Distributed subterranean exploration and mapping with teams of UAVs

NASA Astrophysics Data System (ADS)

Rogers, John G.; Sherrill, Ryan E.; Schang, Arthur; Meadows, Shava L.; Cox, Eric P.; Byrne, Brendan; Baran, David G.; Curtis, J. Willard; Brink, Kevin M.

2017-05-01

Teams of small autonomous UAVs can be used to map and explore unknown environments which are inaccessible to teams of human operators in humanitarian assistance and disaster relief efforts (HA/DR). In addition to HA/DR applications, teams of small autonomous UAVs can enhance Warfighter capabilities and provide operational stand-off for military operations such as cordon and search, counter-WMD, and other intelligence, surveillance, and reconnaissance (ISR) operations. This paper will present a hardware platform and software architecture to enable distributed teams of heterogeneous UAVs to navigate, explore, and coordinate their activities to accomplish a search task in a previously unknown environment.

Mathematical model of unmanned aerial vehicle used for endurance autonomous monitoring

NASA Astrophysics Data System (ADS)

Chelaru, Teodor-Viorel; Chelaru, Adrian

2014-12-01

The paper purpose is to present some aspects regarding the control system of unmanned aerial vehicle - UAV, used to local observations, surveillance and monitoring interest area. The calculus methodology allows a numerical simulation of UAV evolution in bad atmospheric conditions by using nonlinear model, as well as a linear one for obtaining guidance command. The UAV model which will be presented has six DOF (degrees of freedom), and autonomous control system. This theoretical development allows us to build stability matrix, command matrix and control matrix and finally to analyse the stability of autonomous UAV flight. A robust guidance system, based on uncoupled state will be evaluated for different fly conditions and the results will be presented. The flight parameters and guidance will be analysed.

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

NASA Astrophysics Data System (ADS)

Samant, Ashwin; Chang, K. C.

2010-04-01

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

Towards Autonomous Modular UAV Missions: The Detection, Geo-Location and Landing Paradigm

PubMed Central

Kyristsis, Sarantis; Antonopoulos, Angelos; Chanialakis, Theofilos; Stefanakis, Emmanouel; Linardos, Christos; Tripolitsiotis, Achilles; Partsinevelos, Panagiotis

2016-01-01

Nowadays, various unmanned aerial vehicle (UAV) applications become increasingly demanding since they require real-time, autonomous and intelligent functions. Towards this end, in the present study, a fully autonomous UAV scenario is implemented, including the tasks of area scanning, target recognition, geo-location, monitoring, following and finally landing on a high speed moving platform. The underlying methodology includes AprilTag target identification through Graphics Processing Unit (GPU) parallelized processing, image processing and several optimized locations and approach algorithms employing gimbal movement, Global Navigation Satellite System (GNSS) readings and UAV navigation. For the experimentation, a commercial and a custom made quad-copter prototype were used, portraying a high and a low-computational embedded platform alternative. Among the successful targeting and follow procedures, it is shown that the landing approach can be successfully performed even under high platform speeds. PMID:27827883

Towards Autonomous Modular UAV Missions: The Detection, Geo-Location and Landing Paradigm.

PubMed

Kyristsis, Sarantis; Antonopoulos, Angelos; Chanialakis, Theofilos; Stefanakis, Emmanouel; Linardos, Christos; Tripolitsiotis, Achilles; Partsinevelos, Panagiotis

2016-11-03

Nowadays, various unmanned aerial vehicle (UAV) applications become increasingly demanding since they require real-time, autonomous and intelligent functions. Towards this end, in the present study, a fully autonomous UAV scenario is implemented, including the tasks of area scanning, target recognition, geo-location, monitoring, following and finally landing on a high speed moving platform. The underlying methodology includes AprilTag target identification through Graphics Processing Unit (GPU) parallelized processing, image processing and several optimized locations and approach algorithms employing gimbal movement, Global Navigation Satellite System (GNSS) readings and UAV navigation. For the experimentation, a commercial and a custom made quad-copter prototype were used, portraying a high and a low-computational embedded platform alternative. Among the successful targeting and follow procedures, it is shown that the landing approach can be successfully performed even under high platform speeds.

Path Calculation and Packet Translation for UAV Surveillance in Support of Wireless Sensor Networks

DTIC Science & Technology

2006-09-01

AND PACKET TRANSLATION FOR UAV SURVEILLANCE IN SUPPORT OF WIRELESS SENSOR NETWORKS by Stephen Schall September 2006 Thesis Advisor...Calculation and Packet Translation for UAV Surveillance in Support of Wireless Sensor Networks 6. AUTHOR(S) Stephen Schall 5. FUNDING NUMBERS 7...200 words) Wireless Sensor Networks (WSNs) are a relatively new technology with many potential applications, including military and

A Modular, Reconfigurable Surveillance UAV Architecture

DTIC Science & Technology

2003-09-02

Una Società Galileo Avionica A Modular, Reconfigurable Surveillance UAV Architecture METEOR, Finmeccanica Group Zona Industriale di Soleschiano Via...ES) METEOR, Finmeccanica Group Zona Industriale di Soleschiano Via Mario Stoppani 21 34077 Ronchi dei Legionari (GO) ITALY 8. PERFORMING...PMSFMS RS1Backup FMS NSU Payload Control Actuators Router Router RS2 Recovery Devices Una Società Galileo Avionica • Daylight TV Camera • IR Sensor • HR

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

NASA Astrophysics Data System (ADS)

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.

An Autonomous Autopilot Control System Design for Small-Scale UAVs

NASA Technical Reports Server (NTRS)

Ippolito, Corey; Pai, Ganeshmadhav J.; Denney, Ewen W.

2012-01-01

This paper describes the design and implementation of a fully autonomous and programmable autopilot system for small scale autonomous unmanned aerial vehicle (UAV) aircraft. This system was implemented in Reflection and has flown on the Exploration Aerial Vehicle (EAV) platform at NASA Ames Research Center, currently only as a safety backup for an experimental autopilot. The EAV and ground station are built on a component-based architecture called the Reflection Architecture. The Reflection Architecture is a prototype for a real-time embedded plug-and-play avionics system architecture which provides a transport layer for real-time communications between hardware and software components, allowing each component to focus solely on its implementation. The autopilot module described here, although developed in Reflection, contains no design elements dependent on this architecture.

Autonomous Control of a Quadrotor UAV Using Fuzzy Logic

NASA Astrophysics Data System (ADS)

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 Cloud-Based UAV Monitoring and Management System

PubMed Central

Itkin, Mason; Kim, Mihui; Park, Younghee

2016-01-01

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

Development of Cloud-Based UAV Monitoring and Management System.

PubMed

Itkin, Mason; Kim, Mihui; Park, Younghee

2016-11-15

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

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

PubMed

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.

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

PubMed Central

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

2017-01-01

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. PMID:28867775

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

NASA Astrophysics Data System (ADS)

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.

Development of a UAV-based Global Ozone Lidar Demonstrator (GOLD)

NASA Astrophysics Data System (ADS)

Browell, E. V.; Deyoung, R. J.; Hair, J. W.; Ismail, S.; McGee, T.; Hardesty, R. M.; Brewer, W. A.; McDermid, I. S.

2006-12-01

Global ozone measurements are needed across the troposphere with high vertical resolution to enable comprehensive studies of continental and intercontinental atmospheric chemistry and dynamics, which are affected by diverse natural and human-induced processes. The development of a unattended aerial vehicle (UAV) based Global Ozone Lidar Demonstrator (GOLD) is an important step in enabling a space-based ozone and aerosol lidar and for conducting unique UAV-based large-scale atmospheric investigations. The GOLD system will incorporate the most advanced technology developed under the NASA Laser Risk Reduction Program (LRRP) and the Small Business Innovative Research (SBIR) program to produce a compact, autonomously operating ozone and aerosol Differential Absorption Lidar (DIAL) system for a UAV platform. This system will leverage advanced Nd:YAG and optical parametric oscillator (OPO) laser technologies being developed by ITT Industries under the LRRP and the autonomously operating ozone DIAL system being developed by Science and Engineering Services Inc. (SESI) under an SBIR Phase-3 contract. Laser components from ITT will be integrated into the SESI DIAL system, and the resulting GOLD system will be flight tested on a NASA UAV. The development of the GOLD system was initiated as part of the NASA Instrument Incubator Program in December 2005, and great progress has been made towards completing major GOLD subsystems. ITT has begun construction of the high-power Nd:YAG pump laser and the ultraviolet OPO for generating the ozone DIAL wavelengths of 290 and 300 nm and the aerosol visible wavelength at 532 nm. SESI is completing the Phase-3 SBIR contract for the delivery and demonstration of the ozone DIAL receiver and data system, and NOAA is completing detector evaluations for use in the GOLD system. Welch Mechanical is examining system designs for integrating GOLD into the external pod that will be hung under the new IKANA (Predator-B) UAV that NASA Dryden is

A UAV System for Observing Volcanoes and Natural Hazards

NASA Astrophysics Data System (ADS)

Saggiani, G.; Persiani, F.; Ceruti, A.; Tortora, P.; Troiani, E.; Giuletti, F.; Amici, S.; Buongiorno, M.; Distefano, G.; Bentini, G.; Bianconi, M.; Cerutti, A.; Nubile, A.; Sugliani, S.; Chiarini, M.; Pennestri, G.; Petrini, S.; Pieri, D.

2007-12-01

Fixed or rotary wing manned aircraft are currently the most commonly used platforms for airborne reconnaissance in response to natural hazards, such as volcanic eruptions, oil spills, wild fires, earthquakes. Such flights are very often undertaken in hazardous flying conditions (e.g., turbulence, downdrafts, reduced visibility, close proximity to dangerous terrain) and can be expensive. To mitigate these two fundamental issues-- safety and cost--we are exploring the use of small (less than 100kg), relatively inexpensive, but effective, unmanned aerial vehicles (UAVs) for this purpose. As an operational test, in 2004 we flew a small autonomous UAV in the airspace above and around Stromboli Volcano. Based in part on this experience, we are adapting the RAVEN UAV system for such natural hazard surveillance missions. RAVEN has a 50km range, with a 3.5m wingspan, main fuselage length of 4.60m, and maximum weight of 56kg. It has autonomous flight capability and a ground control Station for the mission planning and control. It will carry a variety of imaging devices, including a visible camera, and an IR camera. It will also carry an experimental Fourier micro-interferometer based on MOEMS technology, (developed by IMM Institute of CNR), to detect atmospheric trace gases. Such flexible, capable, and easy-to-deploy UAV systems may significantly shorten the time necessary to characterize the nature and scale of the natural hazard threats if used from the outset of, and systematically during, natural hazard events. When appropriately utilized, such UAVs can provide a powerful new hazard mitigation and documentation tool for civil protection hazard responders. This research was carried out under the auspices of the Italian government, and, in part, under contract to NASA at the Jet Propulsion Laboratory.

Validating a UAV artificial intelligence control system using an autonomous test case generator

NASA Astrophysics Data System (ADS)

Straub, Jeremy; Huber, Justin

2013-05-01

The validation of safety-critical applications, such as autonomous UAV operations in an environment which may include human actors, is an ill posed problem. To confidence in the autonomous control technology, numerous scenarios must be considered. This paper expands upon previous work, related to autonomous testing of robotic control algorithms in a two dimensional plane, to evaluate the suitability of similar techniques for validating artificial intelligence control in three dimensions, where a minimum level of airspeed must be maintained. The results of human-conducted testing are compared to this automated testing, in terms of error detection, speed and testing cost.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roelof Versteeg; Mark McKay; Matt Anderson

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 geophysicalmore » 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

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

DTIC Science & Technology

2015-05-18

both cases, the UAVs encountered icing conditions inevitably losing control and crashing into the water.xxiii Land-based UAVs as well as manned...www2.l- 3com.com/csw/ProductsAndServices/ DataSheets /VORTEX Sales-Sheet WEB.pdf. xxviii L3 Communication Systems, “ROVER 5 Handheld,” accessed on...May 2, 2015, http://www2.l-3com.com/csw/ProductsAndServices/ DataSheets /ROVER-5_Sales- Sheet_WEB.pdf. xxix National Research Council, Autonomous

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

NASA Astrophysics Data System (ADS)

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.

Scalable autonomous operations of unmanned assets

NASA Astrophysics Data System (ADS)

Jung, Sunghun

Although there have been great theoretical advances in the region of Unmanned Aerial Vehicle (UAV) autonomy, applications of those theories into real world are still hesitated due to unexpected disturbances. Most of UAVs which are currently used are mainly, strictly speaking, Remotely Piloted Vehicles (RPA) since most works related with the flight control, sensor data analysis, and decision makings are done by human operators. To increase the degree of autonomy, many researches are focused on developing Unmanned Autonomous Aerial Vehicle (UAAV) which can takeoff, fly to the interested area by avoiding unexpected obstacles, perform various missions with decision makings, come back to the base station, and land on by itself without any human operators. To improve the performance of UAVs, the accuracies of position and orientation sensors are enhanced by integrating a Unmanned Ground Vehicle (UGV) or a solar compass to a UAV; Position sensor accuracy of a GPS sensor on a UAV is improved by referencing the position of a UGV which is calculated by using three GPS sensors and Weighted Centroid Localization (WCL) method; Orientation sensor accuracy is improved as well by using Three Pixel Theorem (TPT) and integrating a solar compass which composed of nine light sensors to a magnetic compass. Also, improved health management of a UAV is fulfilled by developing a wireless autonomous charging station which uses four pairs of transmitter and receiver magnetic loops with four robotic arms. For the software aspect, I also analyze the error propagation of the proposed mission planning hierarchy to achieve the safest size of the buffer zone. In addition, among seven future research areas regarding UAV, this paper mainly focuses on developing algorithms of path planning, trajectory generation, and cooperative tactics for the operations of multiple UAVs using GA based multiple Traveling Salesman Problem (mTSP) which is solved by dividing into m number of Traveling Salesman

Development of a bio-inspired UAV perching system

NASA Astrophysics Data System (ADS)

Xie, Pu

autonomous perching system, the following objectives were included for this project. The statics model was derived through both quasi-static and analytical method. The grasping stable condition and grasping target of the mechanical gripper were studied through the static analysis. Furthermore, the contact behavior between each foot and the perched object was modeled and evaluated on SimMechanics based on the contact force model derived through virtual principle. The kinematics modeling of UAV perching system was governed with Euler angles and quaternions. Also the propulsion model of the brushless motors was introduced and calibrated. In addition, the flight dynamics model of the UAV system was developed for simulation-based analysis prior to developing a hardware prototype and flight experiment. A special inertial measurement unit (IMU) was designed which has the capability of indirectly calculating the angular acceleration from the angular velocity and the linear acceleration readings. Moreover, a commercial-of-the-shelf (COTS) autopilot-APM 2.6 was selected for the autonomous flight control of the quadrotor. The APM 2.6 is a complete open source autopilot system, which allows the user to turn any fixed, rotary wing or multi-rotor vehicle into a fully autonomous vehicle and capable of performing programmed GPS missions with pre-programed waypoints. In addition, algorithms for inverted pendulum control and autonomous perching control was introduced. The proportion-integrate-differential (PID) controller was used for the simplified UAV perching with inverted pendulum model for horizontal balance. The performance of the controller was verified through both simulation and experiment. In addition, for the purpose of achieving the autonomous perching, guidance and control algorithms were developed the UAV perching system. For guidance, the desired flight trajectory was developed based on a bio-behavioral tau theory which was established from studying the natural motion patterns

Cybersecurity for aerospace autonomous systems

NASA Astrophysics Data System (ADS)

Straub, Jeremy

2015-05-01

High profile breaches have occurred across numerous information systems. One area where attacks are particularly problematic is autonomous control systems. This paper considers the aerospace information system, focusing on elements that interact with autonomous control systems (e.g., onboard UAVs). It discusses the trust placed in the autonomous systems and supporting systems (e.g., navigational aids) and how this trust can be validated. Approaches to remotely detect the UAV compromise, without relying on the onboard software (on a potentially compromised system) as part of the process are discussed. How different levels of autonomy (task-based, goal-based, mission-based) impact this remote characterization is considered.

Distributed UAV-Swarm Real-Time Geomatic Data Collection Under Dynamically Changing Resolution Requirements

NASA Astrophysics Data System (ADS)

Almeida, Miguel; Hildmann, Hanno; Solmaz, Gürkan

2017-08-01

Unmanned Aerial Vehicles (UAVs) have been used for reconnaissance and surveillance missions as far back as the Vietnam War, but with the recent rapid increase in autonomy, precision and performance capabilities - and due to the massive reduction in cost and size - UAVs have become pervasive products, available and affordable for the general public. The use cases for UAVs are in the areas of disaster recovery, environmental mapping & protection and increasingly also as extended eyes and ears of civil security forces such as fire-fighters and emergency response units. In this paper we present a swarm algorithm that enables a fleet of autonomous UAVs to collectively perform sensing tasks related to environmental and rescue operations and to dynamically adapt to e.g. changing resolution requirements. We discuss the hardware used to build our own drones and the settings under which we validate the proposed approach.

Nonlinear Landing Control for Quadrotor UAVs

NASA Astrophysics Data System (ADS)

Voos, Holger

Quadrotor UAVs are one of the most preferred type of small unmanned aerial vehicles because of the very simple mechanical construction and propulsion principle. However, the nonlinear dynamic behavior requires a more advanced stabilizing control and guidance of these vehicles. In addition, the small payload reduces the amount of batteries that can be carried and thus also limits the operating range of the UAV. One possible solution for a range extension is the application of a mobile base station for recharging purpose even during operation. However, landing on a moving base station requires autonomous tracking and landing control of the UAV. In this paper, a nonlinear autopilot for quadrotor UAVs is extended with a tracking and landing controller to fulfill the required task.

Using Public Network Infrastructures for UAV Remote Sensing in Civilian Security Operations

DTIC Science & Technology

2011-03-01

leveraging public wireless communication networks for UAV-based sensor networks with respect to existing constraints and user requirements...Detection with an Autonomous Micro UAV Mesh Network . In the near future police departments, fire brigades and other homeland security ...UAV-based sensor networks with respect to existing constraints and user requirements. 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17. LIMITATION

Autonomous Soaring Flight Results

NASA Technical Reports Server (NTRS)

Allen, Michael J.

2006-01-01

A viewgraph presentation on autonomous soaring flight results for Unmanned Aerial Vehicles (UAV)'s is shown. The topics include: 1) Background; 2) Thermal Soaring Flight Results; 3) Autonomous Dolphin Soaring; and 4) Future Plans.

Real-time people and vehicle detection from UAV imagery

NASA Astrophysics Data System (ADS)

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

2011-01-01

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

Research on detection method of UAV obstruction based on binocular vision

NASA Astrophysics Data System (ADS)

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.

UAV Research at NASA Langley: Towards Safe, Reliable, and Autonomous Operations

NASA Technical Reports Server (NTRS)

Davila, Carlos G.

2016-01-01

Unmanned Aerial Vehicles (UAV) are fundamental components in several aspects of research at NASA Langley, such as flight dynamics, mission-driven airframe design, airspace integration demonstrations, atmospheric science projects, and more. In particular, NASA Langley Research Center (Langley) is using UAVs to develop and demonstrate innovative capabilities that meet the autonomy and robotics challenges that are anticipated in science, space exploration, and aeronautics. These capabilities will enable new NASA missions such as asteroid rendezvous and retrieval (ARRM), Mars exploration, in-situ resource utilization (ISRU), pollution measurements in historically inaccessible areas, and the integration of UAVs into our everyday lives all missions of increasing complexity, distance, pace, and/or accessibility. Building on decades of NASA experience and success in the design, fabrication, and integration of robust and reliable automated systems for space and aeronautics, Langley Autonomy Incubator seeks to bridge the gap between automation and autonomy by enabling safe autonomous operations via onboard sensing and perception systems in both data-rich and data-deprived environments. The Autonomy Incubator is focused on the challenge of mobility and manipulation in dynamic and unstructured environments by integrating technologies such as computer vision, visual odometry, real-time mapping, path planning, object detection and avoidance, object classification, adaptive control, sensor fusion, machine learning, and natural human-machine teaming. These technologies are implemented in an architectural framework developed in-house for easy integration and interoperability of cutting-edge hardware and software.

