumentation and consisted of a sensor modelled by Randle's equivalent circuit, a source of harmonic frequency sweep voltage applied to the sensor and a transimpedance amplifier, which transformed the sensor current to voltage. It provided impedance spectroscopy data for different levels of noise, modelled by current and voltage equivalent noise sources applied to the amplifier input. The noise influence on Randle's equivalent circuit specification was analysed by considering the behaviour of the approximation error. Different metrics including absolute, relative, semilogarithmic and logarithmic based distance between complex numbers on a complex plane were considered and compared to one another for evaluating this error. It was shown that the relative and logarithmic based metrics provide more reliable results for the determination of circuit parameters

Analysis of specification of an electrode type sensor equivalent circuit on the base of impedance spectroscopy simulation

Energy Technology Data Exchange (ETDEWEB)

Ogurtsov, V I; Mathewson, A; Sheehan, M M [Tyndall National Institute, Lee Maltings, Prospect Row, Cork (Ireland)

2005-01-01

Simulation of electrochemical impedance spectroscopy (EIS) based on a LabVIEW model of a complex impedance measuring system in the frequency domain has been investigated to specify parameters of Randle's equivalent circuit, which is ordinarily used for electrode sensors. The model was based on a standard system for EIS instrumentation and consisted of a sensor modelled by Randle's equivalent circuit, a source of harmonic frequency sweep voltage applied to the sensor and a transimpedance amplifier, which transformed the sensor current to voltage. It provided impedance spectroscopy data for different levels of noise, modelled by current and voltage equivalent noise sources applied to the amplifier input. The noise influence on Randle's equivalent circuit specification was analysed by considering the behaviour of the approximation error. Different metrics including absolute, relative, semilogarithmic and logarithmic based distance between complex numbers on a complex plane were considered and compared to one another for evaluating this error. It was shown that the relative and logarithmic based metrics provide more reliable results for the determination of circuit parameters.

Application of Low-Cost Fixed-Wing UAV for Inland Lakes Shoreline Investigation

Science.gov (United States)

Templin, Tomasz; Popielarczyk, Dariusz; Kosecki, Rafał

2017-10-01

One of the most important factors that influences the performance of geomorphologic parameters on urban lakes is the water level. It fluctuates periodically, causing shoreline changes. It is especially significant for typical environmental studies like bathymetric surveys, morphometric parameters calculation, sediment depth changes, thermal structure, water quality monitoring, etc. In most reservoirs, it can be obtained from digitized historical maps or plans or directly measured using the instruments such as: geodetic total station, GNSS receivers, UAV with different sensors, satellite and aerial photos, terrestrial and airborne light detection and ranging, or others. Today one of the most popular measuring platforms, increasingly applied in many applications is UAV. Unmanned aerial system can be a cheap, easy to use, on-demand technology for gathering remote sensing data. Our study presents a reliable methodology for shallow lake shoreline investigation with the use of a low-cost fixed-wing UAV system. The research was implemented on a small, eutrophic urban inland reservoir located in the northern part of Poland—Lake Suskie. The geodetic TS, and RTK/GNSS measurements, hydroacoustic soundings and experimental aerial mapping were conducted by the authors in 2012-2015. The article specifically describes the UAV system used for experimental measurements, the obtained results and the accuracy analysis. Final conclusions demonstrate that even a low-cost fixed-wing UAV can provide an excellent tool for accurately surveying a shallow lake shoreline and generate valuable geoinformation data collected definitely faster than when traditional geodetic methods are employed.

Unmanned Aerial Vehicle Based Wireless Sensor Network for Marine-Coastal Environment Monitoring.

Science.gov (United States)

Trasviña-Moreno, Carlos A; Blasco, Rubén; Marco, Álvaro; Casas, Roberto; Trasviña-Castro, Armando

2017-02-24

Marine environments are delicate ecosystems which directly influence local climates, flora, fauna, and human activities. Their monitorization plays a key role in their preservation, which is most commonly done through the use of environmental sensing buoy networks. These devices transmit data by means of satellite communications or close-range base stations, which present several limitations and elevated infrastructure costs. Unmanned Aerial Vehicles (UAV) are another alternative for remote environmental monitoring which provide new types of data and ease of use. These aircraft are mainly used in video capture related applications, in its various light spectrums, and do not provide the same data as sensing buoys, nor can they be used for such extended periods of time. The aim of this research is to provide a flexible, easy to deploy and cost-effective Wireless Sensor Network (WSN) for monitoring marine environments. This proposal uses a UAV as a mobile data collector, low-power long-range communications and sensing buoys as part of a single WSN. A complete description of the design, development, and implementation of the various parts of this system is presented, as well as its validation in a real-world scenario.