Autonomous search and surveillance with small fixed wing aircraft

NASA Astrophysics Data System (ADS)

McGee, Timothy Garland

Small unmanned aerial vehicles (UAVs) have the potential to act as low cost tools in a variety of both civilian and military applications including traffic monitoring, border patrol, and search and rescue. While most current operational UAV systems require human operators, advances in autonomy will allow these systems to reach their full potential as sensor platforms. This dissertation specifically focuses on developing advanced control, path planning, search, and image processing techniques that allow small fixed wing aircraft to autonomously collect data. The problems explored were motivated by experience with the development and experimental flight testing of a fleet of small autonomous fixed wing aircraft. These issues, which have not been fully addressed in past work done on ground vehicles or autonomous helicopters, include the influence of wind and turning rate constraints, the non-negligible velocity of ground targets relative to the aircraft velocity, and limitations on sensor size and processing power on small vehicles. Several contributions for the autonomous operation of small fixed wing aircraft are presented. Several sliding surface controllers are designed which extend previous techniques to include variable sliding surface coefficients and the use of spatial vehicle dynamics. These advances eliminate potential singularities in the control laws to follow spatially defined paths and allow smooth transition between controllers. The optimal solution for the problem of path planning through an ordered set of points for an aircraft with a bounded turning rate in the presence of a constant wind is then discussed. Path planning strategies are also explored to guarantee that a searcher will travel within sensing distance of a mobile ground target. This work assumes only a maximum velocity of the target and is designed to succeed for any possible path of the target. Closed-loop approximations of both the path planning and search techniques, using the sliding

Autonomous Aeromagnetic Surveys Using a Fluxgate Magnetometer.

PubMed

Macharet, Douglas G; Perez-Imaz, Héctor I A; Rezeck, Paulo A F; Potje, Guilherme A; Benyosef, Luiz C C; Wiermann, André; Freitas, Gustavo M; Garcia, Luis G U; Campos, Mario F M

2016-12-17

Recent advances in the research of autonomous vehicles have showed a vast range of applications, such as exploration, surveillance and environmental monitoring. Considering the mining industry, it is possible to use such vehicles in the prospection of minerals of commercial interest beneath the ground. However, tasks such as geophysical surveys are highly dependent on specific sensors, which mostly are not designed to be used in these new range of autonomous vehicles. In this work, we propose a novel magnetic survey pipeline that aims to increase versatility, speed and robustness by using autonomous rotary-wing Unmanned Aerial Vehicles (UAVs). We also discuss the development of a state-of-the-art three-axis fluxgate, where our goal in this work was to refine and adjust the sensor topology and coupled electronics specifically for this type of vehicle and application. The sensor was built with two ring-cores using a specially developed stress-annealed CoFeSiB amorphous ribbon, in order to get sufficient resolution to detect concentrations of small ferrous minerals. Finally, we report on the results of experiments performed with a real UAV in an outdoor environment, showing the efficacy of the methodology in detecting an artificial ferrous anomaly.

DDDAMS-based Urban Surveillance and Crowd Control via UAVs and UGVs

DTIC Science & Technology

2015-12-04

for crowd dynamics modeling by incorporating multi-resolution data, where a grid-based method is used to model crowd motion with UAVs’ low -resolution...information and more computational intensive (and time-consuming). Given that the deployment of fidelity selection results in simulation faces computational... low fidelity information FOV y (A) DR x (A) DR y (A) Not detected high fidelity information Table 1: Parameters for UAV and UGV for their detection

A Camera-Based Target Detection and Positioning UAV System for Search and Rescue (SAR) Purposes

PubMed Central

Sun, Jingxuan; Li, Boyang; Jiang, Yifan; Wen, Chih-yung

2016-01-01

Wilderness search and rescue entails performing a wide-range of work in complex environments and large regions. Given the concerns inherent in large regions due to limited rescue distribution, unmanned aerial vehicle (UAV)-based frameworks are a promising platform for providing aerial imaging. In recent years, technological advances in areas such as micro-technology, sensors and navigation have influenced the various applications of UAVs. In this study, an all-in-one camera-based target detection and positioning system is developed and integrated into a fully autonomous fixed-wing UAV. The system presented in this paper is capable of on-board, real-time target identification, post-target identification and location and aerial image collection for further mapping applications. Its performance is examined using several simulated search and rescue missions, and the test results demonstrate its reliability and efficiency. PMID:27792156

A Camera-Based Target Detection and Positioning UAV System for Search and Rescue (SAR) Purposes.

PubMed

Sun, Jingxuan; Li, Boyang; Jiang, Yifan; Wen, Chih-Yung

2016-10-25

Wilderness search and rescue entails performing a wide-range of work in complex environments and large regions. Given the concerns inherent in large regions due to limited rescue distribution, unmanned aerial vehicle (UAV)-based frameworks are a promising platform for providing aerial imaging. In recent years, technological advances in areas such as micro-technology, sensors and navigation have influenced the various applications of UAVs. In this study, an all-in-one camera-based target detection and positioning system is developed and integrated into a fully autonomous fixed-wing UAV. The system presented in this paper is capable of on-board, real-time target identification, post-target identification and location and aerial image collection for further mapping applications. Its performance is examined using several simulated search and rescue missions, and the test results demonstrate its reliability and efficiency.

Automated UAV-based video exploitation using service oriented architecture framework

NASA Astrophysics Data System (ADS)

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.

Smart Cruise Control: UAV sensor operator intent estimation and its application

NASA Astrophysics Data System (ADS)

Cheng, Hui; Butler, Darren; Kumar, Rakesh

2006-05-01

Due to their long endurance, superior mobility and the low risk posed to the pilot and sensor operator, UAVs have become the preferred platform for persistent ISR missions. However, currently most UAV based ISR missions are conducted through manual operation. Event the simplest tasks, such as vehicle tracking, route reconnaissance and site monitoring, need the sensor operator's undivided attention and constant adjustment of the sensor control. The lack of autonomous behaviour greatly limits of the effectiveness and the capability of UAV-based ISR, especially the use of a large number of UAVs simultaneously. Although fully autonomous UAV based ISR system is desirable, it is still a distant dream due to the complexity and diversity of combat and ISR missions. In this paper, we propose a Smart Cruise Control system that can learn UAV sensor operator's intent and use it to complete tasks automatically, such as route reconnaissance and site monitoring. Using an operator attention model, the proposed system can estimate the operator's intent from how they control the sensor (e.g. camera) and the content of the imagery that is acquired. Therefore, for example, from initially manually controlling the UAV sensor to follow a road, the system can learn not only the preferred operation, "tracking", but also the road appearance, "what to track" in real-time. Then, the learnt models of both road and the desired operation can be used to complete the task automatically. We have demonstrated the Smart Cruise Control system using real UAV videos where roads need to be tracked and buildings need to be monitored.

Feasibility of Turing-Style Tests for Autonomous Aerial Vehicle "Intelligence"

NASA Technical Reports Server (NTRS)

Young, Larry A.

2007-01-01

A new approach is suggested to define and evaluate key metrics as to autonomous aerial vehicle performance. This approach entails the conceptual definition of a "Turing Test" for UAVs. Such a "UAV Turing test" would be conducted by means of mission simulations and/or tailored flight demonstrations of vehicles under the guidance of their autonomous system software. These autonomous vehicle mission simulations and flight demonstrations would also have to be benchmarked against missions "flown" with pilots/human-operators in the loop. In turn, scoring criteria for such testing could be based upon both quantitative mission success metrics (unique to each mission) and by turning to analog "handling quality" metrics similar to the well-known Cooper-Harper pilot ratings used for manned aircraft. Autonomous aerial vehicles would be considered to have successfully passed this "UAV Turing Test" if the aggregate mission success metrics and handling qualities for the autonomous aerial vehicle matched or exceeded the equivalent metrics for missions conducted with pilots/human-operators in the loop. Alternatively, an independent, knowledgeable observer could provide the "UAV Turing Test" ratings of whether a vehicle is autonomous or "piloted." This observer ideally would, in the more sophisticated mission simulations, also have the enhanced capability of being able to override the scripted mission scenario and instigate failure modes and change of flight profile/plans. If a majority of mission tasks are rated as "piloted" by the observer, when in reality the vehicle/simulation is fully- or semi- autonomously controlled, then the vehicle/simulation "passes" the "UAV Turing Test." In this regards, this second "UAV Turing Test" approach is more consistent with Turing s original "imitation game" proposal. The overall feasibility, and important considerations and limitations, of such an approach for judging/evaluating autonomous aerial vehicle "intelligence" will be discussed from a

Autonomous Aeromagnetic Surveys Using a Fluxgate Magnetometer

PubMed Central

Macharet, Douglas G.; Perez-Imaz, Héctor I. A.; Rezeck, Paulo A. F.; Potje, Guilherme A.; Benyosef, Luiz C. C.; Wiermann, André; Freitas, Gustavo M.; Garcia, Luis G. U.; Campos, Mario F. M.

2016-01-01

Recent advances in the research of autonomous vehicles have showed a vast range of applications, such as exploration, surveillance and environmental monitoring. Considering the mining industry, it is possible to use such vehicles in the prospection of minerals of commercial interest beneath the ground. However, tasks such as geophysical surveys are highly dependent on specific sensors, which mostly are not designed to be used in these new range of autonomous vehicles. In this work, we propose a novel magnetic survey pipeline that aims to increase versatility, speed and robustness by using autonomous rotary-wing Unmanned Aerial Vehicles (UAVs). We also discuss the development of a state-of-the-art three-axis fluxgate, where our goal in this work was to refine and adjust the sensor topology and coupled electronics specifically for this type of vehicle and application. The sensor was built with two ring-cores using a specially developed stress-annealed CoFeSiB amorphous ribbon, in order to get sufficient resolution to detect concentrations of small ferrous minerals. Finally, we report on the results of experiments performed with a real UAV in an outdoor environment, showing the efficacy of the methodology in detecting an artificial ferrous anomaly. PMID:27999307

A UAV-based gas sensing system for detecting fugitive methane emissions

NASA Astrophysics Data System (ADS)

Hugenholtz, C.; Barchyn, T.; Myshak, S.; Bauer, J.

2016-12-01

Methane is one of the most prevalent greenhouse gases emitted by human activities and is a major component of government-led initiatives to reduce GHG emissions in Canada, the USA, and elsewhere. In light of growing demand for measurements and verification of atmospheric methane concentration across the oil and gas supply chain, an autonomous airborne gas sensing system was developed that combines a small UAV and a lightweight gas monitor. This paper outlines the technology, analytics, and presents data from a case study to demonstrate the proof of concept. The UAV is a fixed-wing (2.2 m wingspan), battery-operated platform, with a flight endurance of 80-120 minutes. The gas sensor onboard the UAV is a tunable diode laser absorption spectrometer that uses an integrated transmitter/receiver unit and a remote, passive retro-reflector. The transmitter is attached to one of the winglets, while the other is coated with reflective material. The total weight of the UAV and gas sensor is 4.3 kg. During flight, the system operates autonomously, acquiring averages of raw measurements at 1 Hz, with a recorded resolution of 0.0455 ppm. The onboard measurement and control unit (MCU) for the gas sensor is integrated with the UAV autopilot in order to provide time-stamped and geotagged concentration measurements, and to provide real-time flight adjustments when concentration exceeds a pre-determined threshold. The data are retrieved from the MCU when the mission is complete. In order to demonstrate the proof of concept, we present results from a case study and outline opportunities for translating the measurements into decision making.

Swarming Unmanned Aerial Vehicles (UAVS): Extending Marine Aviation Ground Task Force Communications Using UAVS

DTIC Science & Technology

2015-03-02

balloons , large UAVs, and satellite communications are all employed to mitigate LOS and OTH communication on the battlefield. The Marine Corps’ fleets...Phang, N. S. (2006). Tethered operation of autonomous aerial vehicles to provide extended fields of view for autonomous ground vehicles (Master’s

Adaptive pattern for autonomous UAV guidance

NASA Astrophysics Data System (ADS)

Sung, Chen-Ko; Segor, Florian

2013-09-01

The research done at the Fraunhofer IOSB in Karlsruhe within the AMFIS project is focusing on a mobile system to support rescue forces in accidents or disasters. The system consists of a ground control station which has the capability to communicate with a large number of heterogeneous sensors and sensor carriers and provides several open interfaces to allow easy integration of additional sensors into the system. Within this research we focus mainly on UAV such as VTOL (Vertical takeoff and Landing) systems because of their ease of use and their high maneuverability. To increase the positioning capability of the UAV, different onboard processing chains of image exploitation for real time detection of patterns on the ground and the interfacing technology for controlling the UAV from the payload during flight were examined. The earlier proposed static ground pattern was extended by an adaptive component which admits an additional visual communication channel to the aircraft. For this purpose different components were conceived to transfer additive information using changeable patterns on the ground. The adaptive ground pattern and their application suitability had to be tested under external influence. Beside the adaptive ground pattern, the onboard process chains and the adaptations to the demands of changing patterns are introduced in this paper. The tracking of the guiding points, the UAV navigation and the conversion of the guiding point positions from the images to real world co-ordinates in video sequences, as well as use limits and the possibilities of an adaptable pattern are examined.

Development of a GPS/INS/MAG navigation system and waypoint navigator for a VTOL UAV

NASA Astrophysics Data System (ADS)

Meister, Oliver; Mönikes, Ralf; Wendel, Jan; Frietsch, Natalie; Schlaile, Christian; Trommer, Gert F.

2007-04-01

Unmanned aerial vehicles (UAV) can be used for versatile surveillance and reconnaissance missions. If a UAV is capable of flying automatically on a predefined path the range of possible applications is widened significantly. This paper addresses the development of the integrated GPS/INS/MAG navigation system and a waypoint navigator for a small vertical take-off and landing (VTOL) unmanned four-rotor helicopter with a take-off weight below 1 kg. The core of the navigation system consists of low cost inertial sensors which are continuously aided with GPS, magnetometer compass, and a barometric height information. Due to the fact, that the yaw angle becomes unobservable during hovering flight, the integration with a magnetic compass is mandatory. This integration must be robust with respect to errors caused by the terrestrial magnetic field deviation and interferences from surrounding electronic devices as well as ferrite metals. The described integration concept with a Kalman filter overcomes the problem that erroneous magnetic measurements yield to an attitude error in the roll and pitch axis. The algorithm provides long-term stable navigation information even during GPS outages which is mandatory for the flight control of the UAV. In the second part of the paper the guidance algorithms are discussed in detail. These algorithms allow the UAV to operate in a semi-autonomous mode position hold as well an complete autonomous waypoint mode. In the position hold mode the helicopter maintains its position regardless of wind disturbances which ease the pilot job during hold-and-stare missions. The autonomous waypoint navigator enable the flight outside the range of vision and beyond the range of the radio link. Flight test results of the implemented modes of operation are shown.

Maintaining Situation Awareness with Autonomous Airborne Observation Platforms

NASA Technical Reports Server (NTRS)

Freed, Michael; Fitzgerald, Will

2005-01-01

Unmanned Aerial Vehicles (UAVs) offer tremendous potential as intelligence, surveillance and reconnaissance (ISR) platforms for early detection of security threats and for acquisition and maintenance of situation awareness in crisis conditions. However, using their capabilities effectively requires addressing a range of practical and theoretical problems. The paper will describe progress by the "Autonomous Rotorcraft Project," a collaborative effort between NASA and the U.S. Army to develop a practical, flexible capability for UAV-based ISR. Important facets of the project include optimization methods for allocating scarce aircraft resources to observe numerous, distinct sites of interest; intelligent flight automation software than integrates high-level plan generation capabilities with executive control, failure response and flight control functions; a system architecture supporting reconfiguration of onboard sensors to address different kinds of threats; and an advanced prototype vehicle designed to allow large-scale production at low cost. The paper will also address human interaction issues including an empirical method for determining how to allocate roles and responsibilities between flight automation and human operations.

The development of a UGV-mounted automated refueling system for VTOL UAVs

NASA Astrophysics Data System (ADS)

Wills, Mike; Burmeister, Aaron; Nelson, Travis; Denewiler, Thomas; Mullens, Kathy

2006-05-01

This paper describes the latest efforts to develop an Automated UAV Mission System (AUMS) for small vertical takeoff and landing (VTOL) unmanned air vehicles (UAVs). In certain applications such as force protection, perimeter security, and urban surveillance a VTOL UAV can provide far greater utility than fixed-wing UAVs or ground-based sensors. The VTOL UAV can operate much closer to an object of interest and can provide a hover-and-stare capability to keep its sensors trained on an object, while the fixed wing UAV would be forced into a higher altitude loitering pattern where its sensors would be subject to intermittent blockage by obstacles and terrain. The most significant disadvantage of a VTOL UAV when compared to a fixed-wing UAV is its reduced flight endurance. AUMS addresses this disadvantage by providing forward staging, refueling, and recovery capabilities for the VTOL UAV through a host unmanned ground vehicle (UGV), which serves as a launch/recovery platform and service station. The UGV has sufficient payload capacity to carry UAV fuel for multiple launch, recovery, and refuel iterations. The UGV also provides a highly mobile means of forward deploying a small UAV into hazardous areas unsafe for personnel, such as chemically or biologically contaminated areas. Teaming small UAVs with large UGVs can decrease risk to personnel and expand mission capabilities and effectiveness. There are numerous technical challenges being addressed by these development efforts. Among the challenges is the development and integration of a precision landing system compact and light enough to allow it to be mounted on a small VTOL UAV while providing repeatable landing accuracy to safely land on the AUMS. Another challenge is the design of a UGV-transportable, expandable, self-centering landing pad that contains hardware and safety devices for automatically refueling the UAV. A third challenge is making the design flexible enough to accommodate different types of VTOL UAVs

Development of an Autonomous Lidar Instrument for Use on a UAV Platform in Support of Homeland Security

NASA Technical Reports Server (NTRS)

McGill, Matthew; Famiglietti, Joe

2005-01-01

Researchers at NASA's Goddard Space Flight Center have developed an autonomous aerosol backscatter lidar instrument for use on the high-altitude ER-2 aircraft (for more information please visit http://cpl.gsfc.nasa.gov). Work is currently underway to transfer this instrument to a UAV platform such as Global Hawk. While the NASA applications are Earth science and satellite validation, there is clearly a Homeland Security application for such an instrument. One novel concept is to have a fleet of UAVs stationed around the country, each UAV having a payload including a lidar instrument. In the event of attack, the appropriate UAV(s) could be launched for purposes of, e.g., plume detection and tracking that are critical for decision support. While the existing lidar instrument is not directly capable of biological species discrimination, it is capable of plume tracking and thus can demonstrate to DHS the capabilities and utility of such instruments. Using NASA funding we will have an instrument ready to fly on Global Hawk by end of 2005. We would like to find partners, either within private industry or within DHS who would be willing to contribute aircraft access and flight hours for a demonstration flight. Longer-term partnerships to develop more advanced and more capable types of lidar instruments are also desirable. In this presentation we will detail the existing ER-2 lidar instrument and show measurement results, show the progress made on adapting to the Global Hawk platform, present concepts for DHS uses of such instruments, and openly pursue partnership opportunities.

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

NASA Astrophysics Data System (ADS)

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.

Distributed autonomous systems: resource management, planning, and control algorithms

NASA Astrophysics Data System (ADS)

Smith, James F., III; Nguyen, ThanhVu H.

2005-05-01

Distributed autonomous systems, i.e., systems that have separated distributed components, each of which, exhibit some degree of autonomy are increasingly providing solutions to naval and other DoD problems. Recently developed control, planning and resource allocation algorithms for two types of distributed autonomous systems will be discussed. The first distributed autonomous system (DAS) to be discussed consists of a collection of unmanned aerial vehicles (UAVs) that are under fuzzy logic control. The UAVs fly and conduct meteorological sampling in a coordinated fashion determined by their fuzzy logic controllers to determine the atmospheric index of refraction. Once in flight no human intervention is required. A fuzzy planning algorithm determines the optimal trajectory, sampling rate and pattern for the UAVs and an interferometer platform while taking into account risk, reliability, priority for sampling in certain regions, fuel limitations, mission cost, and related uncertainties. The real-time fuzzy control algorithm running on each UAV will give the UAV limited autonomy allowing it to change course immediately without consulting with any commander, request other UAVs to help it, alter its sampling pattern and rate when observing interesting phenomena, or to terminate the mission and return to base. The algorithms developed will be compared to a resource manager (RM) developed for another DAS problem related to electronic attack (EA). This RM is based on fuzzy logic and optimized by evolutionary algorithms. It allows a group of dissimilar platforms to use EA resources distributed throughout the group. For both DAS types significant theoretical and simulation results will be presented.