Investigation of a robust tendon-sheath mechanism for flexible membrane wing application in mini-UAV

Science.gov (United States)

Lee, Shian; Tjahjowidodo, Tegoeh; Lee, Hsuchew; Lai, Benedict

2017-02-01

Two inherent issues manifest themselves in flying mini-unmanned aerial vehicles (mini-UAV) in the dense area at tropical climate regions, namely disturbances from gusty winds and limited space for deployment tasks. Flexible membrane wing (FMW) UAVs are seen to be potentials to mitigate these problems. FMWs are adaptable to gusty airflow as the wings are able to flex according to the gust load to reduce the effective angle-of-attack, thus, reducing the aerodynamic loads on the wing. On the other hand, the flexible structure is allowing the UAV to fold in a compact package, and later on, the mini-UAV can be deployed instantly from the storage tube, e.g. through a catapult mechanism. This paper discusses the development of an FMW UAV actuated by a tendon-sheath mechanism (TSM). This approach allows the wing to morph to generate a rolling moment, while still allowing the wing to fold. Dynamic characteristics of the mechanism that exhibits the strong nonlinear phenomenon of friction on TSM are modeled and compensated for. A feed-forward controller was implemented based on the identified nonlinear behavior to control the warping position of the wing. The proposed strategy is validated experimentally in a wind tunnel facility by creating a gusty environment that is imitating a realistic gusty condition based upon the results of computational fluid dynamics (CFD) simulation. The results demonstrate a stable and robust wing-warping actuation, even in gusty conditions. Accurate wing-warping can be achieved via the TSM, while also allowing the wings to fold.

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.

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.

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

Science.gov (United States)

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

2018-04-01

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

Using Calibrated RGB Imagery from Low-Cost Uavs for Grassland Monitoring: Case Study at the Rengen Grassland Experiment (rge), Germany

Science.gov (United States)

Lussem, U.; Hollberg, J.; Menne, J.; Schellberg, J.; Bareth, G.

2017-08-01

Monitoring the spectral response of intensively managed grassland throughout the growing season allows optimizing fertilizer inputs by monitoring plant growth. For example, site-specific fertilizer application as part of precision agriculture (PA) management requires information within short time. But, this requires field-based measurements with hyper- or multispectral sensors, which may not be feasible on a day to day farming practice. Exploiting the information of RGB images from consumer grade cameras mounted on unmanned aerial vehicles (UAV) can offer cost-efficient as well as near-real time analysis of grasslands with high temporal and spatial resolution. The potential of RGB imagery-based vegetation indices (VI) from consumer grade cameras mounted on UAVs has been explored recently in several. However, for multitemporal analyses it is desirable to calibrate the digital numbers (DN) of RGB-images to physical units. In this study, we explored the comparability of the RGBVI from a consumer grade camera mounted on a low-cost UAV to well established vegetation indices from hyperspectral field measurements for applications in grassland. The study was conducted in 2014 on the Rengen Grassland Experiment (RGE) in Germany. Image DN values were calibrated into reflectance by using the Empirical Line Method (Smith & Milton 1999). Depending on sampling date and VI the correlation between the UAV-based RGBVI and VIs such as the NDVI resulted in varying R2 values from no correlation to up to 0.9. These results indicate, that calibrated RGB-based VIs have the potential to support or substitute hyperspectral field measurements to facilitate management decisions on grasslands.

USING CALIBRATED RGB IMAGERY FROM LOW-COST UAVS FOR GRASSLAND MONITORING: CASE STUDY AT THE RENGEN GRASSLAND EXPERIMENT (RGE, GERMANY

Directory of Open Access Journals (Sweden)

U. Lussem

2017-08-01

Full Text Available Monitoring the spectral response of intensively managed grassland throughout the growing season allows optimizing fertilizer inputs by monitoring plant growth. For example, site-specific fertilizer application as part of precision agriculture (PA management requires information within short time. But, this requires field-based measurements with hyper- or multispectral sensors, which may not be feasible on a day to day farming practice. Exploiting the information of RGB images from consumer grade cameras mounted on unmanned aerial vehicles (UAV can offer cost-efficient as well as near-real time analysis of grasslands with high temporal and spatial resolution. The potential of RGB imagery-based vegetation indices (VI from consumer grade cameras mounted on UAVs has been explored recently in several. However, for multitemporal analyses it is desirable to calibrate the digital numbers (DN of RGB-images to physical units. In this study, we explored the comparability of the RGBVI from a consumer grade camera mounted on a low-cost UAV to well established vegetation indices from hyperspectral field measurements for applications in grassland. The study was conducted in 2014 on the Rengen Grassland Experiment (RGE in Germany. Image DN values were calibrated into reflectance by using the Empirical Line Method (Smith & Milton 1999. Depending on sampling date and VI the correlation between the UAV-based RGBVI and VIs such as the NDVI resulted in varying R2 values from no correlation to up to 0.9. These results indicate, that calibrated RGB-based VIs have the potential to support or substitute hyperspectral field measurements to facilitate management decisions on grasslands.

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

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.

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

Science.gov (United States)

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

2016-06-01

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

Autonomous Chemical Vapour Detection by Micro UAV

Directory of Open Access Journals (Sweden)

Kent Rosser

2015-12-01

Full Text Available The ability to remotely detect and map chemical vapour clouds in open air environments is a topic of significant interest to both defence and civilian communities. In this study, we integrate a prototype miniature colorimetric chemical sensor developed for methyl salicylate (MeS, as a model chemical vapour, into a micro unmanned aerial vehicle (UAV, and perform flights through a raised MeS vapour cloud. Our results show that that the system is capable of detecting MeS vapours at low ppm concentration in real-time flight and rapidly sending this information to users by on-board telemetry. Further, the results also indicate that the sensor is capable of distinguishing “clean” air from “dirty”, multiple times per flight, allowing us to look towards autonomous cloud mapping and source localization applications. Further development will focus on a broader range of integrated sensors, increased autonomy of detection and improved engineering of the system.

Visual Servoing for an Autonomous Hexarotor Using a Neural Network Based PID Controller.

Science.gov (United States)

Lopez-Franco, Carlos; Gomez-Avila, Javier; Alanis, Alma Y; Arana-Daniel, Nancy; Villaseñor, Carlos

2017-08-12

In recent years, unmanned aerial vehicles (UAVs) have gained significant attention. However, we face two major drawbacks when working with UAVs: high nonlinearities and unknown position in 3D space since it is not provided with on-board sensors that can measure its position with respect to a global coordinate system. In this paper, we present a real-time implementation of a servo control, integrating vision sensors, with a neural proportional integral derivative (PID), in order to develop an hexarotor image based visual servo control (IBVS) that knows the position of the robot by using a velocity vector as a reference to control the hexarotor position. This integration requires a tight coordination between control algorithms, models of the system to be controlled, sensors, hardware and software platforms and well-defined interfaces, to allow the real-time implementation, as well as the design of different processing stages with their respective communication architecture. All of these issues and others provoke the idea that real-time implementations can be considered as a difficult task. For the purpose of showing the effectiveness of the sensor integration and control algorithm to address these issues on a high nonlinear system with noisy sensors as cameras, experiments were performed on the Asctec Firefly on-board computer, including both simulation and experimenta results.

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.

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

Directory of Open Access Journals (Sweden)

Dong-Wook Kim

2018-04-01

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

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

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

International Nuclear Information System (INIS)

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

2015-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2015-10-11

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

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

Science.gov (United States)

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

2015-06-01

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

Precision of EM Simulation Based Wireless Location Estimation in Multi-Sensor Capsule Endoscopy.

Science.gov (United States)

Khan, Umair; Ye, Yunxing; Aisha, Ain-Ul; Swar, Pranay; Pahlavan, Kaveh

2018-01-01

In this paper, we compute and examine two-way localization limits for an RF endoscopy pill as it passes through an individuals gastrointestinal (GI) tract. We obtain finite-difference time-domain and finite element method-based simulation results position assessment employing time of arrival (TOA). By means of a 3-D human body representation from a full-wave simulation software and lognormal models for TOA propagation from implant organs to body surface, we calculate bounds on location estimators in three digestive organs: stomach, small intestine, and large intestine. We present an investigation of the causes influencing localization precision, consisting of a range of organ properties; peripheral sensor array arrangements, number of pills in cooperation, and the random variations in transmit power of sensor nodes. We also perform a localization precision investigation for the situation where the transmission signal of the antenna is arbitrary with a known probability distribution. The computational solver outcome shows that the number of receiver antennas on the exterior of the body has higher impact on the precision of the location than the amount of capsules in collaboration within the GI region. The large intestine is influenced the most by the transmitter power probability distribution.

Gust alleviation of highly flexible UAVs with artificial hair sensors

Science.gov (United States)

Su, Weihua; Reich, Gregory W.

2015-04-01

Artificial hair sensors (AHS) have been recently developed in Air Force Research Laboratory (AFRL) using carbon nanotube (CNT). The deformation of CNT in air flow causes voltage and current changes in the circuit, which can be used to quantify the dynamic pressure and aerodynamic load along the wing surface. AFRL has done a lot of essential work in design, manufacturing, and measurement of AHSs. The work in this paper is to bridge the current AFRL's work on AHSs and their feasible applications in flight dynamics and control (e.g., the gust alleviation) of highly flexible aircraft. A highly flexible vehicle is modeled using a strain-based geometrically nonlinear beam formulation, coupled with finite-state inflow aerodynamics. A feedback control algorithm for the rejection of gust perturbations will be developed. A simplified Linear Quadratic Regulator (LQR) controller will be implemented based on the state-space representation of the linearized system. All AHS measurements will be used as the control input, i.e., wing sectional aerodynamic loads will be defined as the control output for designing the feedback gain. Once the controller is designed, closed-loop aeroelastic simulations will be performed to evaluate the performance of different controllers with the force feedback and be compared to traditional controller designs with the state feedback. From the study, the feasibility of AHSs in flight control will be assessed. The whole study will facilitate in building a fly-by-feel simulation environment for autonomous vehicles.