UAVs Being Used for Environmental Surveying

ScienceCinema

Chung, Sandra

2017-12-09

UAVs, are much more sophisticated than your typical remote-controlled plane. INL robotics and remote sensing experts have added state-of-the-art imaging and wireless technology to the UAVs to create intelligent remote surveillance craft that can rapidly survey a wide area for damage and track down security threats.

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

NASA Astrophysics Data System (ADS)

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.

UAV State Estimation Modeling Techniques in AHRS

NASA Astrophysics Data System (ADS)

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.

Autonomous collection of dynamically-cued multi-sensor imagery

NASA Astrophysics Data System (ADS)

Daniel, Brian; Wilson, Michael L.; Edelberg, Jason; Jensen, Mark; Johnson, Troy; Anderson, Scott

2011-05-01

The availability of imagery simultaneously collected from sensors of disparate modalities enhances an image analyst's situational awareness and expands the overall detection capability to a larger array of target classes. Dynamic cooperation between sensors is increasingly important for the collection of coincident data from multiple sensors either on the same or on different platforms suitable for UAV deployment. Of particular interest is autonomous collaboration between wide area survey detection, high-resolution inspection, and RF sensors that span large segments of the electromagnetic spectrum. The Naval Research Laboratory (NRL) in conjunction with the Space Dynamics Laboratory (SDL) is building sensors with such networked communications capability and is conducting field tests to demonstrate the feasibility of collaborative sensor data collection and exploitation. Example survey / detection sensors include: NuSAR (NRL Unmanned SAR), a UAV compatible synthetic aperture radar system; microHSI, an NRL developed lightweight hyper-spectral imager; RASAR (Real-time Autonomous SAR), a lightweight podded synthetic aperture radar; and N-WAPSS-16 (Nighttime Wide-Area Persistent Surveillance Sensor-16Mpix), a MWIR large array gimbaled system. From these sensors, detected target cues are automatically sent to the NRL/SDL developed EyePod, a high-resolution, narrow FOV EO/IR sensor, for target inspection. In addition to this cooperative data collection, EyePod's real-time, autonomous target tracking capabilities will be demonstrated. Preliminary results and target analysis will be presented.

Volcano surveillance by ACR silver fox

USGS Publications Warehouse

Patterson, M.C.L.; Mulligair, A.; Douglas, J.; Robinson, J.; Pallister, J.S.

2005-01-01

Recent growth in the business of unmanned air vehicles (UAVs) both in the US and abroad has improved their overall capability, resulting in a reduction in cost, greater reliability and adoption into areas where they had previously not been considered. Uses in coastal and border patrol, forestry and agriculture have recently been evaluated in an effort to expand the observed area and reduce surveillance and reconnaissance costs for information gathering. The scientific community has both contributed and benefited greatly in this development. A larger suite of light-weight miniaturized sensors now exists for a range of applications which in turn has led to an increase in the gathering of information from these autonomous vehicles. In October 2004 the first eruption of Mount St Helens since 1986 caused tremendous interest amoUg people worldwide. Volcanologists at the U.S. Geological Survey rapidly ramped up the level of monitoring using a variety of ground-based sensors deployed in the crater and on the flanks of the volcano using manned helicopters. In order to develop additional unmanned sensing methods that can be used in potentially hazardous and low visibility conditions, a UAV experiment was conducted during the ongoing eruption early in November. The Silver Fox UAV was flown over and inside the crater to perform routine observation and data gathering, thereby demonstrating a technology that could reduce physical risk to scientists and other field operatives. It was demonstrated that UAVs can be flown autonomously at an active volcano and can deliver real time data to a remote location. Although still relatively limited in extent, these initial flights provided information on volcanic activity and thermal conditions within the crater and at the new (2004) lava dome. The flights demonstrated that readily available visual and infrared video sensors mounted in a small and relatively low-cost aerial platform can provide useful data on volcanic phenomena. This was

Autonomous mobile robotic system for supporting counterterrorist and surveillance operations

NASA Astrophysics Data System (ADS)

Adamczyk, Marek; Bulandra, Kazimierz; Moczulski, Wojciech

2017-10-01

Contemporary research on mobile robots concerns applications to counterterrorist and surveillance operations. The goal is to develop systems that are capable of supporting the police and special forces by carrying out such operations. The paper deals with a dedicated robotic system for surveillance of large objects such as airports, factories, military bases, and many others. The goal is to trace unauthorised persons who try to enter to the guarded area, document the intrusion and report it to the surveillance centre, and then warn the intruder by sound messages and eventually subdue him/her by stunning through acoustic effect of great power. The system consists of several parts. An armoured four-wheeled robot assures required mobility of the system. The robot is equipped with a set of sensors including 3D mapping system, IR and video cameras, and microphones. It communicates with the central control station (CCS) by means of a wideband wireless encrypted system. A control system of the robot can operate autonomously, and under remote control. In the autonomous mode the robot follows the path planned by the CCS. Once an intruder has been detected, the robot can adopt its plan to allow tracking him/her. Furthermore, special procedures of treatment of the intruder are applied including warning about the breach of the border of the protected area, and incapacitation of an appropriately selected very loud sound until a patrol of guards arrives. Once getting stuck the robot can contact the operator who can remotely solve the problem the robot is faced with.

Unmanned air vehicle: autonomous takeoff and landing

NASA Astrophysics Data System (ADS)

Lim, K. L.; Gitano-Briggs, Horizon Walker

2010-03-01

UAVs are increasing in popularity and sophistication due to the demonstrated performance which cannot be attained by manned aircraft1. These developments have been made possible by development of sensors, instrumentation, telemetry and controls during the last few decades. UAVs are now common in areas such as aerial observation and as communication relays3. Most UAVs, however, are still flown by a human pilot via remote control from a ground station. Even the existing autonomous UAVs often require a human pilot to handle the most difficult tasks of take off and landing2 (TOL). This is mainly because the navigation of the airplane requires observation, constant situational assessment and hours of experience from the pilot himself4. Therefore, an autonomous takeoff and landing system (TLS) for UAVs using a few practical design rules with various sensors, instrumentation, etc has been developed. This paper details the design and modeling of the UAV TLS. The model indicates that the UAV's TLS shows promising stability.

Unmanned air vehicle: autonomous takeoff and landing

NASA Astrophysics Data System (ADS)

Lim, K. L.; Gitano-Briggs, Horizon Walker

2009-12-01

UAVs are increasing in popularity and sophistication due to the demonstrated performance which cannot be attained by manned aircraft1. These developments have been made possible by development of sensors, instrumentation, telemetry and controls during the last few decades. UAVs are now common in areas such as aerial observation and as communication relays3. Most UAVs, however, are still flown by a human pilot via remote control from a ground station. Even the existing autonomous UAVs often require a human pilot to handle the most difficult tasks of take off and landing2 (TOL). This is mainly because the navigation of the airplane requires observation, constant situational assessment and hours of experience from the pilot himself4. Therefore, an autonomous takeoff and landing system (TLS) for UAVs using a few practical design rules with various sensors, instrumentation, etc has been developed. This paper details the design and modeling of the UAV TLS. The model indicates that the UAV's TLS shows promising stability.

Pricise Target Geolocation Based on Integeration of Thermal Video Imagery and Rtk GPS in Uavs

NASA Astrophysics Data System (ADS)

Hosseinpoor, H. R.; Samadzadegan, F.; Dadras Javan, F.

2015-12-01

There are an increasingly large number of uses for Unmanned Aerial Vehicles (UAVs) from surveillance, 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 which implicates that it 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 a linear 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 and Kalman filtering and interior orientation parameters of thermal camera from pre-flight laboratory calibration process.

An Improved Vision-based Algorithm for Unmanned Aerial Vehicles Autonomous Landing

NASA Astrophysics Data System (ADS)

Zhao, Yunji; Pei, Hailong

In vision-based autonomous landing system of UAV, the efficiency of target detecting and tracking will directly affect the control system. The improved algorithm of SURF(Speed Up Robust Features) will resolve the problem which is the inefficiency of the SURF algorithm in the autonomous landing system. The improved algorithm is composed of three steps: first, detect the region of the target using the Camshift; second, detect the feature points in the region of the above acquired using the SURF algorithm; third, do the matching between the template target and the region of target in frame. The results of experiment and theoretical analysis testify the efficiency of the algorithm.

Research Institute for Autonomous Precision Guided Systems

DTIC Science & Technology

2007-03-08

research on agile autonomous munitions, in direct support of the Air Force Research Laboratory Munitions Directorate (AFRL/MN). The grant was awarded with a...Flight had (5) research task areas: 1. Aeroforms and Actuation for Small and Micro Agile Air Vehicles 2. Sensing for Autonomous Control and...critical barriers in AAM, but are not covered in the scope of the AVCAAF (Vision-Based Control of Agile, Autonomous Micro Air Vehicles and Small UAVs

Performance Characteristic Mems-Based IMUs for UAVs Navigation

NASA Astrophysics Data System (ADS)

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.

A proposed UAV for indoor patient care.

PubMed

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

2015-09-10

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

Uav-Based 3d Urban Environment Monitoring

NASA Astrophysics Data System (ADS)

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.

Cooperative UAV-Based Communications Backbone for Sensor Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roberts, R S

2001-10-07

The objective of this project is to investigate the use of unmanned air vehicles (UAVs) as mobile, adaptive communications backbones for ground-based sensor networks. In this type of network, the UAVs provide communication connectivity to sensors that cannot communicate with each other because of terrain, distance, or other geographical constraints. In these situations, UAVs provide a vertical communication path for the sensors, thereby mitigating geographic obstacles often imposed on networks. With the proper use of UAVs, connectivity to a widely disbursed sensor network in rugged terrain is readily achieved. Our investigation has focused on networks where multiple cooperating UAVs aremore » used to form a network backbone. The advantage of using multiple UAVs to form the network backbone is parallelization of sensor connectivity. Many widely spaced or isolated sensors can be connected to the network at once using this approach. In these networks, the UAVs logically partition the sensor network into sub-networks (subnets), with one UAV assigned per subnet. Partitioning the network into subnets allows the UAVs to service sensors in parallel thereby decreasing the sensor-to-network connectivity. A UAV services sensors in its subnet by flying a route (path) through the subnet, uplinking data collected by the sensors, and forwarding the data to a ground station. An additional advantage of using multiple UAVs in the network is that they provide redundancy in the communications backbone, so that the failure of a single UAV does not necessarily imply the loss of the network.« less

Radar sensing via a Micro-UAV-borne system

NASA Astrophysics Data System (ADS)

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

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

PubMed

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.

Path planning and Ground Control Station simulator for UAV

NASA Astrophysics Data System (ADS)

Ajami, A.; Balmat, J.; Gauthier, J.-P.; Maillot, T.

In this paper we present a Universal and Interoperable Ground Control Station (UIGCS) simulator for fixed and rotary wing Unmanned Aerial Vehicles (UAVs), and all types of payloads. One of the major constraints is to operate and manage multiple legacy and future UAVs, taking into account the compliance with NATO Combined/Joint Services Operational Environment (STANAG 4586). Another purpose of the station is to assign the UAV a certain degree of autonomy, via autonomous planification/replanification strategies. The paper is organized as follows. In Section 2, we describe the non-linear models of the fixed and rotary wing UAVs that we use in the simulator. In Section 3, we describe the simulator architecture, which is based upon interacting modules programmed independently. This simulator is linked with an open source flight simulator, to simulate the video flow and the moving target in 3D. To conclude this part, we tackle briefly the problem of the Matlab/Simulink software connection (used to model the UAV's dynamic) with the simulation of the virtual environment. Section 5 deals with the control module of a flight path of the UAV. The control system is divided into four distinct hierarchical layers: flight path, navigation controller, autopilot and flight control surfaces controller. In the Section 6, we focus on the trajectory planification/replanification question for fixed wing UAV. Indeed, one of the goals of this work is to increase the autonomy of the UAV. We propose two types of algorithms, based upon 1) the methods of the tangent and 2) an original Lyapunov-type method. These algorithms allow either to join a fixed pattern or to track a moving target. Finally, Section 7 presents simulation results obtained on our simulator, concerning a rather complicated scenario of mission.

Characteristic Analysis on UAV-MIMO Channel Based on Normalized Correlation Matrix

PubMed Central

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

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. PMID:24977185

Graph theoretic framework based cooperative control and estimation of multiple UAVs for target tracking

NASA Astrophysics Data System (ADS)

Ahmed, Mousumi

Designing the control technique for nonlinear dynamic systems is a significant challenge. Approaches to designing a nonlinear controller are studied and an extensive study on backstepping based technique is performed in this research with the purpose of tracking a moving target autonomously. Our main motivation is to explore the controller for cooperative and coordinating unmanned vehicles in a target tracking application. To start with, a general theoretical framework for target tracking is studied and a controller in three dimensional environment for a single UAV is designed. This research is primarily focused on finding a generalized method which can be applied to track almost any reference trajectory. The backstepping technique is employed to derive the controller for a simplified UAV kinematic model. This controller can compute three autopilot modes i.e. velocity, ground heading (or course angle), and flight path angle for tracking the unmanned vehicle. Numerical implementation is performed in MATLAB with the assumption of having perfect and full state information of the target to investigate the accuracy of the proposed controller. This controller is then frozen for the multi-vehicle problem. Distributed or decentralized cooperative control is discussed in the context of multi-agent systems. A consensus based cooperative control is studied; such consensus based control problem can be viewed from the algebraic graph theory concepts. The communication structure between the UAVs is represented by the dynamic graph where UAVs are represented by the nodes and the communication links are represented by the edges. The previously designed controller is augmented to account for the group to obtain consensus based on their communication. A theoretical development of the controller for the cooperative group of UAVs is presented and the simulation results for different communication topologies are shown. This research also investigates the cases where the communication

Applications of UAVs for Remote Sensing of Critical Infrastructure

NASA Technical Reports Server (NTRS)

Wegener, Steve; Brass, James; Schoenung, Susan

2003-01-01

The surveillance of critical facilities and national infrastructure such as waterways, roadways, pipelines and utilities requires advanced technological tools to provide timely, up to date information on structure status and integrity. Unmanned Aerial Vehicles (UAVs) are uniquely suited for these tasks, having large payload and long duration capabilities. UAVs also have the capability to fly dangerous and dull missions, orbiting for 24 hours over a particular area or facility providing around the clock surveillance with no personnel onboard. New UAV platforms and systems are becoming available for commercial use. High altitude platforms are being tested for use in communications, remote sensing, agriculture, forestry and disaster management. New payloads are being built and demonstrated onboard the UAVs in support of these applications. Smaller, lighter, lower power consumption imaging systems are currently being tested over coffee fields to determine yield and over fires to detect fire fronts and hotspots. Communication systems that relay video, meteorological and chemical data via satellite to users on the ground in real-time have also been demonstrated. Interest in this technology for infrastructure characterization and mapping has increased dramatically in the past year. Many of the UAV technological developments required for resource and disaster monitoring are being used for the infrastructure and facility mapping activity. This paper documents the unique contributions from NASA;s Environmental Research Aircraft and Sensor Technology (ERAST) program to these applications. ERAST is a UAV technology development effort by a consortium of private aeronautical companies and NASA. Details of demonstrations of UAV capabilities currently underway are also presented.

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

NASA Astrophysics Data System (ADS)

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.

Robust all-source positioning of UAVs based on belief propagation

NASA Astrophysics Data System (ADS)

Chen, Xi; Gao, Wenyun; Wang, Jiabo

2013-12-01

For unmanned air vehicles (UAVs) to survive hostile operational environments, it is always preferable to utilize all wireless positioning sources available to fuse a robust position. While belief propagation is a well-established method for all source data fusion, it is not an easy job to handle all the mathematics therein. In this work, a comprehensive mathematical framework for belief propagation-based all-source positioning of UAVs is developed, taking wireless sources including Global Navigation Satellite Systems (GNSS) space vehicles, peer UAVs, ground control stations, and signal of opportunities. Based on the mathematical framework, a positioning algorithm named Belief propagation-based Opportunistic Positioning of UAVs (BOPU) is proposed, with an unscented particle filter for Bayesian approximation. The robustness of the proposed BOPU is evaluated by a fictitious scenario that a group of formation flying UAVs encounter GNSS countermeasures en route. Four different configurations of measurements availability are simulated. The results show that the performance of BOPU varies only slightly with different measurements availability.

Earthbound Unmanned Autonomous Vehicles (UAVS) As Planetary Science Testbeds

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Research on performance requirements of turbofan engine used on carrier-based UAV

NASA Astrophysics Data System (ADS)

Zhao, Shufan; Li, Benwei; Zhang, Wenlong; Wu, Heng; Feng, Tang

2017-05-01

According to the mission requirements of the carrier-based unmanned aerial vehicle (UAV), a mode level flight was established to calculate the thrust requirements from altitude 9 km to 13 km. Then, the estimation method of flight profile was used to calculate the weight of UAV in each stage to get the specific fuel consumption requirements of the UAV in standby stage. The turbofan engine of carrier-based UAV should meet the thrust and specific fuel consumption requirements. Finally, the GSP software was used to verify the simulation of a small high-bypass turbofan engine. The conclusion is useful for the turbofan engine selection of carrier-based UAV.

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

NASA Astrophysics Data System (ADS)

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.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chelaru, Teodor-Viorel, E-mail: teodor.chelaru@upb.ro; Chelaru, Adrian, E-mail: achelaru@incas.ro

The paper purpose is to present some aspects regarding the control system of unmanned aerial vehicle - UAV, used to local observations, surveillance and monitoring interest area. The calculus methodology allows a numerical simulation of UAV evolution in bad atmospheric conditions by using nonlinear model, as well as a linear one for obtaining guidance command. The UAV model which will be presented has six DOF (degrees of freedom), and autonomous control system. This theoretical development allows us to build stability matrix, command matrix and control matrix and finally to analyse the stability of autonomous UAV flight. A robust guidance system,more » based on uncoupled state will be evaluated for different fly conditions and the results will be presented. The flight parameters and guidance will be analysed.« less

Detection, Location and Grasping Objects Using a Stereo Sensor on UAV in Outdoor Environments.

PubMed

Ramon Soria, Pablo; Arrue, Begoña C; Ollero, Anibal

2017-01-07

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.

Detection, Location and Grasping Objects Using a Stereo Sensor on UAV in Outdoor Environments

PubMed Central

Ramon Soria, Pablo; Arrue, Begoña C.; Ollero, Anibal

2017-01-01

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. PMID:28067851

Towards distributed ATR using subjective logic combination rules with a swarm of UAVs

NASA Astrophysics Data System (ADS)

O'Hara, Stephen; Simon, Michael; Zhu, Qiuming

2007-04-01

In this paper, we present our initial findings demonstrating a cost-effective approach to Aided Target Recognition (ATR) employing a swarm of inexpensive Unmanned Aerial Vehicles (UAVs). We call our approach Distributed ATR (DATR). Our paper describes the utility of DATR for autonomous UAV operations, provides an overview of our methods, and the results of our initial simulation-based implementation and feasibility study. Our technology is aimed towards small and micro UAVs where platform restrictions allow only a modest quality camera and limited on-board computational capabilities. It is understood that an inexpensive sensor coupled with limited processing capability would be challenged in deriving a high probability of detection (P d) while maintaining a low probability of false alarms (P fa). Our hypothesis is that an evidential reasoning approach to fusing the observations of multiple UAVs observing approximately the same scene can raise the P d and lower the P fa sufficiently in order to provide a cost-effective ATR capability. This capability can lead to practical implementations of autonomous, coordinated, multi-UAV operations. In our system, the live video feed from a UAV is processed by a lightweight real-time ATR algorithm. This algorithm provides a set of possible classifications for each detected object over a possibility space defined by a set of exemplars. The classifications for each frame within a short observation interval (a few seconds) are used to generate a belief statement. Our system considers how many frames in the observation interval support each potential classification. A definable function transforms the observational data into a belief value. The belief value, or opinion, represents the UAV's belief that an object of the particular class exists in the area covered during the observation interval. The opinion is submitted as evidence in an evidential reasoning system. Opinions from observations over the same spatial area will have

Automated geographic registration and radiometric correction for UAV-based mosaics

USDA-ARS?s Scientific Manuscript database

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...

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

NASA Astrophysics Data System (ADS)

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.

Reinforcement Learning with Autonomous Small Unmanned Aerial Vehicles in Cluttered Environments

NASA Technical Reports Server (NTRS)

Tran, Loc; Cross, Charles; Montague, Gilbert; Motter, Mark; Neilan, James; Qualls, Garry; Rothhaar, Paul; Trujillo, Anna; Allen, B. Danette

2015-01-01

We present ongoing work in the Autonomy Incubator at NASA Langley Research Center (LaRC) exploring the efficacy of a data set aggregation approach to reinforcement learning for small unmanned aerial vehicle (sUAV) flight in dense and cluttered environments with reactive obstacle avoidance. The goal is to learn an autonomous flight model using training experiences from a human piloting a sUAV around static obstacles. The training approach uses video data from a forward-facing camera that records the human pilot's flight. Various computer vision based features are extracted from the video relating to edge and gradient information. The recorded human-controlled inputs are used to train an autonomous control model that correlates the extracted feature vector to a yaw command. As part of the reinforcement learning approach, the autonomous control model is iteratively updated with feedback from a human agent who corrects undesired model output. This data driven approach to autonomous obstacle avoidance is explored for simulated forest environments furthering autonomous flight under the tree canopy research. This enables flight in previously inaccessible environments which are of interest to NASA researchers in Earth and Atmospheric sciences.

Micro-UAV tracking framework for EO exploitation

NASA Astrophysics Data System (ADS)

Browning, David; Wilhelm, Joe; Van Hook, Richard; Gallagher, John

2012-06-01

Historically, the Air Force's research into aerial platforms for sensing systems has focused on low-, mid-, and highaltitude platforms. Though these systems are likely to comprise the majority of the Air Force's assets for the foreseeable future, they have limitations. Specifically, these platforms, their sensor packages, and their data exploitation software are unsuited for close-quarter surveillance, such as in alleys and inside of buildings. Micro-UAVs have been gaining in popularity, especially non-fixed-wing platforms such as quad-rotors. These platforms are much more appropriate for confined spaces. However, the types of video exploitation techniques that can effectively be used are different from the typical nadir-looking aerial platform. This paper discusses the creation of a framework for testing existing and new video exploitation algorithms, as well as describes a sample micro-UAV-based tracker.

Computational analysis of unmanned aerial vehicle (UAV)

NASA Astrophysics Data System (ADS)

Abudarag, Sakhr; Yagoub, Rashid; Elfatih, Hassan; Filipovic, Zoran

2017-01-01

A computational analysis has been performed to verify the aerodynamics properties of Unmanned Aerial Vehicle (UAV). The UAV-SUST has been designed and fabricated at the Department of Aeronautical Engineering at Sudan University of Science and Technology in order to meet the specifications required for surveillance and reconnaissance mission. It is classified as a medium range and medium endurance UAV. A commercial CFD solver is used to simulate steady and unsteady aerodynamics characteristics of the entire UAV. In addition to Lift Coefficient (CL), Drag Coefficient (CD), Pitching Moment Coefficient (CM) and Yawing Moment Coefficient (CN), the pressure and velocity contours are illustrated. The aerodynamics parameters are represented a very good agreement with the design consideration at angle of attack ranging from zero to 26 degrees. Moreover, the visualization of the velocity field and static pressure contours is indicated a satisfactory agreement with the proposed design. The turbulence is predicted by enhancing K-ω SST turbulence model within the computational fluid dynamics code.

Sense and avoid technology for Global Hawk and Predator UAVs

NASA Astrophysics Data System (ADS)

McCalmont, John F.; Utt, James; Deschenes, Michael; Taylor, Michael J.

2005-05-01

The Sensors Directorate at the Air Force Research Laboratory (AFRL) along with Defense Research Associates, Inc. (DRA) conducted a flight demonstration of technology that could potentially satisfy the Federal Aviation Administration's (FAA) requirement for Unmanned Aerial Vehicles (UAVs) to sense and avoid local air traffic sufficient to provide an "...equivalent level of safety, comparable to see-and-avoid requirements for manned aircraft". This FAA requirement must be satisfied for autonomous UAV operation within the national airspace. The real-time on-board system passively detects approaching aircraft, both cooperative and non-cooperative, using imaging sensors operating in the visible/near infrared band and a passive moving target indicator algorithm. Detection range requirements for RQ-4 and MQ-9 UAVs were determined based on analysis of flight geometries, avoidance maneuver timelines, system latencies and human pilot performance. Flight data and UAV operating parameters were provided by the system program offices, prime contractors, and flight-test personnel. Flight demonstrations were conducted using a surrogate UAV (Aero Commander) and an intruder aircraft (Beech Bonanza). The system demonstrated target detection ranges out to 3 nautical miles in nose-to-nose scenarios and marginal visual meteorological conditions. (VMC) This paper will describe the sense and avoid requirements definition process and the system concept (sensors, algorithms, processor, and flight rest results) that has demonstrated the potential to satisfy the FAA sense and avoid requirements.

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

NASA Astrophysics Data System (ADS)

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

Impact of Prior Flight Experience on Learning Predator UAV Operator Skills

DTIC Science & Technology

2002-02-01

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

Fielding An Amphibious UAV: Development, Results, and Lessons Learned

NASA Technical Reports Server (NTRS)

Pisanich, Greg; Morris, Stephen

2002-01-01

This report summarizes the work completed on the design and flight-testing of a small, unmanned, amphibious demonstrator aircraft that flies autonomously. The aircraft named ACAT (Autonomous Cargo Amphibious Transport) is intended to be a large cargo carrying unmanned aircraft that operates from water to avoid airspace and airfield conflict issues between manned and unmanned aircraft. To demonstrate the feasibility of this concept, a demonstrator ACAT was designed, built, and flown that has a six-foot wingspan and can fly autonomously from land or water airfield. The demonstrator was designed for a 1-hour duration and 1-mile telemetry range. A sizing code was used to design the smallest demonstrator UAV to achieve these goals. The final design was a six-foot wingspan, twin hull configuration that distributes the cargo weight across the span, reducing the wing structural weight. The demonstrator airframe was constructed from balsa wood, fiberglass, and plywood. A 4-stroke model airplane engine powered by methanol fuel was mounted in a pylon above the wing and powers the ACAT UAV. Initial flight tests from land and water were conducted under manual radio control and confirmed the amphibious capability of the design. Flight avionics that were developed by MLB for production UAVs were installed in the ACAT demonstrator. The flight software was also enhanced to permit autonomous takeoff and landing from water. A complete autonomous flight from ahard runway was successfully completed on July 5, 2001 and consisted of a take-off, rectangular flight pattern, and landing under complete computer control. A completely autonomous flight that featured a water takeoff and landing was completed on October 4, 2001. This report describes these activities in detail and highlights the challenges encountered and solved during the development of the ACAT demonstrator. hard runway was successfully completed on July 5, 2001 and consisted of a take-off, rectangular flight pattern, and

Towards an Autonomous Vision-Based Unmanned Aerial System against Wildlife Poachers

PubMed Central

Olivares-Mendez, Miguel A.; Fu, Changhong; Ludivig, Philippe; Bissyandé, Tegawendé F.; Kannan, Somasundar; Zurad, Maciej; Annaiyan, Arun; Voos, Holger; Campoy, Pascual

2015-01-01

Poaching is an illegal activity that remains out of control in many countries. Based on the 2014 report of the United Nations and Interpol, the illegal trade of global wildlife and natural resources amounts to nearly $213 billion every year, which is even helping to fund armed conflicts. Poaching activities around the world are further pushing many animal species on the brink of extinction. Unfortunately, the traditional methods to fight against poachers are not enough, hence the new demands for more efficient approaches. In this context, the use of new technologies on sensors and algorithms, as well as aerial platforms is crucial to face the high increase of poaching activities in the last few years. Our work is focused on the use of vision sensors on UAVs for the detection and tracking of animals and poachers, as well as the use of such sensors to control quadrotors during autonomous vehicle following and autonomous landing. PMID:26703597

Towards an Autonomous Vision-Based Unmanned Aerial System against Wildlife Poachers.

PubMed

Olivares-Mendez, Miguel A; Fu, Changhong; Ludivig, Philippe; Bissyandé, Tegawendé F; Kannan, Somasundar; Zurad, Maciej; Annaiyan, Arun; Voos, Holger; Campoy, Pascual

2015-12-12

Poaching is an illegal activity that remains out of control in many countries. Based on the 2014 report of the United Nations and Interpol, the illegal trade of global wildlife and natural resources amounts to nearly $ 213 billion every year, which is even helping to fund armed conflicts. Poaching activities around the world are further pushing many animal species on the brink of extinction. Unfortunately, the traditional methods to fight against poachers are not enough, hence the new demands for more efficient approaches. In this context, the use of new technologies on sensors and algorithms, as well as aerial platforms is crucial to face the high increase of poaching activities in the last few years. Our work is focused on the use of vision sensors on UAVs for the detection and tracking of animals and poachers, as well as the use of such sensors to control quadrotors during autonomous vehicle following and autonomous landing.

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

PubMed

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.

Real-time implementations of acoustic signal enhancement techniques for aerial based surveillance and rescue applications

NASA Astrophysics Data System (ADS)

Ramos, Antonio L. L.; Shao, Zhili; Holthe, Aleksander; Sandli, Mathias F.

2017-05-01

The introduction of the System-on-Chip (SoC) technology has brought exciting new opportunities for the development of smart low cost embedded systems spanning a wide range of applications. Currently available SoC devices are capable of performing high speed digital signal processing tasks in software while featuring relatively low development costs and reduced time-to-market. Unmanned aerial vehicles (UAV) are an application example that has shown tremendous potential in an increasing number of scenarios, ranging from leisure to surveillance as well as in search and rescue missions. Video capturing from UAV platforms is a relatively straightforward task that requires almost no preprocessing. However, that does not apply to audio signals, especially in cases where the data is to be used to support real-time decision making. In fact, the enormous amount of acoustic interference from the surroundings, including the noise from the UAVs propellers, becomes a huge problem. This paper discusses a real-time implementation of the NLMS adaptive filtering algorithm applied to enhancing acoustic signals captured from UAV platforms. The model relies on a combination of acoustic sensors and a computational inexpensive algorithm running on a digital signal processor. Given its simplicity, this solution can be incorporated into the main processing system of an UAV using the SoC technology, and run concurrently with other required tasks, such as flight control and communications. Simulations and real-time DSP-based implementations have shown significant signal enhancement results by efficiently mitigating the interference from the noise generated by the UAVs propellers as well as from other external noise sources.

Obstacle Detection and Avoidance System Based on Monocular Camera and Size Expansion Algorithm for UAVs

PubMed Central

Al-Kaff, Abdulla; García, Fernando; Martín, David; De La Escalera, Arturo; Armingol, José María

2017-01-01

One of the most challenging problems in the domain of autonomous aerial vehicles is the designing of a robust real-time obstacle detection and avoidance system. This problem is complex, especially for the micro and small aerial vehicles, that is due to the Size, Weight and Power (SWaP) constraints. Therefore, using lightweight sensors (i.e., Digital camera) can be the best choice comparing with other sensors; such as laser or radar.For real-time applications, different works are based on stereo cameras in order to obtain a 3D model of the obstacles, or to estimate their depth. Instead, in this paper, a method that mimics the human behavior of detecting the collision state of the approaching obstacles using monocular camera is proposed. The key of the proposed algorithm is to analyze the size changes of the detected feature points, combined with the expansion ratios of the convex hull constructed around the detected feature points from consecutive frames. During the Aerial Vehicle (UAV) motion, the detection algorithm estimates the changes in the size of the area of the approaching obstacles. First, the method detects the feature points of the obstacles, then extracts the obstacles that have the probability of getting close toward the UAV. Secondly, by comparing the area ratio of the obstacle and the position of the UAV, the method decides if the detected obstacle may cause a collision. Finally, by estimating the obstacle 2D position in the image and combining with the tracked waypoints, the UAV performs the avoidance maneuver. The proposed algorithm was evaluated by performing real indoor and outdoor flights, and the obtained results show the accuracy of the proposed algorithm compared with other related works. PMID:28481277

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

PubMed

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.

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

PubMed Central

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

2017-01-01

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. PMID:28956839

Using Natural Language to Enable Mission Managers to Control Multiple Heterogeneous UAVs

NASA Technical Reports Server (NTRS)

Trujillo, Anna C.; Puig-Navarro, Javier; Mehdi, S. Bilal; Mcquarry, A. Kyle

2016-01-01

The availability of highly capable, yet relatively cheap, unmanned aerial vehicles (UAVs) is opening up new areas of use for hobbyists and for commercial activities. This research is developing methods beyond classical control-stick pilot inputs, to allow operators to manage complex missions without in-depth vehicle expertise. These missions may entail several heterogeneous UAVs flying coordinated patterns or flying multiple trajectories deconflicted in time or space to predefined locations. This paper describes the functionality and preliminary usability measures of an interface that allows an operator to define a mission using speech inputs. With a defined and simple vocabulary, operators can input the vast majority of mission parameters using simple, intuitive voice commands. Although the operator interface is simple, it is based upon autonomous algorithms that allow the mission to proceed with minimal input from the operator. This paper also describes these underlying algorithms that allow an operator to manage several UAVs.

Feasibility Study for an Autonomous UAV - Magnetometer System

DTIC Science & Technology

2007-11-01

collect data from multiple magnetometers at high sampling rates (~100 Hz), and associated with these acquisition systems are highly accurate...component for an UAV helicopter- magnetometer system is the ability to have precise positioning (both for flightpath execution and for data acquisition...discussed under section 6.3. Figure 6.11 shows the fluxgate data used to compensate a total field magnetometer as previously described. The red

Optimization of processing parameters of UAV integral structural components based on yield response

NASA Astrophysics Data System (ADS)

Chen, Yunsheng

2018-05-01

In order to improve the overall strength of unmanned aerial vehicle (UAV), it is necessary to optimize the processing parameters of UAV structural components, which is affected by initial residual stress in the process of UAV structural components processing. Because machining errors are easy to occur, an optimization model for machining parameters of UAV integral structural components based on yield response is proposed. The finite element method is used to simulate the machining parameters of UAV integral structural components. The prediction model of workpiece surface machining error is established, and the influence of the path of walking knife on residual stress of UAV integral structure is studied, according to the stress of UAV integral component. The yield response of the time-varying stiffness is analyzed, and the yield response and the stress evolution mechanism of the UAV integral structure are analyzed. The simulation results show that this method is used to optimize the machining parameters of UAV integral structural components and improve the precision of UAV milling processing. The machining error is reduced, and the deformation prediction and error compensation of UAV integral structural parts are realized, thus improving the quality of machining.

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

PubMed Central

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

2015-01-01

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. PMID:25808767

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

PubMed

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.

Planification de trajectoires pour une flotte d'UAVs

NASA Astrophysics Data System (ADS)

Ait El Cadi, Abdessamad

In this thesis we address the problem of coordinating and controlling a fleet of Unmanned Aerial Vehicles (UAVs) during a surveillance mission in a dynamic context. The problem is vast and is related to several scientific domains. We have studied three important parts of this problem: • modeling the ground with all its constraints; • computing a shortest non-holonomic continuous path in a risky environment with a presence of obstacles; • planning a surveillance mission for a fleet of UAVs in a real context. While investigating the scientific literature related to these topics, we have detected deficiencies in the modeling of the ground and in the computation of the shortest continuous path, two critical aspects for the planning of a mission. So after the literature review, we have proposed answers to these two aspects and have applied our developments to the planning of a mission of a fleet of UAVs in a risky environment with the presence of obstacles. Obstacles could be natural like mountain or any non flyable zone. We have first modeled the ground as a directed graph. However, instead of using a classic mesh, we opted for an intelligent modeling that reduces the computing time on the graph without losing accuracy. The proposed model is based on the concept of visibility graph, and it also takes into account the obstacles, the danger areas and the constraint of non-holonomy of the UAVs- the kinematic constraint of the planes that imposes a maximum steering angle. The graph is then cleaned to keep only the minimum information needed for the calculation of trajectories. The generation of this graph possibly requires a lot of computation time, but it is done only once before the planning and will not affect the performance of trajectory calculations. We have also developed another simpler graph that does not take into account the constraint of non-holonomy. The advantage of this second graph is that it reduces the computation time. However, it requires the use

DTM Generation with Uav Based Photogrammetric Point Cloud

NASA Astrophysics Data System (ADS)

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.

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

PubMed

Vetrella, Amedeo Rodi; Fasano, Giancarmine; Accardo, Domenico; Moccia, Antonio

2016-12-17

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.

Design and implementation of a remote UAV-based mobile health monitoring system

NASA Astrophysics Data System (ADS)

Li, Songwei; Wan, Yan; Fu, Shengli; Liu, Mushuang; Wu, H. Felix

2017-04-01

Unmanned aerial vehicles (UAVs) play increasing roles in structure health monitoring. With growing mobility in modern Internet-of-Things (IoT) applications, the health monitoring of mobile structures becomes an emerging application. In this paper, we develop a UAV-carried vision-based monitoring system that allows a UAV to continuously track and monitor a mobile infrastructure and transmit back the monitoring information in real- time from a remote location. The monitoring system uses a simple UAV-mounted camera and requires only a single feature located on the mobile infrastructure for target detection and tracking. The computation-effective vision-based tracking solution based on a single feature is an improvement over existing vision-based lead-follower tracking systems that either have poor tracking performance due to the use of a single feature, or have improved tracking performance at a cost of the usage of multiple features. In addition, a UAV-carried aerial networking infrastructure using directional antennas is used to enable robust real-time transmission of monitoring video streams over a long distance. Automatic heading control is used to self-align headings of directional antennas to enable robust communication in mobility. Compared to existing omni-communication systems, the directional communication solution significantly increases the operation range of remote monitoring systems. In this paper, we develop the integrated modeling framework of camera and mobile platforms, design the tracking algorithm, develop a testbed of UAVs and mobile platforms, and evaluate system performance through both simulation studies and field tests.

UAV-based Radar Sounding of Antarctic Ice

NASA Astrophysics Data System (ADS)

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

Radar based autonomous sensor module

NASA Astrophysics Data System (ADS)

Styles, Tim

2016-10-01

Most surveillance systems combine camera sensors with other detection sensors that trigger an alert to a human operator when an object is detected. The detection sensors typically require careful installation and configuration for each application and there is a significant burden on the operator to react to each alert by viewing camera video feeds. A demonstration system known as Sensing for Asset Protection with Integrated Electronic Networked Technology (SAPIENT) has been developed to address these issues using Autonomous Sensor Modules (ASM) and a central High Level Decision Making Module (HLDMM) that can fuse the detections from multiple sensors. This paper describes the 24 GHz radar based ASM, which provides an all-weather, low power and license exempt solution to the problem of wide area surveillance. The radar module autonomously configures itself in response to tasks provided by the HLDMM, steering the transmit beam and setting range resolution and power levels for optimum performance. The results show the detection and classification performance for pedestrians and vehicles in an area of interest, which can be modified by the HLDMM without physical adjustment. The module uses range-Doppler processing for reliable detection of moving objects and combines Radar Cross Section and micro-Doppler characteristics for object classification. Objects are classified as pedestrian or vehicle, with vehicle sub classes based on size. Detections are reported only if the object is detected in a task coverage area and it is classified as an object of interest. The system was shown in a perimeter protection scenario using multiple radar ASMs, laser scanners, thermal cameras and visible band cameras. This combination of sensors enabled the HLDMM to generate reliable alerts with improved discrimination of objects and behaviours of interest.

Coordinating UAV information for executing national security-oriented collaboration

NASA Astrophysics Data System (ADS)

Isenor, Anthony W.; Allard, Yannick; Lapinski, Anna-Liesa S.; Demers, Hugues; Radulescu, Dan

2014-10-01

Unmanned Aerial Vehicles (UAVs) are being used by numerous nations for defence-related missions. In some cases, the UAV is considered a cost-effective means to acquire data such as imagery over a location or object. Considering Canada's geographic expanse, UAVs are also being suggested as a potential platform for use in surveillance of remote areas, such as northern Canada. However, such activities are typically associated with security as opposed to defence. The use of a defence platform for security activities introduces the issue of information exchange between the defence and security communities and their software applications. This paper explores the flow of information from the system used by the UAVs employed by the Royal Canadian Navy. Multiple computers are setup, each with the information system used by the UAVs, including appropriate communication between the systems. Simulated data that may be expected from a typical maritime UAV mission is then fed into the information system. The information structures common to the Canadian security community are then used to store and transfer the simulated data. The resulting data flow from the defence-oriented UAV system to the security-oriented information structure is then displayed using an open source geospatial application. Use of the information structures and applications relevant to the security community avoids the distribution restrictions often associated with defence-specific applications.