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

Science.gov (United States)

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

2016-05-01

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

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

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

Science.gov (United States)

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

2017-09-01

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

Next Generation UAV Based Spectral Systems for Environmental Monitoring

Data.gov (United States)

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

Design and application of star map simulation system for star sensors

Science.gov (United States)

Wu, Feng; Shen, Weimin; Zhu, Xifang; Chen, Yuheng; Xu, Qinquan

2013-12-01

Modern star sensors are powerful to measure attitude automatically which assure a perfect performance of spacecrafts. They achieve very accurate attitudes by applying algorithms to process star maps obtained by the star camera mounted on them. Therefore, star maps play an important role in designing star cameras and developing procession algorithms. Furthermore, star maps supply significant supports to exam the performance of star sensors completely before their launch. However, it is not always convenient to supply abundant star maps by taking pictures of the sky. Thus, star map simulation with the aid of computer attracts a lot of interests by virtue of its low price and good convenience. A method to simulate star maps by programming and extending the function of the optical design program ZEMAX is proposed. The star map simulation system is established. Firstly, based on analyzing the working procedures of star sensors to measure attitudes and the basic method to design optical system by ZEMAX, the principle of simulating star sensor imaging is given out in detail. The theory about adding false stars and noises, and outputting maps is discussed and the corresponding approaches are proposed. Then, by external programming, the star map simulation program is designed and produced. Its user interference and operation are introduced. Applications of star map simulation method in evaluating optical system, star image extraction algorithm and star identification algorithm, and calibrating system errors are presented completely. It was proved that the proposed simulation method provides magnificent supports to the study on star sensors, and improves the performance of star sensors efficiently.

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

Directory of Open Access Journals (Sweden)

C. I. Yoo

2016-06-01

Full Text Available Natural beach is controlled by many factors related to wave and tidal forces, wind, sediment, and initial topography. For this reason, if numerous topographic data of beach is accurately collected, coastal erosion/acceleration is able to be assessed and clarified. Generally, however, many studies on coastal erosion have limitation to analyse the whole beach, carried out of partial area as like shoreline (horizontal 2D and beach profile (vertical 2D on account of limitation of numerical simulation. This is an important application for prevention of coastal erosion, and UAV photogrammetry is also used to 3D topographic data. This paper analyses the use of unmanned aerial vehicles (UAV to 3D map and beach volume change. UAV (Quadcopter equipped with a non-metric camera was used to acquire images in Songjung beach which is located south-east Korea peninsula. The dynamics of beach topography, its geometric properties and estimates of eroded and deposited sand volumes were determined by combining elevation data with quarterly RTK-VRS measurements. To explore the new possibilities for assessment of coastal change we have developed a methodology for 3D analysis of coastal topography evolution based on existing high resolution elevation data combined with low coast, UAV and on-ground RTK-VRS surveys. DSMs were obtained by stereo-matching using Agisoft Photoscan. Using GCPs the vertical accuracy of the DSMs was found to be 10 cm or better. The resulting datasets were integrated in a local coordinates and the method proved to be a very useful fool for the detection of areas where coastal erosion occurs and for the quantification of beach change. The value of such analysis is illustrated by applications to coastal of South Korea sites that face significant management challenges.

ANALYSIS OF SPECTRAL CHARACTERISTICS AMONG DIFFERENT SENSORS BY USE OF SIMULATED RS IMAGES

Institute of Scientific and Technical Information of China (English)

无

2000-01-01

This research, by use of RS image-simulating method, simulated apparent reflectance images at sensor level and ground-reflectance images of SPOT-HRV,CBERS-CCD,Landsat-TM and NOAA14-AVHRR' s corresponding bands. These images were used to analyze sensor's differences caused by spectral sensitivity and atmospheric impacts. The differences were analyzed on Normalized Difference Vegetation Index(NDVI). The results showed that the differences of sensors' spectral characteristics cause changes of their NDVI and reflectance. When multiple sensors' data are applied to digital analysis, the error should be taken into account. Atmospheric effect makes NDVI smaller, and atn~pheric correction has the tendency of increasing NDVI values. The reflectance and their NDVIs of different sensors can be used to analyze the differences among sensor' s features. The spectral analysis method based on RS simulated images can provide a new way to design the spectral characteristics of new sensors.

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

Science.gov (United States)

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

2018-06-01

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

Gravitational Reference Sensor Front-End Electronics Simulator for LISA

International Nuclear Information System (INIS)

Meshksar, Neda; Ferraioli, Luigi; Mance, Davor; Zweifel, Peter; Giardini, Domenico; Ten Pierick, Jan

2017-01-01

At the ETH Zurich we are developing a modular simulator that provides a realistic simulation of the Front End Electronics (FEE) for LISA Gravitational Reference Sensor (GRS). It is based on the GRS FEE-simulator already implemented for LISA Pathfinder. It considers, in particular, the non-linearity and the critical details of hardware, such as the non-linear multiplicative noise caused by voltage reference instability, test mass charging and detailed actuation and sensing algorithms. We present the simulation modules, considering the above-mentioned features. Based on the ETH GRS FEE-simulator for LISA Pathfinder we aim to develop a modular simulator that provides a realistic simulation of GRS FEE for LISA. (paper)