Networking Multiple Autonomous Air and Ocean Vehicles for Oceanographic Research and Monitoring

NASA Astrophysics Data System (ADS)

McGillivary, P. A.; Borges de Sousa, J.; Rajan, K.

2013-12-01

Autonomous underwater and surface vessels (AUVs and ASVs) are coming into wider use as components of oceanographic research, including ocean observing systems. Unmanned airborne vehicles (UAVs) are now available at modest cost, allowing multiple UAVs to be deployed with multiple AUVs and ASVs. For optimal use good communication and coordination among vehicles is essential. We report on the use of multiple AUVs networked in communication with multiple UAVs. The UAVs are augmented by inferential reasoning software developed at MBARI that allows UAVs to recognize oceanographic fronts and change their navigation and control. This in turn allows UAVs to automatically to map frontal features, as well as to direct AUVs and ASVs to proceed to such features and conduct sampling via onboard sensors to provide validation for airborne mapping. ASVs can also act as data nodes for communication between UAVs and AUVs, as well as collecting data from onboard sensors, while AUVs can sample the water column vertically. This allows more accurate estimation of phytoplankton biomass and productivity, and can be used in conjunction with UAV sampling to determine air-sea flux of gases (e.g. CO2, CH4, DMS) affecting carbon budgets and atmospheric composition. In particular we describe tests in July 2013 conducted off Sesimbra, Portugal in conjunction with the Portuguese Navy by the University of Porto and MBARI with the goal of tracking large fish in the upper water column with coordinated air/surface/underwater measurements. A thermal gradient was observed in the infrared by a low flying UAV, which was used to dispatch an AUV to obtain ground truth to demonstrate the event-response capabilities using such autonomous platforms. Additional field studies in the future will facilitate integration of multiple unmanned systems into research vessel operations. The strength of hardware and software tools described in this study is to permit fundamental oceanographic measurements of both ocean

Using Distance Sensors to Perform Collision Avoidance Maneuvres on Uav Applications

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

Contingency Software in Autonomous Systems: Technical Level Briefing

NASA Technical Reports Server (NTRS)

Lutz, Robyn R.; Patterson-Hines, Ann

2006-01-01

Contingency management is essential to the robust operation of complex systems such as spacecraft and Unpiloted Aerial Vehicles (UAVs). Automatic contingency handling allows a faster response to unsafe scenarios with reduced human intervention on low-cost and extended missions. Results, applied to the Autonomous Rotorcraft Project and Mars Science Lab, pave the way to more resilient autonomous systems.

Vision-based sensing for autonomous in-flight refueling

NASA Astrophysics Data System (ADS)

Scott, D.; Toal, M.; Dale, J.

2007-04-01

A significant capability of unmanned airborne vehicles (UAV's) is that they can operate tirelessly and at maximum efficiency in comparison to their human pilot counterparts. However a major limiting factor preventing ultra-long endurance missions is that they require landing to refuel. Development effort has been directed to allow UAV's to automatically refuel in the air using current refueling systems and procedures. The 'hose & drogue' refueling system was targeted as it is considered the more difficult case. Recent flight trials resulted in the first-ever fully autonomous airborne refueling operation. Development has gone into precision GPS-based navigation sensors to maneuver the aircraft into the station-keeping position and onwards to dock with the refueling drogue. However in the terminal phases of docking, the accuracy of the GPS is operating at its performance limit and also disturbance factors on the flexible hose and basket are not predictable using an open-loop model. Hence there is significant uncertainty on the position of the refueling drogue relative to the aircraft, and is insufficient in practical operation to achieve a successful and safe docking. A solution is to augment the GPS based system with a vision-based sensor component through the terminal phase to visually acquire and track the drogue in 3D space. The higher bandwidth and resolution of camera sensors gives significantly better estimates on the state of the drogue position. Disturbances in the actual drogue position caused by subtle aircraft maneuvers and wind gusting can be visually tracked and compensated for, providing an accurate estimate. This paper discusses the issues involved in visually detecting a refueling drogue, selecting an optimum camera viewpoint, and acquiring and tracking the drogue throughout a widely varying operating range and conditions.

Towards a New Architecture for Autonomous Data Collection

NASA Astrophysics Data System (ADS)

Tanzi, T. J.; Roudier, Y.; Apvrille, L.

2015-08-01

A new generation of UAVs is coming that will help improve the situational awareness and assessment necessary to ensure quality data collection, especially in difficult conditions like natural disasters. Operators should be relieved from time-consuming data collection tasks as much as possible and at the same time, UAVs should assist data collection operations through a more insightful and automated guidance thanks to advanced sensing capabilities. In order to achieve this vision, two challenges must be addressed though. The first one is to achieve a sufficient autonomy, both in terms of navigation and of interpretation of the data sensed. The second one relates to the reliability of the UAV with respect to accidental (safety) or even malicious (security) risks. This however requires the design and development of new embedded architectures for drones to be more autonomous, while mitigating the harm they may potentially cause. We claim that the increased complexity and flexibility of such platforms requires resorting to modelling, simulation, or formal verification techniques in order to validate such critical aspects of the platform. This paper first discusses the potential and challenges faced by autonomous UAVs for data acquisition. The design of a flexible and adaptable embedded UAV architecture is then addressed. Finally, the need for validating the properties of the platform is discussed. Our approach is sketched and illustrated with the example of a lightweight drone performing 3D reconstructions out of the combination of 2D image acquisition and a specific motion control.

UAV Trajectory Modeling Using Neural Networks

NASA Technical Reports Server (NTRS)

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

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

PubMed Central

Vetrella, Amedeo Rodi; Fasano, Giancarmine; Accardo, Domenico; Moccia, Antonio

2016-01-01

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. PMID:27999318

UAV-based remote sensing of the Heumoes landslide, Austria Vorarlberg

NASA Astrophysics Data System (ADS)

Niethammer, U.; Joswig, M.

2009-04-01

The Heumoes landslide, is located in the eastern Vorarlberg Alps, Austria, 10 km southeast of Dornbirn. The extension of the landslide is about 2000 m in west to east direction and about 500 m at its widest extent in north to south direction. It occurs between an elevation of 940 m in the east and 1360 m in the west, slope angles of more than 60 % can be observed as well as almost flat areas. Its total volume is estimated to be 9.400.000 cubic meters and its average velocities amount to some centimeter per year. Surface signatures or 'photolineations' of creeping landslides, e.g. fractures and rupture lines in sediments and street pavings, and vegetation contrasts by changes of water table in shallow vegetation in principle can be resolved by remote sensing. The necessary ground cell resolution of few centimeters, however, generally can't be achieved by routine areal or satellite imagery. The fast technological progress of unmanned areal vehicles (UAV) and the reduced payload by miniaturized optical cameras now allow for UAV remote sensing applications that are below the high financial limits of military intelligence. Even with 'low-cost' equipment, the necessary centimeter-scale ground cell resolution can be achieved by adapting the flight altitude to some ten to one hundred meters. Operated by scientists experienced in remote-control flight models, UAV remote sensing can now be performed routinely, and campaign-wise after any significant event of, e.g., heavy rainfall, or partial mudflow. We have investigated a concept of UAV-borne remote sensing based on motorized gliders, and four-propeller helicopters or 'quad-rotors'. Several missions were flown over the Heumoes landslide. Between 2006 and 2008 three series UAV-borne photographs of the Heumoes landslide were taken and could be combined to orto-mosaics of the slope area within few centimeters ground cell resolution. We will present the concept of our low cost quad-rotor UAV system and first results of the

The Practical Application of Uav-Based Photogrammetry Under Economic Aspects

NASA Astrophysics Data System (ADS)

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

Advanced Broadband Links for TIER III UAV Data Communication

NASA Astrophysics Data System (ADS)

Griethe, Wolfgang; Gregory, Mark; Heine, Frank; Kampfner, Hartmut

2011-08-01

Unmanned Aeronautical Vehicle (UAV) are getting more and more importance because of their prominent role as national reconnaissance systems, for disaster monitoring, and environmental mapping. However, the existence of reliable and robust data links are indispensable for Unmanned Aircraft System (UAS) missions. In particular for Beyond Line-Of-Sight operations (BLOS) of Tier III UAVs, satellite data links are a key element since extensive sensor data have to be transmitted preferably in real-time or near real-time.The paper demonstrates that the continuously increasing number of UAS and the intensified use of high resolution sensors will reveal RF-bandwidth as a limitating factor in the communication chain of Tier III UAVs. The RF-bandwidth gap can be partly closed by use of high-order modulation, of course, but much more progress in terms of bandwidth allocation can be achieved by using optical transmission technology. Consequently, the paper underlines that meanwhile this technology has been sufficiently verified in space, and shows that optical links are suited as well for broadband communications of Tier III UAVs. Moreover, the advantages of LaserCom in UAV scenarios and its importance for Network Centric Warfare (NCW) as well as for Command, Control, Communications, Computers, Intelligens, Surveillance, and Reconnaissance (C4ISR) are emphasized. Numerous practical topics and design requirements, relevant for the establishment of optical links onboard of Tier III UAVs, are discussed.

Semiautonomous Avionics-and-Sensors System for a UAV

NASA Technical Reports Server (NTRS)

Shams, Qamar

2006-01-01

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

Robust Vision-Based Pose Estimation Algorithm for AN Uav with Known Gravity Vector

NASA Astrophysics Data System (ADS)

Kniaz, V. V.

2016-06-01

Accurate estimation of camera external orientation with respect to a known object is one of the central problems in photogrammetry and computer vision. In recent years this problem is gaining an increasing attention in the field of UAV autonomous flight. Such application requires a real-time performance and robustness of the external orientation estimation algorithm. The accuracy of the solution is strongly dependent on the number of reference points visible on the given image. The problem only has an analytical solution if 3 or more reference points are visible. However, in limited visibility conditions it is often needed to perform external orientation with only 2 visible reference points. In such case the solution could be found if the gravity vector direction in the camera coordinate system is known. A number of algorithms for external orientation estimation for the case of 2 known reference points and a gravity vector were developed to date. Most of these algorithms provide analytical solution in the form of polynomial equation that is subject to large errors in the case of complex reference points configurations. This paper is focused on the development of a new computationally effective and robust algorithm for external orientation based on positions of 2 known reference points and a gravity vector. The algorithm implementation for guidance of a Parrot AR.Drone 2.0 micro-UAV is discussed. The experimental evaluation of the algorithm proved its computational efficiency and robustness against errors in reference points positions and complex configurations.

Uav Photogrammetry: Block Triangulation Comparisons

NASA Astrophysics Data System (ADS)

Gini, R.; Pagliari, D.; Passoni, D.; Pinto, L.; Sona, G.; Dosso, P.

2013-08-01

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.

The Altus Cumulus Electrification Study (ACES): A UAV-Based Science Demonstration

NASA Technical Reports Server (NTRS)

Blakeslee, R. J.; Croskey, C. L.; Desch, M. D.; Farrell, W. M.; Goldberg, R. A.; Houser, J. G.; Kim, H. S.; Mach, D. M.; Mitchell, J. D.; Stoneburner, J. C.

2003-01-01

The Altus Cumulus Electrification Study (ACES) is an unmanned aerial vehicle (UAV)- based project that investigated thunderstorms in the vicinity of the Florida Everglades in August 2002. ACES was conducted to investigate storm electrical activity and its relationship to storm morphology, and to validate satellite-based lightning measurements. In addition, as part of the NASA sponsored UAV-based science demonstration program, this project provided a scientifically useful demonstration of the utility and promise of UAV platforms for Earth science and applications observations. ACES employed the Altus II aircraft, built by General Atomics - Aeronautical Systems, Inc. Key science objectives simultaneously addressed by ACES are to: (1) investigate lightning-storm relationships, (2) study storm electrical budgets, and provide Lightning Imaging Sensor validation. The ACES payload included electrical, magnetic, and optical sensors to remotely characterize the lightning activity and the electrical environment within and around thunderstorms. ACES contributed important electrical and optical measurements not available from other sources. Also, the high altitude vantage point of the UAV observing platform (up to 55,000 feet) provided cloud-top perspective. By taking advantage of its slow flight speed (70 to 100 knots), long endurance, and high altitude flight, the Altus was flown near, and when possible, over (but never into) thunderstorms for long periods of time that allowed investigations to be conducted over entire storm life cycles. An innovative real time weather system was used to identify and vector the aircraft to selected thunderstorms and safely fly around these storms, while, at the same time monitor the weather near our base of operations. In addition, concurrent ground-based observations that included radar (Miami and Key West WSRBD, NASA NPOL), satellite imagery, and lightning (NALDN and Los Alamos EDOT) enable the UAV measurements to be more completely

AVALON: definition and modeling of a vertical takeoff and landing UAV

NASA Astrophysics Data System (ADS)

Silva, N. B. F.; Marconato, E. A.; Branco, K. R. L. J. C.

2015-09-01

Unmanned Aerial Vehicles (UAVs) have been used in numerous applications, like remote sensing, precision agriculture and atmospheric data monitoring. Vertical takeoff and landing (VTOL) is a modality of these aircrafts, which are capable of taking off and landing vertically, like a helicopter. This paper presents the definition and modeling of a fixed- wing VTOL, named AVALON (Autonomous VerticAL takeOff and laNding), which has the advantages of traditional aircrafts with improved performance and can take off and land in small areas. The principles of small UAVs development were followed to achieve a better design and to increase the range of applications for this VTOL. Therefore, we present the design model of AVALON validated in a flight simulator and the results show its validity as a physical option for an UAV platform.

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

NASA Astrophysics Data System (ADS)

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

Vision Based Obstacle Detection in Uav Imaging

NASA Astrophysics Data System (ADS)

Badrloo, S.; Varshosaz, M.

2017-08-01

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.

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

NASA Astrophysics Data System (ADS)

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.

A method of fast mosaic for massive UAV images

NASA Astrophysics Data System (ADS)

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

2014-11-01

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

3-D model-based tracking for UAV indoor localization.

PubMed

Teulière, Céline; Marchand, Eric; Eck, Laurent

2015-05-01

This paper proposes a novel model-based tracking approach for 3-D localization. One main difficulty of standard model-based approach lies in the presence of low-level ambiguities between different edges. In this paper, given a 3-D model of the edges of the environment, we derive a multiple hypotheses tracker which retrieves the potential poses of the camera from the observations in the image. We also show how these candidate poses can be integrated into a particle filtering framework to guide the particle set toward the peaks of the distribution. Motivated by the UAV indoor localization problem where GPS signal is not available, we validate the algorithm on real image sequences from UAV flights.

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

NASA Astrophysics Data System (ADS)

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.

Approach for Autonomous Control of Unmanned Aerial Vehicle Using Intelligent Agents for Knowledge Creation

NASA Technical Reports Server (NTRS)

Dufrene, Warren R., Jr.

2004-01-01

This paper describes the development of a planned approach for Autonomous operation of an Unmanned Aerial Vehicle (UAV). A Hybrid approach will seek to provide Knowledge Generation thru the application of Artificial Intelligence (AI) and Intelligent Agents (IA) for UAV control. The application of many different types of AI techniques for flight will be explored during this research effort. The research concentration will be directed to the application of different AI methods within the UAV arena. By evaluating AI approaches, which will include Expert Systems, Neural Networks, Intelligent Agents, Fuzzy Logic, and Complex Adaptive Systems, a new insight may be gained into the benefits of AI techniques applied to achieving true autonomous operation of these systems thus providing new intellectual merit to this research field. The major area of discussion will be limited to the UAV. The systems of interest include small aircraft, insects, and miniature aircraft. Although flight systems will be explored, the benefits should apply to many Unmanned Vehicles such as: Rovers, Ocean Explorers, Robots, and autonomous operation systems. The flight system will be broken down into control agents that will represent the intelligent agent approach used in AI. After the completion of a successful approach, a framework of applying a Security Overseer will be added in an attempt to address errors, emergencies, failures, damage, or over dynamic environment. The chosen control problem was the landing phase of UAV operation. The initial results from simulation in FlightGear are presented.

Development and Testing of a Two-UAV Communication Relay System.

PubMed

Li, Boyang; Jiang, Yifan; Sun, Jingxuan; Cai, Lingfeng; Wen, Chih-Yung

2016-10-13

In the development of beyond-line-of-sight (BLOS) Unmanned Aerial Vehicle (UAV) systems, communication between the UAVs and the ground control station (GCS) is of critical importance. The commonly used economical wireless modules are restricted by the short communication range and are easily blocked by obstacles. The use of a communication relay system provides a practical way to solve these problems, improving the performance of UAV communication in BLOS and cross-obstacle operations. In this study, a communication relay system, in which a quadrotor was used to relay radio communication for another quadrotor was developed and tested. First, the UAVs used as the airborne platform were constructed, and the hardware for the communication relay system was selected and built up. Second, a set of software programs and protocol for autonomous mission control, communication relay control, and ground control were developed. Finally, the system was fully integrated into the airborne platform and tested both indoor and in-flight. The Received Signal Strength Indication (RSSI) and noise value in two typical application scenarios were recorded. The test results demonstrated the ability of this system to extend the communication range and build communication over obstacles. This system also shows the feasibility to coordinate multiple UAVs' communication with the same relay structure.

Multimodal UAV detection: study of various intrusion scenarios

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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.

Simulation to Flight Test for a UAV Controls Testbed

NASA Technical Reports Server (NTRS)

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.

Annotation of UAV surveillance video

NASA Astrophysics Data System (ADS)

Howlett, Todd; Robertson, Mark A.; Manthey, Dan; Krol, John

2004-08-01

Significant progress toward the development of a video annotation capability is presented in this paper. Research and development of an object tracking algorithm applicable for UAV video is described. Object tracking is necessary for attaching the annotations to the objects of interest. A methodology and format is defined for encoding video annotations using the SMPTE Key-Length-Value encoding standard. This provides the following benefits: a non-destructive annotation, compliance with existing standards, video playback in systems that are not annotation enabled and support for a real-time implementation. A model real-time video annotation system is also presented, at a high level, using the MPEG-2 Transport Stream as the transmission medium. This work was accomplished to meet the Department of Defense"s (DoD"s) need for a video annotation capability. Current practices for creating annotated products are to capture a still image frame, annotate it using an Electric Light Table application, and then pass the annotated image on as a product. That is not adequate for reporting or downstream cueing. It is too slow and there is a severe loss of information. This paper describes a capability for annotating directly on the video.

Automated geographic registration and radiometric correction for UAV-based mosaics

NASA Astrophysics Data System (ADS)

Thomasson, J. Alex; Shi, Yeyin; Sima, Chao; Yang, Chenghai; Cope, Dale A.

2017-05-01

Texas A and 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 science-based utilization of such mosaics are geographic registration and radiometric calibration. In our current research project, image files are taken to the computer laboratory after the flight, and semi-manual pre-processing is implemented on the raw image data, including ortho-mosaicking and radiometric calibration. Ground control points (GCPs) are critical for high-quality geographic registration of images during mosaicking. Applications requiring accurate reflectance data also require radiometric-calibration references so that reflectance values of image objects can be calculated. We have developed a method for automated geographic registration and radiometric correction with targets that are installed semi-permanently at distributed locations around fields. The targets are a combination of black (≍5% reflectance), dark gray (≍20% reflectance), and light gray (≍40% reflectance) sections that provide for a transformation of pixel-value to reflectance in the dynamic range of crop fields. The exact spectral reflectance of each target is known, having been measured with a spectrophotometer. At the time of installation, each target is measured for position with a real-time kinematic GPS receiver to give its precise latitude and longitude. Automated location of the reference targets in the images is required for precise, automated, geographic registration; and automated calculation of the digital-number to reflectance transformation is required for automated radiometric calibration. To validate the system for radiometric calibration, a calibrated UAV-based image mosaic of a field was compared to a calibrated single image from a manned aircraft. Reflectance

UAV-borne lidar with MEMS mirror-based scanning capability

NASA Astrophysics Data System (ADS)

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 <90mm x 60mm x 40mm, weighing less than 40g and consuming less than 750mW of power using a ~5mW laser. This MEMS scan module was controlled by a 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 <70mm x 60mm x 60mm, and weigh <50g when powered by the UAV's 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.

Determination of UAV pre-flight Checklist for flight test purpose using qualitative failure analysis

NASA Astrophysics Data System (ADS)

Hendarko; Indriyanto, T.; Syardianto; Maulana, F. A.

2018-05-01

Safety aspects are of paramount importance in flight, especially in flight test phase. Before performing any flight tests of either manned or unmanned aircraft, one should include pre-flight checklists as a required safety document in the flight test plan. This paper reports on the development of a new approach for determination of pre-flight checklists for UAV flight test based on aircraft’s failure analysis. The Lapan’s LSA (Light Surveillance Aircraft) is used as a study case, assuming this aircraft has been transformed into the unmanned version. Failure analysis is performed on LSA using fault tree analysis (FTA) method. Analysis is focused on propulsion system and flight control system, which fail of these systems will lead to catastrophic events. Pre-flight checklist of the UAV is then constructed based on the basic causes obtained from failure analysis.

Change Detection in Uav Video Mosaics Combining a Feature Based Approach and Extended Image Differencing

NASA Astrophysics Data System (ADS)

Saur, Günter; Krüger, Wolfgang

2016-06-01

Change detection is an important task when using unmanned aerial vehicles (UAV) for video surveillance. We address changes of short time scale using observations in time distances of a few hours. Each observation (previous and current) is a short video sequence acquired by UAV in near-Nadir view. Relevant changes are, e.g., recently parked or moved vehicles. Examples for non-relevant changes are parallaxes caused by 3D structures of the scene, shadow and illumination changes, and compression or transmission artifacts. In this paper we present (1) a new feature based approach to change detection, (2) a combination with extended image differencing (Saur et al., 2014), and (3) the application to video sequences using temporal filtering. In the feature based approach, information about local image features, e.g., corners, is extracted in both images. The label "new object" is generated at image points, where features occur in the current image and no or weaker features are present in the previous image. The label "vanished object" corresponds to missing or weaker features in the current image and present features in the previous image. This leads to two "directed" change masks and differs from image differencing where only one "undirected" change mask is extracted which combines both label types to the single label "changed object". The combination of both algorithms is performed by merging the change masks of both approaches. A color mask showing the different contributions is used for visual inspection by a human image interpreter.

Unmanned Aerial Vehicles unique cost estimating requirements

NASA Astrophysics Data System (ADS)

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

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

Research on the attitude of small UAV based on MEMS devices

NASA Astrophysics Data System (ADS)

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.

Position-adaptive explosive detection concepts for swarming micro-UAVs

NASA Astrophysics Data System (ADS)

Selmic, Rastko R.; Mitra, Atindra

2008-04-01

We have formulated a series of position-adaptive sensor concepts for explosive detection applications using swarms of micro-UAV's. These concepts are a generalization of position-adaptive radar concepts developed for challenging conditions such as urban environments. For radar applications, this concept is developed with platforms within a UAV swarm that spatially-adapt to signal leakage points on the perimeter of complex clutter environments to collect information on embedded objects-of-interest. The concept is generalized for additional sensors applications by, for example, considering a wooden cart that contains explosives. We can formulate system-of-systems concepts for a swarm of micro-UAV's in an effort to detect whether or not a given cart contains explosives. Under this new concept, some of the members of the UAV swarm can serve as position-adaptive "transmitters" by blowing air over the cart and some of the members of the UAV swarm can serve as position-adaptive "receivers" that are equipped with chem./bio sensors that function as "electronic noses". The final objective can be defined as improving the particle count for the explosives in the air that surrounds a cart via development of intelligent position-adaptive control algorithms in order to improve the detection and false-alarm statistics. We report on recent simulation results with regard to designing optimal sensor placement for explosive or other chemical agent detection. This type of information enables the development of intelligent control algorithms for UAV swarm applications and is intended for the design of future system-of-systems with adaptive intelligence for advanced surveillance of unknown regions. Results are reported as part of a parametric investigation where it is found that the probability of contaminant detection depends on the air flow that carries contaminant particles, geometry of the surrounding space, leakage areas, and other factors. We present a concept of position

User evaluation of a GUI for controlling an autonomous persistent surveillance team

NASA Astrophysics Data System (ADS)

Scerri, Paul; Owens, Sean; Sycara, Katia; Lewis, Michael

2010-04-01

In future military missions, there will be many sensor assets collecting much important information about the environment. User control over surveillance assets is important to ensure that the specific data collected is appropriate for the current mission. Unfortunately, previous work has shown that individual users cannot effectively control more than about four assets, even if the assets have significant autonomy. In the ACCAST project, we hypothesized that by including autonomous teamwork between the assets and allowing users to interact by describing what the team as a whole and specific sub-teams should do, we could dramatically scale up the number of assets an individual user could effectively control. In this paper, we present the results of an experiment where users controlled up to 30 autonomous assets performing a complex mission. The assets autonomously worked together using sophisticated teamwork and the user could tell sub-teams to execute team oriented plans which described the steps required to achieve a team objective without describing exactly which asset performed which role and without having to specify how the team should handle routine information sharing, communications and failure circumstances. The users, soldiers from Fort Benning, were surprisingly good at managing the assets and were all able to complete the complex mission with extremely low friendly and civilian casualties.

Unmanned air vehicle (UAV) ultra-persitence research

DOE Office of Scientific and Technical Information (OSTI.GOV)

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.« less

Control and design of multiple unmanned air vehicles for persistent surveillance

NASA Astrophysics Data System (ADS)

Nigam, Nikhil

Control of multiple autonomous aircraft for search and exploration, is a topic of current research interest for applications such as weather monitoring, geographical surveys, search and rescue, tactical reconnaissance, and extra-terrestrial exploration, and the need to distribute sensing is driven by considerations of efficiency, reliability, cost and scalability. Hence, this problem has been extensively studied in the fields of controls and artificial intelligence. The task of persistent surveillance is different from a coverage/exploration problem, in that all areas need to be continuously searched, minimizing the time between visitations to each region in the target space. This distinction does not allow a straightforward application of most exploration techniques to the problem, although ideas from these methods can still be used. The use of aerial vehicles is motivated by their ability to cover larger spaces and their relative insensitivity to terrain. However, the dynamics of Unmanned Air Vehicles (UAVs) adds complexity to the control problem. Most of the work in the literature decouples the vehicle dynamics and control policies, but their interaction is particularly interesting for a surveillance mission. Stochastic environments and UAV failures further enrich the problem by requiring the control policies to be robust, and this aspect is particularly important for hardware implementations. For a persistent mission, it becomes imperative to consider the range/endurance constraints of the vehicles. The coupling of the control policy with the endurance constraints of the vehicles is an aspect that has not been sufficiently explored. Design of UAVs for desirable mission performance is also an issue of considerable significance. The use of a single monolithic optimization for such a problem has practical limitations, and decomposition-based design is a potential alternative. In this research high-level control policies are devised, that are scalable, reliable

Development and Validation of a UAV Based System for Air Pollution Measurements

PubMed Central

Villa, Tommaso Francesco; Salimi, Farhad; Morton, Kye; Morawska, Lidia; Gonzalez, Felipe

2016-01-01

Air quality data collection near pollution sources is difficult, particularly when sites are complex, have physical barriers, or are themselves moving. Small Unmanned Aerial Vehicles (UAVs) offer new approaches to air pollution and atmospheric studies. However, there are a number of critical design decisions which need to be made to enable representative data collection, in particular the location of the air sampler or air sensor intake. The aim of this research was to establish the best mounting point for four gas sensors and a Particle Number Concentration (PNC) monitor, onboard a hexacopter, so to develop a UAV system capable of measuring point source emissions. The research included two different tests: (1) evaluate the air flow behavior of a hexacopter, its downwash and upwash effect, by measuring air speed along three axes to determine the location where the sensors should be mounted; (2) evaluate the use of gas sensors for CO2, CO, NO2 and NO, and the PNC monitor (DISCmini) to assess the efficiency and performance of the UAV based system by measuring emissions from a diesel engine. The air speed behavior map produced by test 1 shows the best mounting point for the sensors to be alongside the UAV. This position is less affected by the propeller downwash effect. Test 2 results demonstrated that the UAV propellers cause a dispersion effect shown by the decrease of gas and PN concentration measured in real time. A Linear Regression model was used to estimate how the sensor position, relative to the UAV center, affects pollutant concentration measurements when the propellers are turned on. This research establishes guidelines on how to develop a UAV system to measure point source emissions. Such research should be undertaken before any UAV system is developed for real world data collection. PMID:28009820

Development and Validation of a UAV Based System for Air Pollution Measurements.

PubMed

Villa, Tommaso Francesco; Salimi, Farhad; Morton, Kye; Morawska, Lidia; Gonzalez, Felipe

2016-12-21

Air quality data collection near pollution sources is difficult, particularly when sites are complex, have physical barriers, or are themselves moving. Small Unmanned Aerial Vehicles (UAVs) offer new approaches to air pollution and atmospheric studies. However, there are a number of critical design decisions which need to be made to enable representative data collection, in particular the location of the air sampler or air sensor intake. The aim of this research was to establish the best mounting point for four gas sensors and a Particle Number Concentration (PNC) monitor, onboard a hexacopter, so to develop a UAV system capable of measuring point source emissions. The research included two different tests: (1) evaluate the air flow behavior of a hexacopter, its downwash and upwash effect, by measuring air speed along three axes to determine the location where the sensors should be mounted; (2) evaluate the use of gas sensors for CO₂, CO, NO₂ and NO, and the PNC monitor (DISCmini) to assess the efficiency and performance of the UAV based system by measuring emissions from a diesel engine. The air speed behavior map produced by test 1 shows the best mounting point for the sensors to be alongside the UAV. This position is less affected by the propeller downwash effect. Test 2 results demonstrated that the UAV propellers cause a dispersion effect shown by the decrease of gas and PN concentration measured in real time. A Linear Regression model was used to estimate how the sensor position, relative to the UAV center, affects pollutant concentration measurements when the propellers are turned on. This research establishes guidelines on how to develop a UAV system to measure point source emissions. Such research should be undertaken before any UAV system is developed for real world data collection.

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

PubMed Central

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

2017-01-01

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: σB=1.63×10−4 (°), σL=1.35×10−4 (°), σH=15.8 (m), σsum=27.6 (m), where σB represents the longitude error, σL represents the latitude error, σH represents the altitude error, and σsum represents the error radius. PMID:28067814

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

PubMed

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.

Autonomous Inspection of Electrical Transmission Structures with Airborne UV Sensors - NASA Report on Dominion Virginia Power Flights of November 2016

NASA Technical Reports Server (NTRS)

Moore, Andrew J.; Schubert, Matthew; Nicholas Rymer

2017-01-01

The report details test and measurement flights to demonstrate autonomous UAV inspection of high voltage electrical transmission structures. A UAV built with commercial, off-the-shelf hardware and software, supplemented with custom sensor logging software, measured ultraviolet emissions from a test generator placed on a low-altitude substation and a medium-altitude switching tower. Since corona discharge precedes catastrophic electrical faults on high-voltage structures, detection and geolocation of ultraviolet emissions is needed to develop a UAV-based self-diagnosing power grid. Signal readings from an onboard ultraviolet sensor were validated during flight with a commercial corona camera. Geolocation was accomplished with onboard GPS; the UAV position was logged to a local ground station and transmitted in real time to a NASA server for tracking in the national airspace.

Evaluating the accuracy of orthophotos and 3D models from UAV photogrammetry

NASA Astrophysics Data System (ADS)

Julge, Kalev; Ellmann, Artu

2015-04-01

Rapid development of unmanned aerial vehicles (UAV) in recent years has made their use for various applications more feasible. This contribution evaluates the accuracy and quality of different UAV remote sensing products (i.e. orthorectified image, point cloud and 3D model). Two different autonomous fixed wing UAV systems were used to collect the aerial photographs. One is a mass-produced commercial UAV system, the other is a similar state-of-the-art UAV system. Three different study areas with varying sizes and characteristics (including urban areas, forests, fields, etc.) were surveyed. The UAV point clouds, 3D models and orthophotos were generated with three different commercial and free-ware software. The performance of each of these was evaluated. The effect of flying height on the accuracy of the results was explored, as well as the optimum number and placement of ground control points. Also the achieved results, when the only georeferencing data originates from the UAV system's on-board GNSS and inertial measurement unit, are investigated. Problems regarding the alignment of certain types of aerial photos (e.g. captured over forested areas) are discussed. The quality and accuracy of UAV photogrammetry products are evaluated by comparing them with control measurements made with GNSS-measurements on the ground, as well as high-resolution airborne laser scanning data and other available orthophotos (e.g. those acquired for large scale national mapping). Vertical comparisons are made on surfaces that have remained unchanged in all campaigns, e.g. paved roads. Planar comparisons are performed by control surveys of objects that are clearly identifiable on orthophotos. The statistics of these differences are used to evaluate the accuracy of UAV remote sensing. Some recommendations are given on how to conduct UAV mapping campaigns cost-effectively and with minimal time-consumption while still ensuring the quality and accuracy of the UAV data products. Also the

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

NASA Astrophysics Data System (ADS)

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 (< 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.

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

NASA Astrophysics Data System (ADS)

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.

Searching Lost People with Uavs: the System and Results of the Close-Search Project

NASA Astrophysics Data System (ADS)

Molina, P.; Colomina, I.; Vitoria, T.; Silva, P. F.; Skaloud, J.; Kornus, W.; Prades, R.; Aguilera, C.

2012-07-01

This paper will introduce the goals, concept and results of the project named CLOSE-SEARCH, which stands for 'Accurate and safe EGNOS-SoL Navigation for UAV-based low-cost Search-And-Rescue (SAR) operations'. The main goal is to integrate a medium-size, helicopter-type Unmanned Aerial Vehicle (UAV), a thermal imaging sensor and an EGNOS-based multi-sensor navigation system, including an Autonomous Integrity Monitoring (AIM) capability, to support search operations in difficult-to-access areas and/or night operations. The focus of the paper is three-fold. Firstly, the operational and technical challenges of the proposed approach are discussed, such as ultra-safe multi-sensor navigation system, the use of combined thermal and optical vision (infrared plus visible) for person recognition and Beyond-Line-Of-Sight communications among others. Secondly, the implementation of the integrity concept for UAV platforms is discussed herein through the AIM approach. Based on the potential of the geodetic quality analysis and on the use of the European EGNOS system as a navigation performance starting point, AIM approaches integrity from the precision standpoint; that is, the derivation of Horizontal and Vertical Protection Levels (HPLs, VPLs) from a realistic precision estimation of the position parameters is performed and compared to predefined Alert Limits (ALs). Finally, some results from the project test campaigns are described to report on particular project achievements. Together with actual Search-and-Rescue teams, the system was operated in realistic, user-chosen test scenarios. In this context, and specially focusing on the EGNOS-based UAV navigation, the AIM capability and also the RGB/thermal imaging subsystem, a summary of the results is presented.

Pricise Target Geolocation and Tracking Based on Uav Video Imagery

NASA Astrophysics Data System (ADS)

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.

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

PubMed

Hocraffer, Amy; Nam, Chang S

2017-01-01

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

Guidance and Control of a Small Unmanned Aerial Vehicle and Autonomous Flight Experiments

NASA Astrophysics Data System (ADS)

Fujinaga, Jin; Tokutake, Hiroshi; Sunada, Shigeru

This paper describes the development of a fixed-wing small-size UAV and the design of its flight controllers. The developed UAV’s wing span is 0.6m, and gross weight is 0.27kg. In order to ensure robust performances of the longitudinal and lateral-directional motions of the UAV, flight controllers are designed for these motions with μ-synthesis. Numerical simulations show that the designed controllers attain good robust stabilities and performances, and have good tracking performance for command. After an order-reduction and discretization, the designed flight controllers were implemented in the UAV. A flight test was performed, and the ability of the UAV to fly autonomously, passing over waypoints, was demonstrated.

Approach for Autonomous Control of Unmanned Aerial Vehicle Using Intelligent Agents for Knowledge Creation

NASA Technical Reports Server (NTRS)

Dufrene, Warren R., Jr.

2004-01-01

This paper describes the development of a planned approach for Autonomous operation of an Unmanned Aerial Vehicle (UAV). A Hybrid approach will seek to provide Knowledge Generation through the application of Artificial Intelligence (AI) and Intelligent Agents (IA) for UAV control. The applications of several different types of AI techniques for flight are explored during this research effort. The research concentration is directed to the application of different AI methods within the UAV arena. By evaluating AI and biological system approaches. which include Expert Systems, Neural Networks. Intelligent Agents, Fuzzy Logic, and Complex Adaptive Systems, a new insight may be gained into the benefits of AI and CAS techniques applied to achieving true autonomous operation of these systems. Although flight systems were explored, the benefits should apply to many Unmanned Vehicles such as: Rovers. Ocean Explorers, Robots, and autonomous operation systems. A portion of the flight system is broken down into control agents that represent the intelligent agent approach used in AI. After the completion of a successful approach, a framework for applying an intelligent agent is presented. The initial results from simulation of a security agent for communication are presented.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

UAV field demonstration of social media enabled tactical data link

NASA Astrophysics Data System (ADS)

Olson, Christopher C.; Xu, Da; Martin, Sean R.; Castelli, Jonathan C.; Newman, Andrew J.

2015-05-01

This paper addresses the problem of enabling Command and Control (C2) and data exfiltration functions for missions using small, unmanned, airborne surveillance and reconnaissance platforms. The authors demonstrated the feasibility of using existing commercial wireless networks as the data transmission infrastructure to support Unmanned Aerial Vehicle (UAV) autonomy functions such as transmission of commands, imagery, metadata, and multi-vehicle coordination messages. The authors developed and integrated a C2 Android application for ground users with a common smart phone, a C2 and data exfiltration Android application deployed on-board the UAVs, and a web server with database to disseminate the collected data to distributed users using standard web browsers. The authors performed a mission-relevant field test and demonstration in which operators commanded a UAV from an Android device to search and loiter; and remote users viewed imagery, video, and metadata via web server to identify and track a vehicle on the ground. Social media served as the tactical data link for all command messages, images, videos, and metadata during the field demonstration. Imagery, video, and metadata were transmitted from the UAV to the web server via multiple Twitter, Flickr, Facebook, YouTube, and similar media accounts. The web server reassembled images and video with corresponding metadata for distributed users. The UAV autopilot communicated with the on-board Android device via on-board Bluetooth network.

Development and Testing of a Two-UAV Communication Relay System

PubMed Central

Li, Boyang; Jiang, Yifan; Sun, Jingxuan; Cai, Lingfeng; Wen, Chih-Yung

2016-01-01

In the development of beyond-line-of-sight (BLOS) Unmanned Aerial Vehicle (UAV) systems, communication between the UAVs and the ground control station (GCS) is of critical importance. The commonly used economical wireless modules are restricted by the short communication range and are easily blocked by obstacles. The use of a communication relay system provides a practical way to solve these problems, improving the performance of UAV communication in BLOS and cross-obstacle operations. In this study, a communication relay system, in which a quadrotor was used to relay radio communication for another quadrotor was developed and tested. First, the UAVs used as the airborne platform were constructed, and the hardware for the communication relay system was selected and built up. Second, a set of software programs and protocol for autonomous mission control, communication relay control, and ground control were developed. Finally, the system was fully integrated into the airborne platform and tested both indoor and in-flight. The Received Signal Strength Indication (RSSI) and noise value in two typical application scenarios were recorded. The test results demonstrated the ability of this system to extend the communication range and build communication over obstacles. This system also shows the feasibility to coordinate multiple UAVs’ communication with the same relay structure. PMID:27754369

UAV-based landslide deformation monitoring - first results from Corvara landslide

NASA Astrophysics Data System (ADS)

Thiebes, Benni; Tomelleri, Enrico; Mejia-Aguilar, Abraham; Schlögel, Romy; Darvishi, Mehdi; Remondino, Fabio; Toschi, Isabella; Rutzinger, Martin; Zieher, Thomas

2016-04-01

In recent years, unmanned aerial vehicles (UAVs) have been more frequently utilised to study geomorphological and natural hazard processes, including gravitational mass movements such as landslides. UAVs can be equipped with different sensors, e.g. photo cameras and laser scanners, and the data that can be achieved can substantially improve the monitoring and understanding of the involved natural processes. One of the main advantages of UAVs is their flexibility that allows for carrying out assessments of large areas in short periods of time and at much lower costs than other platforms, e.g. airplanes or helicopters. Thereby, UAVs represent an interesting technique to complement more traditional monitoring methods. Here we present some first results of the EUREGIO-funded LEMONADE project that is concerned with the combination and integration of novel and traditional landslide monitoring techniques. We carried out a series of UAV flights over a particularly active part of the Corvara landslide and acquired aerial imagery for quantitative assessments of the retrogressive enlargement of the landslide over recent years. Additional field surveys including terrestrial laser scanning, and UAV-based photogrammetry and laser scanning are scheduled for summer 2016. The Corvara landslide is a large complex earthflow in the Italian Dolomites that has been investigated by a wide range of methodologies over the past years. The landslide is characterised by movement patterns of greatly varying magnitude, ranging from annual rates of a few cm to more than 20 m. The current and past monitoring activities concentrated on GPS measurements as well as multi-temporal differential radar interferometry utilising artificial corner reflectors. Thereby, primarily punctual displacement data were achieved and spatial information on topographic and geomorphic changes were consequently sparse. For our photogrammetry study, we utilised a SoLeon octocopter equipped with a Ricoh GR 16.2 Megapixels

Small Autonomous Aircraft Servo Health Monitoring

NASA Technical Reports Server (NTRS)

Quintero, Steven

2008-01-01

Small air vehicles offer challenging power, weight, and volume constraints when considering implementation of system health monitoring technologies. In order to develop a testbed for monitoring the health and integrity of control surface servos and linkages, the Autonomous Aircraft Servo Health Monitoring system has been designed for small Uninhabited Aerial Vehicle (UAV) platforms to detect problematic behavior from servos and the air craft structures they control, This system will serve to verify the structural integrity of an aircraft's servos and linkages and thereby, through early detection of a problematic situation, minimize the chances of an aircraft accident. Embry-Riddle Aeronautical University's rotary-winged UAV has an Airborne Power management unit that is responsible for regulating, distributing, and monitoring the power supplied to the UAV's avionics. The current sensing technology utilized by the Airborne Power Management system is also the basis for the Servo Health system. The Servo Health system measures the current draw of the servos while the servos are in Motion in order to quantify the servo health. During a preflight check, deviations from a known baseline behavior can be logged and their causes found upon closer inspection of the aircraft. The erratic behavior nay include binding as a result of dirt buildup or backlash caused by looseness in the mechanical linkages. Moreover, the Servo Health system will allow elusive problems to be identified and preventative measures taken to avoid unnecessary hazardous conditions in small autonomous aircraft.