UAV applications for thermodynamic profiling: Emphasis on ice fog research

Science.gov (United States)

Gultepe, Ismail; Heymsfield, Andrew J.; Fernando, Harindra J. S.; Hoch, Sebastian W.; Ware, Randolph

2016-04-01

Ice fog occurs often over the Arctic, cold climatic, and mountainous regions for about 30% of time where temperature (T) can go down to -10°C or below. Ice Nucleation (IN) and cooling processes play an important role by the controlling the intensity of ice fog conditions that affect aviation application, transportation, and local climate. Ice fog can also occur at T above -10°C but close to 0°C it occurs due to freezing of supercooled droplets that include an IN. To better document ice fog conditions, observations from the ice fog events of the Indirect and Semi-Direct Aerosol effects on Climate (ISDAC) project, Barrow, Alaska, Fog Remote Sensing And Modeling (FRAM) project Yellowknife, Northwest Territories, and the Mountain Terrain Atmospheric Modeling and Observations (MATERHORN) project, Heber City, Utah, were analyzed.. Measurements difficulties of small ice fog particles at cold temperatures and low-level flying restrictions prevent observations from aircraft within the surface boundary layer. However, unmanned Aerial Vehicles (UAVs) can be operated safely to measure IN number concentration, Relative Humidity with respect to ice (RHi), T, horizontal wind speed (Uh) and direction, and ice crystal spectra less than about 500 micron. Thermodynamic profiling by a Radiometrics Profiling Microwave Radiometer (PMWR) and Vaisala CL51 ceilometer was used to describe ice fog conditions in the vertical and its time development. In this presentation, ice fog characteristics and its thermodynamic environment will be presented using both ground-based and airborne platforms such as a UAV with new sensors. Some examples of measurements from the UAV for future research, and challenges related to both ice fog measurements and visibility parameterization will also be presented.

The optimal design of UAV wing structure

Science.gov (United States)

Długosz, Adam; Klimek, Wiktor

2018-01-01

The paper presents an optimal design of UAV wing, made of composite materials. The aim of the optimization is to improve strength and stiffness together with reduction of the weight of the structure. Three different types of functionals, which depend on stress, stiffness and the total mass are defined. The paper presents an application of the in-house implementation of the evolutionary multi-objective algorithm in optimization of the UAV wing structure. Values of the functionals are calculated on the basis of results obtained from numerical simulations. Numerical FEM model, consisting of different composite materials is created. Adequacy of the numerical model is verified by results obtained from the experiment, performed on a tensile testing machine. Examples of multi-objective optimization by means of Pareto-optimal set of solutions are presented.

On-Board Mining in the Sensor Web

Science.gov (United States)

Tanner, S.; Conover, H.; Graves, S.; Ramachandran, R.; Rushing, J.

2004-12-01

On-board data mining can contribute to many research and engineering applications, including natural hazard detection and prediction, intelligent sensor control, and the generation of customized data products for direct distribution to users. The ability to mine sensor data in real time can also be a critical component of autonomous operations, supporting deep space missions, unmanned aerial and ground-based vehicles (UAVs, UGVs), and a wide range of sensor meshes, webs and grids. On-board processing is expected to play a significant role in the next generation of NASA, Homeland Security, Department of Defense and civilian programs, providing for greater flexibility and versatility in measurements of physical systems. In addition, the use of UAV and UGV systems is increasing in military, emergency response and industrial applications. As research into the autonomy of these vehicles progresses, especially in fleet or web configurations, the applicability of on-board data mining is expected to increase significantly. Data mining in real time on board sensor platforms presents unique challenges. Most notably, the data to be mined is a continuous stream, rather than a fixed store such as a database. This means that the data mining algorithms must be modified to make only a single pass through the data. In addition, the on-board environment requires real time processing with limited computing resources, thus the algorithms must use fixed and relatively small amounts of processing time and memory. The University of Alabama in Huntsville is developing an innovative processing framework for the on-board data and information environment. The Environment for On-Board Processing (EVE) and the Adaptive On-board Data Processing (AODP) projects serve as proofs-of-concept of advanced information systems for remote sensing platforms. The EVE real-time processing infrastructure will upload, schedule and control the execution of processing plans on board remote sensors. These plans

a Mobile Multi-Sensor Platform for Building Reconstruction Integrating Terrestrial and Autonomous Uav-Based Close Range Data Acquisition

Science.gov (United States)

Cefalu, A.; Haala, N.; Schmohl, S.; Neumann, I.; Genz, T.

2017-08-01

Photogrammetric data capture of complex 3D objects using UAV imagery has become commonplace. Software tools based on algorithms like Structure-from-Motion and multi-view stereo image matching enable the fully automatic generation of densely meshed 3D point clouds. In contrast, the planning of a suitable image network usually requires considerable effort of a human expert, since this step directly influences the precision and completeness of the resulting point cloud. Planning of suitable camera stations can be rather complex, in particular for objects like buildings, bridges and monuments, which frequently feature strong depth variations to be acquired by high resolution images at a short distance. Within the paper, we present an automatic flight mission planning tool, which generates flight lines while aiming at camera configurations, which maintain a roughly constant object distance, provide sufficient image overlap and avoid unnecessary stations. Planning is based on a coarse Digital Surface Model and an approximate building outline. As a proof of concept, we use the tool within our research project MoVEQuaD, which aims at the reconstruction of building geometry at sub-centimetre accuracy.

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

Science.gov (United States)

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

2018-03-01

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

ANALYSIS OF COMBINED UAV-BASED RGB AND THERMAL REMOTE SENSING DATA: A NEW APPROACH TO CROWD MONITORING

Directory of Open Access Journals (Sweden)

S. Schulte

2017-08-01

Full Text Available Collecting vast amount of data does not solely help to fulfil information needs related to crowd monitoring, it is rather important to collect data that is suitable to meet specific information requirements. In order to address this issue, a prototype is developed to facilitate the combination of UAV-based RGB and thermal remote sensing datasets. In an experimental approach, image sensors were mounted on a remotely piloted aircraft and captured two video datasets over a crowd. A group of volunteers performed diverse movements that depict real world scenarios. The prototype is deriving the movement on the ground and is programmed in MATLAB. This novel detection approach using combined data is afterwards evaluated against detection algorithms that only use a single data source. Our tests show that the combination of RGB and thermal remote sensing data is beneficial for the field of crowd monitoring regarding the detection of crowd movement.

High-Fidelity Computational Aerodynamics of the Elytron 4S UAV

Science.gov (United States)

Ventura Diaz, Patricia; Yoon, Seokkwan; Theodore, Colin R.

2018-01-01

High-fidelity Computational Fluid Dynamics (CFD) have been carried out for the Elytron 4S Unmanned Aerial Vehicle (UAV), also known as the converticopter "proto12". It is the scaled wind tunnel model of the Elytron 4S, an Urban Air Mobility (UAM) concept, a tilt-wing, box-wing rotorcraft capable of Vertical Take-Off and Landing (VTOL). The three-dimensional unsteady Navier-Stokes equations are solved on overset grids employing high-order accurate schemes, dual-time stepping, and a hybrid turbulence model using NASA's CFD code OVERFLOW. The Elytron 4S UAV has been simulated in airplane mode and in helicopter mode.

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.

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.

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

Science.gov (United States)

Jean Liénard; Andre Vogs; Demetrios Gatziolis; Nikolay Strigul

2016-01-01

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

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.

THE ACCURACY OF AUTOMATIC PHOTOGRAMMETRIC TECHNIQUES ON ULTRA-LIGHT UAV IMAGERY

Directory of Open Access Journals (Sweden)

O. Küng

2012-09-01

Full Text Available This paper presents an affordable, fully automated and accurate mapping solutions based on ultra-light UAV imagery. Several datasets are analysed and their accuracy is estimated. We show that the accuracy highly depends on the ground resolution (flying height of the input imagery. When chosen appropriately this mapping solution can compete with traditional mapping solutions that capture fewer high-resolution images from airplanes and that rely on highly accurate orientation and positioning sensors on board. Due to the careful integration with recent computer vision techniques, the post processing is robust and fully automatic and can deal with inaccurate position and orientation information which are typically problematic with traditional techniques.

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

Science.gov (United States)

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

2017-09-26

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

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

The New Evolution for SIA Rotorcraft UAV Project

Directory of Open Access Journals (Sweden)

Juntong Qi

2010-01-01

Full Text Available This paper describes recent research on the design, implement, and testing of a new small-scaled rotorcraft Unmanned Aerial Vehicle (RUAV system—ServoHeli-40. A turbine-powered UAV weighted less than 15 kg was designed, and its major components were tested at the Shenyang Institute of Automation, Chinese Academy of Sciences in Shenyang, China. The aircraft was designed to reach a top speed of more than 20 mps, flying a distance of more than 10 kilometers, and it is going to be used as a test-bed for experimentally evaluating advanced control methodologies dedicated on improving the maneuverability, reliability, as well as autonomy of RUAV. Sensors and controller are all onboard. The full system has been tested successfully in the autonomous mode using the multichannel active modeling controller. The results show that in a real windy environment the rotorcraft UAV can follow the trajectory which was assigned by the ground control station exactly, and the new control method is obviously more effective than the one in the past year's research.

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

Directory of Open Access Journals (Sweden)

H. Moon

2016-06-01

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

UAV Communication Management and Coordination for Multitarget Tracking

Science.gov (United States)

2009-02-26

6.3 Weighted Trace Penalty 16 6.4 Results with WTP for ECTG 17 7 Multiple UAV Case 20 7.1 Extension of WTP 20 7.2 Coordinated sensor motion...growth by a weighted trace penalty ( WTP ) term, which is a product of the current covariancc trace and the minimum distance to observability (MDO) for a...Specifically, the terminal cost or ECTG term using the WTP has the form J(b) = JWTP(b) := iD(s, e) Tfc P\\ (6.1) where 7 is a positive constant, i is the

Assessing the consistency of UAV-derived point clouds and images acquired at different altitudes

Science.gov (United States)

Ozcan, O.