Feasibility study of a novel miniaturized spectral imaging system architecture in UAV surveillance

NASA Astrophysics Data System (ADS)

Liu, Shuyang; Zhou, Tao; Jia, Xiaodong; Cui, Hushan; Huang, Chengjun

2016-01-01

The spectral imaging technology is able to analysis the spectral and spatial geometric character of the target at the same time. To break through the limitation brought by the size, weight and cost of the traditional spectral imaging instrument, a miniaturized novel spectral imaging based on CMOS processing has been introduced in the market. This technology has enabled the possibility of applying spectral imaging in the UAV platform. In this paper, the relevant technology and the related possible applications have been presented to implement a quick, flexible and more detailed remote sensing system.

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

NASA Technical Reports Server (NTRS)

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

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

NASA Astrophysics Data System (ADS)

Gentry, D.; Guarro, M.; Demachkie, I. S.; Stumfall, I.; Dahlgren, R. P.

2016-12-01

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

Agent-Based Simulation and Analysis of a Defensive UAV Swarm Against an Enemy UAV Swarm

DTIC Science & Technology

2011-06-01

de Investigacion, Programas y Desarrollo de la Armada Armada de Chile CHILE 10. CAPT Jeffrey Kline, USN(ret.) Naval Postgraduate School Monterey, California 91 ...this de - fensive swarm system, an agent-based simulation model is developed, and appropriate designs of experiments and statistical analyses are... de - velopment and implementation of counter UAV technology from readily-available commercial products. The organization leverages the “largest

Guidance and Control of an Autonomous Soaring Vehicle with Flight Test Results

NASA Technical Reports Server (NTRS)

Allen, Michael J.

2007-01-01

A guidance and control method was developed to detect and exploit thermals for energy gain. Latency in energy rate estimation degraded performance. The concept of a UAV harvesting energy from the atmosphere has been shown to be feasible with existing technology. Many UAVs have similar mission constraints to birds and sailplanes. a) Surveillance; b) Point to point flight with minimal energy; and c) Increased ground speed.

High Resolution UAV-based Passive Microwave L-band Imaging of Soil Moisture

NASA Astrophysics Data System (ADS)

Gasiewski, A. J.; Stachura, M.; Elston, J.; McIntyre, E. M.

2013-12-01

Due to long electrical wavelengths and aperture size limitations the scaling of passive microwave remote sensing of soil moisture from spaceborne low-resolution applications to high resolution applications suitable for precision agriculture requires use of low flying aerial vehicles. This presentation summarizes a project to develop a commercial Unmanned Aerial Vehicle (UAV) hosting a precision microwave radiometer for mapping of soil moisture in high-value shallow root-zone crops. The project is based on the use of the Tempest electric-powered UAV and a compact digital L-band (1400-1427 MHz) passive microwave radiometer developed specifically for extremely small and lightweight aerial platforms or man-portable, tractor, or tower-based applications. Notable in this combination are a highly integrated UAV/radiometer antenna design and use of both the upwelling emitted signal from the surface and downwelling cold space signal for precise calibration using a lobe-correlating radiometer architecture. The system achieves a spatial resolution comparable to the altitude of the UAV above the ground while referencing upwelling measurements to the constant and well-known background temperature of cold space. The radiometer incorporates digital sampling and radio frequency interference mitigation along with infrared, near-infrared, and visible (red) sensors for surface temperature and vegetation biomass correction. This NASA-sponsored project is being developed both for commercial application in cropland water management, L-band satellite validation, and estuarian plume studies.

Design and evaluation of an autonomous, obstacle avoiding, flight control system using visual sensors

NASA Astrophysics Data System (ADS)

Crawford, Bobby Grant

In an effort to field smaller and cheaper Uninhabited Aerial Vehicles (UAVs), the Army has expressed an interest in an ability of the vehicle to autonomously detect and avoid obstacles. Current systems are not suitable for small aircraft. NASA Langley Research Center has developed a vision sensing system that uses small semiconductor cameras. The feasibility of using this sensor for the purpose of autonomous obstacle avoidance by a UAV is the focus of the research presented in this document. The vision sensor characteristics are modeled and incorporated into guidance and control algorithms designed to generate flight commands based on obstacle information received from the sensor. The system is evaluated by simulating the response to these flight commands using a six degree-of-freedom, non-linear simulation of a small, fixed wing UAV. The simulation is written using the MATLAB application and runs on a PC. Simulations were conducted to test the longitudinal and lateral capabilities of the flight control for a range of airspeeds, camera characteristics, and wind speeds. Results indicate that the control system is suitable for obstacle avoiding flight control using the simulated vision system. In addition, a method for designing and evaluating the performance of such a system has been developed that allows the user to easily change component characteristics and evaluate new systems through simulation.

Risk-Free Volcano Observations Using an Unmanned Autonomous Helicopter: seismic observations near the active vent of Sakurajima volcano, Japan

NASA Astrophysics Data System (ADS)

Ohminato, T.; Kaneko, T.; Koyama, T.; Yasuda, A.; Watanabe, A.; Takeo, M.; Honda, Y.; Kajiwara, K.; Kanda, W.; Iguchi, M.; Yanagisawa, T.

2010-12-01

Observations in the vicinity of summit area of active volcanoes are important not only for understanding physical processes in the volcanic conduit but also for eruption prediction and volcanic hazards mitigation. It is, however, challenging to install observation sensors near active vents because of the danger of sudden eruptions. We need safe and efficient ways of installing sensors near the summit of active volcanoes. We have been developing an volcano observation system based on an unmanned autonomous vehicle (UAV) for risk-free volcano observations. Our UAV is an unmanned autonomous helicopter manufactured by Yamaha-Motor Co., Ltd. The UAV is 3.6m long and weighs 84kg with maximum payload of 10kg. The UAV can aviate autonomously along a previously programmed path within a meter accuracy using real-time kinematics differential GPS equipment. The maximum flight time and distance from the operator are 90 minutes and 5km, respectively. We have developed various types of volcano observation techniques adequate for the UAV, such as aeromagnetic survey, taking infrared and visible images from onboard high-resolution cameras, volcanic ash sampling in the vicinity of active vents. Recently, we have developed an earthquake observation module (EOM), which is exclusively designed for the UAV installation in the vicinity of active volcanic vent. In order to meet the various requirements for UAV installation, the EOM is very compact, light-weight (5-6kg), and is solar-powered. It is equipped with GPS for timing, a communication device using cellular-phone network, and triaxial accelerometers. Our first application of the EOM installation using the UAV is one of the most active volcanoes in Japan, Sakurajima volcano. Since 2006, explosive eruptions have been continuing at the reopened Showa crater at the eastern flank near the summit of Sakurajima. Entering the area within 2 km from the active craters is prohibited, and thus there were no observation station in the vicinity

Putting Technology to Work in Science - How to Select Unmanned Aerial Vehicles (UAV) and their Instrumentation for Atmospheric and Earth Surface Observations

NASA Astrophysics Data System (ADS)

Teller, Amit; Lange, Manfred; Ioannou, Stelios; Keleshis, Christos

2010-05-01

The Autonomous Flying Platforms for Atmospheric and Earth Surface Observations project (APAESO) of the Energy, Environment and Water Research Center (EEWRC) at the Cyprus Institute is aimed at the dual purpose of carrying out atmospheric and earth-surface observations in the Mediterranean. The APAESO platforms will offer the unique potential to determine physical, chemical and radiative atmospheric properties, aerosol and dust concentrations, atmospheric dynamics, surface morphology, vegetation and land use patterns as well as ocean surface properties (biology, waves, currents) and to carry out archaeological site reconnaissance and contaminant detection at high spatial resolution. The first phase of APAESO was dedicated to the preliminary design and the selection of an Unmanned Aerial Vehicle (UAV) as the backbone of the APAESO infrastructure. Selection of a UAV suitable for the many research objectives as outlined above is challenging because the UAV technology is new and rapidly evolving. This notwithstanding, a very large number of systems, mostly utilized for defense purposes, are currently available. The major challenge in the selection process lies in considering the trade-off between different platform characteristics (e.g. payload weight, endurance, max. altitude for operation and price) and in optimizing the potential performance of the UAV. Based on the required characteristics for the UAV platform, a survey of possible UAVs and suitable sensors was prepared based on various data sources. We used an elimination process in order to consider only a few models for the final selection process out of about 1000 commercially available UAV models that were initially investigated. The presentation will discuss the main scientific objectives that determine the specification of the UAV platform, major considerations in selecting best available technology for our needs and will briefly describe the next phases of the project.

A Q-Learning Approach to Flocking With UAVs in a Stochastic Environment.

PubMed

Hung, Shao-Ming; Givigi, Sidney N

2017-01-01

In the past two decades, unmanned aerial vehicles (UAVs) have demonstrated their efficacy in supporting both military and civilian applications, where tasks can be dull, dirty, dangerous, or simply too costly with conventional methods. Many of the applications contain tasks that can be executed in parallel, hence the natural progression is to deploy multiple UAVs working together as a force multiplier. However, to do so requires autonomous coordination among the UAVs, similar to swarming behaviors seen in animals and insects. This paper looks at flocking with small fixed-wing UAVs in the context of a model-free reinforcement learning problem. In particular, Peng's Q(λ) with a variable learning rate is employed by the followers to learn a control policy that facilitates flocking in a leader-follower topology. The problem is structured as a Markov decision process, where the agents are modeled as small fixed-wing UAVs that experience stochasticity due to disturbances such as winds and control noises, as well as weight and balance issues. Learned policies are compared to ones solved using stochastic optimal control (i.e., dynamic programming) by evaluating the average cost incurred during flight according to a cost function. Simulation results demonstrate the feasibility of the proposed learning approach at enabling agents to learn how to flock in a leader-follower topology, while operating in a nonstationary stochastic environment.

Long-Term, Autonomous Measurement of Atmospheric Carbon Dioxide Using an Ormosil Nanocomposite-Based Optical Sensor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kisholoy Goswami

2005-10-11

The goal of this project is to construct a prototype carbon dioxide sensor that can be commercialized to offer a low-cost, autonomous instrument for long-term, unattended measurements. Currently, a cost-effective CO2 sensor system is not available that can perform cross-platform measurements (ground-based or airborne platforms such as balloon and unmanned aerial vehicle (UAV)) for understanding the carbon sequestration phenomenon. The CO2 sensor would support the research objectives of DOE-sponsored programs such as AmeriFlux and the North American Carbon Program (NACP). Global energy consumption is projected to rise 60% over the next 20 years and use of oil is projected tomore » increase by approximately 40%. The combustion of coal, oil, and natural gas has increased carbon emissions globally from 1.6 billion tons in 1950 to 6.3 billion tons in 2000. This figure is expected to reach 10 billon tons by 2020. It is important to understand the fate of this excess CO2 in the global carbon cycle. The overall goal of the project is to develop an accurate and reliable optical sensor for monitoring carbon dioxide autonomously at least for one year at a point remote from the actual CO2 release site. In Phase I of this project, InnoSense LLC (ISL) demonstrated the feasibility of an ormosil-monolith based Autonomous Sensor for Atmospheric CO2 (ASAC) device. All of the Phase I objectives were successfully met.« less

Wireless Command-and-Control of UAV-Based Imaging LANs

NASA Technical Reports Server (NTRS)

Herwitz, Stanley; Dunagan, S. E.; Sullivan, D. V.; Slye, R. E.; Leung, J. G.; Johnson, L. F.

2006-01-01

Dual airborne imaging system networks were operated using a wireless line-of-sight telemetry system developed as part of a 2002 unmanned aerial vehicle (UAV) imaging mission over the USA s largest coffee plantation on the Hawaiian island of Kauai. A primary mission objective was the evaluation of commercial-off-the-shelf (COTS) 802.11b wireless technology for reduction of payload telemetry costs associated with UAV remote sensing missions. Predeployment tests with a conventional aircraft demonstrated successful wireless broadband connectivity between a rapidly moving airborne imaging local area network (LAN) and a fixed ground station LAN. Subsequently, two separate LANs with imaging payloads, packaged in exterior-mounted pressure pods attached to the underwing of NASA's Pathfinder-Plus UAV, were operated wirelessly by ground-based LANs over independent Ethernet bridges. Digital images were downlinked from the solar-powered aircraft at data rates of 2-6 megabits per second (Mbps) over a range of 6.5 9.5 km. An integrated wide area network enabled payload monitoring and control through the Internet from a range of ca. 4000 km during parts of the mission. The recent advent of 802.11g technology is expected to boost the system data rate by about a factor of five.

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

NASA Astrophysics Data System (ADS)

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

Surface target-tracking guidance by self-organizing formation flight of fixed-wing UAV

NASA Astrophysics Data System (ADS)

Regina, N.; Zanzi, M.

This paper presents a new concept of ground target surveillance based on a formation flight of two Unmanned Aerial Vehicles (UAVs) of fixed-wing type. Each UAV considered in this work has its own guidance law specifically designed for two different aims. A self organizing non-symmetric collaborative surveying scheme has been developed based on pursuers with different roles: the close-up-pursuer and the distance-pursuer. The close-up-pursuer behaves according to a guidance law which takes it to continually over-fly the target, also optimizing flight endurance. On the other hand, the distancepursuer behaves so as to circle around the target by flying at a certain distance and altitude from it; moreover, its motion ensures the maximum “ seeability” of the ground based target. In addition, the guidance law designed for the distance-pursuer also implements a collision avoidance feature in order to prevent possible risks of collision with the close-up-pursuer during the tracking maneuvers. The surveying scheme is non-symmetric in the sense that the collision avoidance feature is accomplished by a guidance law implemented only on one of the two pursuers; moreover, it is collaborative because the surveying is performed by different tasks of two UAVs and is self-organizing because, due to the collision avoidance feature, target tracking does not require pre-planned collision-risk-free trajectories but trajectories are generated in real time.

Assessing UAVs in Monitoring Crop Evapotranspiration within a Heterogeneous Soil

NASA Astrophysics Data System (ADS)

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.

Three Dimentional Reconstruction of Large Cultural Heritage Objects Based on Uav Video and Tls Data

NASA Astrophysics Data System (ADS)

Xu, Z.; Wu, T. H.; Shen, Y.; Wu, L.

2016-06-01

This paper investigates the synergetic use of unmanned aerial vehicle (UAV) and terrestrial laser scanner (TLS) in 3D reconstruction of cultural heritage objects. Rather than capturing still images, the UAV that equips a consumer digital camera is used to collect dynamic videos to overcome its limited endurance capacity. Then, a set of 3D point-cloud is generated from video image sequences using the automated structure-from-motion (SfM) and patch-based multi-view stereo (PMVS) methods. The TLS is used to collect the information that beyond the reachability of UAV imaging e.g., partial building facades. A coarse to fine method is introduced to integrate the two sets of point clouds UAV image-reconstruction and TLS scanning for completed 3D reconstruction. For increased reliability, a variant of ICP algorithm is introduced using local terrain invariant regions in the combined designation. The experimental study is conducted in the Tulou culture heritage building in Fujian province, China, which is focused on one of the TuLou clusters built several hundred years ago. Results show a digital 3D model of the Tulou cluster with complete coverage and textural information. This paper demonstrates the usability of the proposed method for efficient 3D reconstruction of heritage object based on UAV video and TLS data.

Multiple UAV Cooperation for Wildfire Monitoring

NASA Astrophysics Data System (ADS)

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.

Implementation and performance evaluation of acoustic denoising algorithms for UAV

NASA Astrophysics Data System (ADS)

Chowdhury, Ahmed Sony Kamal

Unmanned Aerial Vehicles (UAVs) have become popular alternative for wildlife monitoring and border surveillance applications. Elimination of the UAV's background noise and classifying the target audio signal effectively are still a major challenge. The main goal of this thesis is to remove UAV's background noise by means of acoustic denoising techniques. Existing denoising algorithms, such as Adaptive Least Mean Square (LMS), Wavelet Denoising, Time-Frequency Block Thresholding, and Wiener Filter, were implemented and their performance evaluated. The denoising algorithms were evaluated for average Signal to Noise Ratio (SNR), Segmental SNR (SSNR), Log Likelihood Ratio (LLR), and Log Spectral Distance (LSD) metrics. To evaluate the effectiveness of the denoising algorithms on classification of target audio, we implemented Support Vector Machine (SVM) and Naive Bayes classification algorithms. Simulation results demonstrate that LMS and Discrete Wavelet Transform (DWT) denoising algorithm offered superior performance than other algorithms. Finally, we implemented the LMS and DWT algorithms on a DSP board for hardware evaluation. Experimental results showed that LMS algorithm's performance is robust compared to DWT for various noise types to classify target audio signals.

Diverse Planning for UAV Control and Remote Sensing

PubMed Central

Tožička, Jan; Komenda, Antonín

2016-01-01

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. PMID:28009831

Diverse Planning for UAV Control and Remote Sensing.

PubMed

Tožička, Jan; Komenda, Antonín

2016-12-21

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.

a Metadata Based Approach for Analyzing Uav Datasets for Photogrammetric Applications

NASA Astrophysics Data System (ADS)

Dhanda, A.; Remondino, F.; Santana Quintero, M.

2018-05-01

This paper proposes a methodology for pre-processing and analysing Unmanned Aerial Vehicle (UAV) datasets before photogrammetric processing. In cases where images are gathered without a detailed flight plan and at regular acquisition intervals the datasets can be quite large and be time consuming to process. This paper proposes a method to calculate the image overlap and filter out images to reduce large block sizes and speed up photogrammetric processing. The python-based algorithm that implements this methodology leverages the metadata in each image to determine the end and side overlap of grid-based UAV flights. Utilizing user input, the algorithm filters out images that are unneeded for photogrammetric processing. The result is an algorithm that can speed up photogrammetric processing and provide valuable information to the user about the flight path.

Uav-Based Automatic Tree Growth Measurement for Biomass Estimation

NASA Astrophysics Data System (ADS)

Karpina, M.; Jarząbek-Rychard, M.; Tymków, P.; Borkowski, A.

2016-06-01

Manual in-situ measurements of geometric tree parameters for the biomass volume estimation are time-consuming and economically non-effective. Photogrammetric techniques can be deployed in order to automate the measurement procedure. The purpose of the presented work is an automatic tree growth estimation based on Unmanned Aircraft Vehicle (UAV) imagery. The experiment was conducted in an agriculture test field with scots pine canopies. The data was collected using a Leica Aibotix X6V2 platform equipped with a Nikon D800 camera. Reference geometric parameters of selected sample plants were measured manually each week. In situ measurements were correlated with the UAV data acquisition. The correlation aimed at the investigation of optimal conditions for a flight and parameter settings for image acquisition. The collected images are processed in a state of the art tool resulting in a generation of dense 3D point clouds. The algorithm is developed in order to estimate geometric tree parameters from 3D points. Stem positions and tree tops are identified automatically in a cross section, followed by the calculation of tree heights. The automatically derived height values are compared to the reference measurements performed manually. The comparison allows for the evaluation of automatic growth estimation process. The accuracy achieved using UAV photogrammetry for tree heights estimation is about 5cm.