2016-12-01

Unmanned Aerial Vehicles (UAVs) offer several advantages in terms of cost and image resolution compared to terrestrial photogrammetry and satellite remote sensing system. Nowadays, UAVs that bridge the gap between the satellite scale and field scale applications were initiated to be used in various application areas to acquire hyperspatial and high temporal resolution imageries due to working capacity and acquiring in a short span of time with regard to conventional photogrammetry methods. UAVs have been used for various fields such as for the creation of 3-D earth models, production of high resolution orthophotos, network planning, field monitoring and agricultural lands as well. Thus, geometric accuracy of orthophotos and volumetric accuracy of point clouds are of capital importance for land surveying applications. Correspondingly, Structure from Motion (SfM) photogrammetry, which is frequently used in conjunction with UAV, recently appeared in environmental sciences as an impressive tool allowing for the creation of 3-D models from unstructured imagery. In this study, it was aimed to reveal the spatial accuracy of the images acquired from integrated digital camera and the volumetric accuracy of Digital Surface Models (DSMs) which were derived from UAV flight plans at different altitudes using SfM methodology. Low-altitude multispectral overlapping aerial photography was collected at the altitudes of 30 to 100 meters and georeferenced with RTK-GPS ground control points. These altitudes allow hyperspatial imagery with the resolutions of 1-5 cm depending upon the sensor being used. Preliminary results revealed that the vertical comparison of UAV-derived point clouds with respect to GPS measurements pointed out an average distance at cm-level. Larger values are found in areas where instantaneous changes in surface are present.

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

Direct Georeferencing of Uav Data Based on Simple Building Structures

Science.gov (United States)

Tampubolon, W.; Reinhardt, W.

2016-06-01

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

DIRECT GEOREFERENCING OF UAV DATA BASED ON SIMPLE BUILDING STRUCTURES

Directory of Open Access Journals (Sweden)

W. Tampubolon

2016-06-01

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

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.

Visual Servoing for an Autonomous Hexarotor Using a Neural Network Based PID Controller

Science.gov (United States)

Lopez-Franco, Carlos; Alanis, Alma Y.; Arana-Daniel, Nancy; Villaseñor, Carlos

2017-01-01

In recent years, unmanned aerial vehicles (UAVs) have gained significant attention. However, we face two major drawbacks when working with UAVs: high nonlinearities and unknown position in 3D space since it is not provided with on-board sensors that can measure its position with respect to a global coordinate system. In this paper, we present a real-time implementation of a servo control, integrating vision sensors, with a neural proportional integral derivative (PID), in order to develop an hexarotor image based visual servo control (IBVS) that knows the position of the robot by using a velocity vector as a reference to control the hexarotor position. This integration requires a tight coordination between control algorithms, models of the system to be controlled, sensors, hardware and software platforms and well-defined interfaces, to allow the real-time implementation, as well as the design of different processing stages with their respective communication architecture. All of these issues and others provoke the idea that real-time implementations can be considered as a difficult task. For the purpose of showing the effectiveness of the sensor integration and control algorithm to address these issues on a high nonlinear system with noisy sensors as cameras, experiments were performed on the Asctec Firefly on-board computer, including both simulation and experimenta results. PMID:28805689

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...

On decentralized adaptive full-order sliding mode control of multiple UAVs.

Science.gov (United States)

Xiang, Xianbo; Liu, Chao; Su, Housheng; Zhang, Qin

2017-11-01

In this study, a novel decentralized adaptive full-order sliding mode control framework is proposed for the robust synchronized formation motion of multiple unmanned aerial vehicles (UAVs) subject to system uncertainty. First, a full-order sliding mode surface in a decentralized manner is designed to incorporate both the individual position tracking error and the synchronized formation error while the UAV group is engaged in building a certain desired geometric pattern in three dimensional space. Second, a decentralized virtual plant controller is constructed which allows the embedded low-pass filter to attain the chattering free property of the sliding mode controller. In addition, robust adaptive technique is integrated in the decentralized chattering free sliding control design in order to handle unknown bounded uncertainties, without requirements for assuming a priori knowledge of bounds on the system uncertainties as stated in conventional chattering free control methods. Subsequently, system robustness as well as stability of the decentralized full-order sliding mode control of multiple UAVs is synthesized. Numerical simulation results illustrate the effectiveness of the proposed control framework to achieve robust 3D formation flight of the multi-UAV system. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

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.

LUNA: low-flying UAV-based forest monitoring system

Science.gov (United States)

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

2015-04-01

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

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.

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.

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.

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

Directory of Open Access Journals (Sweden)

Guorong Cai

2018-02-01

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

Vision Based Displacement Detection for Stabilized UAV Control on Cloud Server

Directory of Open Access Journals (Sweden)

Hyeok-June Jeong

2016-01-01

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

Band registration of tuneable frame format hyperspectral UAV imagers in complex scenes

Science.gov (United States)

Honkavaara, Eija; Rosnell, Tomi; Oliveira, Raquel; Tommaselli, Antonio

2017-12-01

A recent revolution in miniaturised sensor technology has provided markets with novel hyperspectral imagers operating in the frame format principle. In the case of unmanned aerial vehicle (UAV) based remote sensing, the frame format technology is highly attractive in comparison to the commonly utilised pushbroom scanning technology, because it offers better stability and the possibility to capture stereoscopic data sets, bringing an opportunity for 3D hyperspectral object reconstruction. Tuneable filters are one of the approaches for capturing multi- or hyperspectral frame images. The individual bands are not aligned when operating a sensor based on tuneable filters from a mobile platform, such as UAV, because the full spectrum recording is carried out in the time-sequential principle. The objective of this investigation was to study the aspects of band registration of an imager based on tuneable filters and to develop a rigorous and efficient approach for band registration in complex 3D scenes, such as forests. The method first determines the orientations of selected reference bands and reconstructs the 3D scene using structure-from-motion and dense image matching technologies. The bands, without orientation, are then matched to the oriented bands accounting the 3D scene to provide exterior orientations, and afterwards, hyperspectral orthomosaics, or hyperspectral point clouds, are calculated. The uncertainty aspects of the novel approach were studied. An empirical assessment was carried out in a forested environment using hyperspectral images captured with a hyperspectral 2D frame format camera, based on a tuneable Fabry-Pérot interferometer (FPI) on board a multicopter and supported by a high spatial resolution consumer colour camera. A theoretical assessment showed that the method was capable of providing band registration accuracy better than 0.5-pixel size. The empirical assessment proved the performance and showed that, with the novel method, most parts of

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.

Application Of Reinforcement Learning In Heading Control Of A Fixed Wing UAV Using X-Plane Platform

Directory of Open Access Journals (Sweden)

Kimathi

2017-02-01

Full Text Available Heading control of an Unmanned Aerial Vehicle UAV is a vital operation of an autopilot system. It is executed by employing a design of control algorithms that control its direction and navigation. Most commonly available autopilots exploit Proportional-Integral-Derivative PID based heading controllers. In this paper we propose an online adaptive reinforcement learning heading controller. The autopilot heading controller will be designed in MatlabSimulink for controlling a UAV in X-Plane test platform. Through this platform the performance of the controller is shown using real time simulations. The performance of this controller is compared to that of a PID controller. The results show that the proposed method performs better than a well tuned PID controller.

Unmanned air vehicle (UAV) ultra-persitence research

Energy Technology Data Exchange (ETDEWEB)

Dron, S. B.

2012-03-01

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

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

Directory of Open Access Journals (Sweden)

Shao-lei Zhou

2016-01-01

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

A carbon nanotube-based pressure sensor

International Nuclear Information System (INIS)

Karimov, Kh S; Saleem, M; Khan, Adam; Qasuria, T A; Mateen, A; Karieva, Z M

2011-01-01

In this study, a carbon nanotube (CNT)-based Al/CNT/Al pressure sensor was designed, fabricated and investigated. The sensor was fabricated by depositing CNTs on an adhesive elastic polymer tape and placing this in an elastic casing. The diameter of multiwalled nanotubes varied between 10 and 30 nm. The nominal thickness of the CNT layers in the sensors was in the range ∼300-430 μm. The inter-electrode distance (length) and the width of the surface-type sensors were in the ranges 4-6 and 3-4 mm, respectively. The dc resistance of the sensors decreased 3-4 times as the pressure was increased up to 17 kN m -2 . The resistance-pressure relationships were simulated.

Modeling Multioperator Multi-UAV Operator Attention Allocation Problem Based on Maximizing the Global Reward

Directory of Open Access Journals (Sweden)

Yuhang Wu

2016-01-01

Full Text Available This paper focuses on the attention allocation problem (AAP in modeling multioperator multi-UAV (MOMU, with the operator model and task properties taken into consideration. The model of MOMU operator AAP based on maximizing the global reward is established and used to allocate tasks to all operators as well as set work time and rest time to each task simultaneously for operators. The proposed model is validated in Matlab simulation environment, using the immune algorithm and dynamic programming algorithm to evaluate the performance of the model in terms of the reward value with regard to the work time, rest time, and task allocation. The result shows that the total reward of the proposed model is larger than the one obtained from previously published methods using local maximization and the total reward of our method has an exponent-like relation with the task arrival rate. The proposed model can improve the operators’ task processing efficiency in the MOMU command and control scenarios.

An Energy Oriented Model and Simulator for Wireless Sensor etworks

African Journals Online (AJOL)

Nafiisah

Wireless Sensor Network, Energy Modeling, Simulation, Energy. Efficiency ..... xMBCR: This scheme is based on the MBCR strategy, but improves the battery ... Moreover WSNs require large scale deployment (smart dusts) in remote and.

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