Multi-temporal UAV based data for mapping crop type and structure in smallholder dominated Tanzanian agricultural landscape

NASA Astrophysics Data System (ADS)

Nagol, J. R.; Chung, C.; Dempewolf, J.; Maurice, S.; Mbungu, W.; Tumbo, S.

2015-12-01

Timely mapping and monitoring of crops like Maize, an important food security crop in Tanzania, can facilitate timely response by government and non-government organizations to food shortage or surplus conditions. Small UAVs can play an important role in linking the spaceborne remote sensing data and ground based measurement to improve the calibration and validation of satellite based estimates of in-season crop metrics. In Tanzania most of the growing season is often obscured by clouds. UAV data, if collected within a stratified statistical sampling framework, can also be used to directly in lieu of spaceborne data to infer mid-season yield estimates at regional scales.Here we present an object based approach to estimate crop metrics like crop type, area, and height using multi-temporal UAV based imagery. The methods were tested at three 1km2 plots in Kilosa, Njombe, and Same districts in Tanzania. At these sites both ground based and UAV based data were collected on a monthly time-step during the year 2015 growing season. SenseFly eBee drone with RGB and NIR-R-G camera was used to collect data. Crop type classification accuracies of above 85% were easily achieved.

State estimation for autonomous flight in cluttered environments

NASA Astrophysics Data System (ADS)

Langelaan, Jacob Willem

Safe, autonomous operation in complex, cluttered environments is a critical challenge facing autonomous mobile systems. The research described in this dissertation was motivated by a particularly difficult example of autonomous mobility: flight of a small Unmanned Aerial Vehicle (UAV) through a forest. In cluttered environments (such as forests or natural and urban canyons) signals from navigation beacons such as GPS may frequently be occluded. Direct measurements of vehicle position are therefore unavailable, and information required for flight control, obstacle avoidance, and navigation must be obtained using only on-board sensors. However, payload limitations of small UAVs restrict both the mass and physical dimensions of sensors that can be carried. This dissertation describes the development and proof-of-concept demonstration of a navigation system that uses only a low-cost inertial measurement unit and a monocular camera. Micro electromechanical inertial measurements units are well suited to small UAV applications and provide measurements of acceleration and angular rate. However, they do not provide information about nearby obstacles (needed for collision avoidance) and their noise and bias characteristics lead to unbounded growth in computed position. A monocular camera can provide bearings to nearby obstacles and landmarks. These bearings can be used both to enable obstacle avoidance and to aid navigation. Presented here is a solution to the problem of estimating vehicle state (position, orientation and velocity) as well as positions of obstacles in the environment using only inertial measurements and bearings to obstacles. This is a highly nonlinear estimation problem, and standard estimation techniques such as the Extended Kalman Filter are prone to divergence in this application. In this dissertation a Sigma Point Kalman Filter is implemented, resulting in an estimator which is able to cope with the significant nonlinearities in the system equations and

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

NASA Astrophysics Data System (ADS)

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.

FlyCap: Markerless Motion Capture Using Multiple Autonomous Flying Cameras.

PubMed

Xu, Lan; Liu, Yebin; Cheng, Wei; Guo, Kaiwen; Zhou, Guyue; Dai, Qionghai; Fang, Lu

2017-07-18

Aiming at automatic, convenient and non-instrusive motion capture, this paper presents a new generation markerless motion capture technique, the FlyCap system, to capture surface motions of moving characters using multiple autonomous flying cameras (autonomous unmanned aerial vehicles(UAVs) each integrated with an RGBD video camera). During data capture, three cooperative flying cameras automatically track and follow the moving target who performs large-scale motions in a wide space. We propose a novel non-rigid surface registration method to track and fuse the depth of the three flying cameras for surface motion tracking of the moving target, and simultaneously calculate the pose of each flying camera. We leverage the using of visual-odometry information provided by the UAV platform, and formulate the surface tracking problem in a non-linear objective function that can be linearized and effectively minimized through a Gaussian-Newton method. Quantitative and qualitative experimental results demonstrate the plausible surface and motion reconstruction results.

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

PubMed

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.

Autonomous microsystems for ground observation (AMIGO)

NASA Astrophysics Data System (ADS)

Laou, Philips

2005-05-01

This paper reports the development of a prototype autonomous surveillance microsystem AMIGO that can be used for remote surveillance. Each AMIGO unit is equipped with various sensors and electronics. These include passive infrared motion sensor, acoustic sensor, uncooled IR camera, electronic compass, global positioning system (GPS), and spread spectrum wireless transceiver. The AMIGO unit was configured to multipoint (AMIGO units) to point (base station) communication mode. In addition, field trials were conducted with AMIGO in various scenarios. These scenarios include personnel and vehicle intrusion detection (motion or sound) and target imaging; determination of target GPS position by triangulation; GPS position real time tracking; entrance event counting; indoor surveillance; and aerial surveillance on a radio controlled model plane. The architecture and test results of AMIGO will be presented.

The future of structural fieldwork - UAV assisted aerial photogrammetry

NASA Astrophysics Data System (ADS)

Vollgger, Stefan; Cruden, Alexander

2015-04-01

Unmanned aerial vehicles (UAVs), commonly referred to as drones, are opening new and low cost possibilities to acquire high-resolution aerial images and digital surface models (DSM) for applications in structural geology. UAVs can be programmed to fly autonomously along a user defined grid to systematically capture high-resolution photographs, even in difficult to access areas. The photographs are subsequently processed using software that employ SIFT (scale invariant feature transform) and SFM (structure from motion) algorithms. These photogrammetric routines allow the extraction of spatial information (3D point clouds, digital elevation models, 3D meshes, orthophotos) from 2D images. Depending on flight altitude and camera setup, sub-centimeter spatial resolutions can be achieved. By "digitally mapping" georeferenced 3D models and images, orientation data can be extracted directly and used to analyse the structural framework of the mapped object or area. We present UAV assisted aerial mapping results from a coastal platform near Cape Liptrap (Victoria, Australia), where deformed metasediments of the Palaeozoic Lachlan Fold Belt are exposed. We also show how orientation and spatial information of brittle and ductile structures extracted from the photogrammetric model can be linked to the progressive development of folds and faults in the region. Even though there are both technical and legislative limitations, which might prohibit the use of UAVs without prior commercial licensing and training, the benefits that arise from the resulting high-resolution, photorealistic models can substantially contribute to the collection of new data and insights for applications in structural geology.

Enhanced surveillance of acute flaccid paralysis following importation of wild poliovirus in Xinjiang Uygur Autonomous Region, China

PubMed Central

2014-01-01

Background After being polio free for more than 10 years, an outbreak occurred in China in 2011 in Xinjiang Uygur Autonomous Region (Xinjiang) following the importation of wild poliovirus (WPV) originating from neighboring Pakistan. Methods To strengthen acute flaccid paralysis (AFP) surveillance in Xinjiang, “zero case daily reporting” and retrospective searching of AFP cases were initiated after the confirmation of the WPV outbreak. To pinpoint all the polio cases in time, AFP surveillance system was expanded to include persons of all ages in the entire population in Xinjiang. Results Totally, 578 AFP cases were reported in 2011 in Xinjiang, including 21 WPV cases, 23 clinical compatible polio cases and 534 non-polio AFP cases. Of the 44 polio cases, 27 (61.4%) cases were reported among adults aged 15–53 years. Strengthening AFP surveillance resulted in an increase in the number of non-polio AFP cases in 2011 (148 children < 15 years) compared with 76 cases < 15 years in 2010. The AFP surveillance system in Xinjiang was sensitive enough to detect polio cases, with the AFP incidence of 3.28/100,000 among children < 15 years of age. Conclusions Incorporating adult cases into the AFP surveillance system is of potential value to understand the overall characteristics of the epidemic and to guide emergency responses, especially in countries facing WPV outbreak following long-term polio free status. The AFP surveillance system in Xinjiang was satisfactory despite limitations in biological sample collection. PMID:24576083

GPS navigation algorithms for Autonomous Airborne Refueling of Unmanned Air Vehicles

NASA Astrophysics Data System (ADS)

Khanafseh, Samer Mahmoud

Unmanned Air Vehicles (UAVs) have recently generated great interest because of their potential to perform hazardous missions without risking loss of life. If autonomous airborne refueling is possible for UAVs, mission range and endurance will be greatly enhanced. However, concerns about UAV-tanker proximity, dynamic mobility and safety demand that the relative navigation system meets stringent requirements on accuracy, integrity, and continuity. In response, this research focuses on developing high-performance GPS-based navigation architectures for Autonomous Airborne Refueling (AAR) of UAVs. The AAR mission is unique because of the potentially severe sky blockage introduced by the tanker. To address this issue, a high-fidelity dynamic sky blockage model was developed and experimentally validated. In addition, robust carrier phase differential GPS navigation algorithms were derived, including a new method for high-integrity reacquisition of carrier cycle ambiguities for recently-blocked satellites. In order to evaluate navigation performance, world-wide global availability and sensitivity covariance analyses were conducted. The new navigation algorithms were shown to be sufficient for turn-free scenarios, but improvement in performance was necessary to meet the difficult requirements for a general refueling mission with banked turns. Therefore, several innovative methods were pursued to enhance navigation performance. First, a new theoretical approach was developed to quantify the position-domain integrity risk in cycle ambiguity resolution problems. A mechanism to implement this method with partially-fixed cycle ambiguity vectors was derived, and it was used to define tight upper bounds on AAR navigation integrity risk. A second method, where a new algorithm for optimal fusion of measurements from multiple antennas was developed, was used to improve satellite coverage in poor visibility environments such as in AAR. Finally, methods for using data-link extracted

An UAV scheduling and planning method for post-disaster survey

NASA Astrophysics Data System (ADS)

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.

Uav Photgrammetric Workflows: a best Practice Guideline

NASA Astrophysics Data System (ADS)

Federman, A.; Santana Quintero, M.; Kretz, S.; Gregg, J.; Lengies, M.; Ouimet, C.; Laliberte, J.

2017-08-01

The increasing commercialization of unmanned aerial vehicles (UAVs) has opened the possibility of performing low-cost aerial image acquisition for the documentation of cultural heritage sites through UAV photogrammetry. The flying of UAVs in Canada is regulated through Transport Canada and requires a Special Flight Operations Certificate (SFOC) in order to fly. Various image acquisition techniques have been explored in this review, as well as well software used to register the data. A general workflow procedure has been formulated based off of the literature reviewed. A case study example of using UAV photogrammetry at Prince of Wales Fort is discussed, specifically in relation to the data acquisition and processing. Some gaps in the literature reviewed highlight the need for streamlining the SFOC application process, and incorporating UAVs into cultural heritage documentation courses.

Unmanned Aerial Vehicle (UAV) Dynamic-Tracking Directional Wireless Antennas for Low Powered Applications that Require Reliable Extended Range Operations in Time Critical Scenarios

DOE Office of Scientific and Technical Information (OSTI.GOV)

Scott G. Bauer; Matthew O. Anderson; James R. Hanneman

2005-10-01

The proven value of DOD Unmanned Aerial Vehicles (UAVs) will ultimately transition to National and Homeland Security missions that require real-time aerial surveillance, situation awareness, force protection, and sensor placement. Public services first responders who routinely risk personal safety to assess and report a situation for emergency actions will likely be the first to benefit from these new unmanned technologies. ‘Packable’ or ‘Portable’ small class UAVs will be particularly useful to the first responder. They require the least amount of training, no fixed infrastructure, and are capable of being launched and recovered from the point of emergency. All UAVs requiremore » wireless communication technologies for real- time applications. Typically on a small UAV, a low bandwidth telemetry link is required for command and control (C2), and systems health monitoring. If the UAV is equipped with a real-time Electro-Optical or Infrared (EO/Ir) video camera payload, a dedicated high bandwidth analog/digital link is usually required for reliable high-resolution imagery. In most cases, both the wireless telemetry and real-time video links will be integrated into the UAV with unity gain omni-directional antennas. With limited on-board power and payload capacity, a small UAV will be limited with the amount of radio-frequency (RF) energy it transmits to the users. Therefore, ‘packable’ and ‘portable’ UAVs will have limited useful operational ranges for first responders. This paper will discuss the limitations of small UAV wireless communications. The discussion will present an approach of utilizing a dynamic ground based real-time tracking high gain directional antenna to provide extend range stand-off operation, potential RF channel reuse, and assured telemetry and data communications from low-powered UAV deployed wireless assets.« less

Optical and acoustical UAV detection

NASA Astrophysics Data System (ADS)

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.

An Analytical Thermal Model for Autonomous Soaring Research

NASA Technical Reports Server (NTRS)

Allen, Michael

2006-01-01

A viewgraph presentation describing an analytical thermal model used to enable research on autonomous soaring for a small UAV aircraft is given. The topics include: 1) Purpose; 2) Approach; 3) SURFRAD Data; 4) Convective Layer Thickness; 5) Surface Heat Budget; 6) Surface Virtual Potential Temperature Flux; 7) Convective Scaling Velocity; 8) Other Calculations; 9) Yearly trends; 10) Scale Factors; 11) Scale Factor Test Matrix; 12) Statistical Model; 13) Updraft Strength Calculation; 14) Updraft Diameter; 15) Updraft Shape; 16) Smoothed Updraft Shape; 17) Updraft Spacing; 18) Environment Sink; 19) Updraft Lifespan; 20) Autonomous Soaring Research; 21) Planned Flight Test; and 22) Mixing Ratio.

Photovoltaic electric power applied to Unmanned Aerial Vehicles (UAV)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Geis, J.; Arnold, J.H.

1994-09-01

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

Fusion of spatio-temporal UAV and proximal sensing data for an agricultural decision support system

NASA Astrophysics Data System (ADS)

Katsigiannis, P.; Galanis, G.; Dimitrakos, A.; Tsakiridis, N.; Kalopesas, C.; Alexandridis, T.; Chouzouri, A.; Patakas, A.; Zalidis, G.

2016-08-01

Over the last few years, multispectral and thermal remote sensing imagery from unmanned aerial vehicles (UAVs) has found application in agriculture and has been regarded as a means of field data collection and crop condition monitoring source. The integration of information derived from the analysis of these remotely sensed data into agricultural management applications facilitates and aids the stakeholder's decision making. Whereas agricultural decision support systems (DSS) have long been utilised in farming applications, there are still critical gaps to be addressed; as the current approach often neglects the plant's level information and lacks the robustness to account for the spatial and temporal variability of environmental parameters within agricultural systems. In this paper, we demonstrate the use of a custom built autonomous UAV platform in providing critical information for an agricultural DSS. This hexacopter UAV bears two cameras which can be triggered simultaneously and can capture both the visible, near-infrared (VNIR) and the thermal infrared (TIR) wavelengths. The platform was employed for the rapid extraction of the normalized difference vegetation index (NDVI) and the crop water stress index (CWSI) of three different plantations, namely a kiwi, a pomegranate, and a vine field. The simultaneous recording of these two complementary indices and the creation of maps was advantageous for the accurate assessment of the plantation's status. Fusion of UAV and soil scanner system products pinpointed the necessity for adjustment of the irrigation management applied. It is concluded that timely CWSI and NDVI measures retrieved for different crop growing stages can provide additional information and can serve as a tool to support the existing irrigation DSS that had so far been exclusively based on telemetry data from soil and agrometeorological sensors. Additionally, the use of the multi-sensor UAV was found to be beneficial in collecting timely, spatio

Optimization of dynamic soaring maneuvers to enhance endurance of a versatile UAV

NASA Astrophysics Data System (ADS)

Mir, Imran; Maqsood, Adnan; Akhtar, Suhail

2017-06-01

Dynamic soaring is a process of acquiring energy available in atmospheric wind shears and is commonly exhibited by soaring birds to perform long distance flights. This paper aims to demonstrate a viable algorithm which can be implemented in near real time environment to formulate optimal trajectories for dynamic soaring maneuvers for a small scale Unmanned Aerial Vehicle (UAV). The objective is to harness maximum energy from atmosphere wind shear to improve loiter time for Intelligence, Surveillance and Reconnaissance (ISR) missions. Three-dimensional point-mass UAV equations of motion and linear wind gradient profile are used to model flight dynamics. Utilizing UAV states, controls, operational constraints, initial and terminal conditions that enforce a periodic flight, dynamic soaring problem is formulated as an optimal control problem. Optimized trajectories of the maneuver are subsequently generated employing pseudo spectral techniques against distant UAV performance parameters. The discussion also encompasses the requirement for generation of optimal trajectories for dynamic soaring in real time environment and the ability of the proposed algorithm for speedy solution generation. Coupled with the fact that dynamic soaring is all about immediately utilizing the available energy from the wind shear encountered, the proposed algorithm promises its viability for practical on board implementations requiring computation of trajectories in near real time.

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

NASA Astrophysics Data System (ADS)

Müller, Thomas

2017-05-01

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

Pressurized Structure Technology for UAVS

DTIC Science & Technology

2008-12-01

deficiencies of the UAVs just listed is to employ lighter-than-air or pressurized structure-based ( PSB ) technology. Basically, the UAV will be built such...that a considerable percentage of its weight is supported by or constructed from inflatable structures containing air or helium. PSB technology...neutral buoyancy will allow much slower flight speeds and increased maneuverability while expending little power. PSB airframes used in conjunction

Flight Control System Development for the BURRO Autonomous UAV

NASA Technical Reports Server (NTRS)

Colbourne, Jason D.; Frost, Chad R.; Tischler, Mark B.; Ciolani, Luigi; Sahai, Ranjana; Tomoshofski, Chris; LaMontagne, Troy; Rutkowski, Michael (Technical Monitor)

2000-01-01

Developing autonomous flying vehicles has been a growing field in aeronautical research within the last decade and will continue into the next century. With concerns about safety, size, and cost of manned aircraft, several autonomous vehicle projects are currently being developed; uninhabited rotorcraft offer solutions to requirements for hover, vertical take-off and landing, as well as slung load transportation capabilities. The newness of the technology requires flight control engineers to question what design approaches, control law architectures, and performance criteria apply to control law development and handling quality evaluation. To help answer these questions, this paper documents the control law design process for Kaman Aerospace BURRO project. This paper will describe the approach taken to design control laws and develop math models which will be used to convert the manned K-MAX into the BURRO autonomous rotorcraft. With the ability of the K-MAX to lift its own weight (6000 lb) the load significantly affects the dynamics of the system; the paper addresses the additional design requirements for slung load autonomous flight. The approach taken in this design was to: 1) generate accurate math models of the K-MAX helicopter with and without slung loads, 2) select design specifications that would deliver good performance as well as satisfy mission criteria, and 3) develop and tune the control system architecture to meet the design specs and mission criteria. An accurate math model was desired for control system development. The Comprehensive Identification from Frequency Responses (CIFER(R)) software package was used to identify a linear math model for unloaded and loaded flight at hover, 50 kts, and 100 kts. The results of an eight degree-of-freedom CIFER(R)-identified linear model for the unloaded hover flight condition are presented herein, and the identification of the two-body slung-load configuration is in progress.

Autonomous facial recognition system inspired by human visual system based logarithmical image visualization technique

NASA Astrophysics Data System (ADS)

Wan, Qianwen; Panetta, Karen; Agaian, Sos

2017-05-01

Autonomous facial recognition system is widely used in real-life applications, such as homeland border security, law enforcement identification and authentication, and video-based surveillance analysis. Issues like low image quality, non-uniform illumination as well as variations in poses and facial expressions can impair the performance of recognition systems. To address the non-uniform illumination challenge, we present a novel robust autonomous facial recognition system inspired by the human visual system based, so called, logarithmical image visualization technique. In this paper, the proposed method, for the first time, utilizes the logarithmical image visualization technique coupled with the local binary pattern to perform discriminative feature extraction for facial recognition system. The Yale database, the Yale-B database and the ATT database are used for computer simulation accuracy and efficiency testing. The extensive computer simulation demonstrates the method's efficiency, accuracy, and robustness of illumination invariance for facial recognition.

A new stratospheric sounding platform based on unmanned aerial vehicle (UAV) droppable from meteorological balloon

NASA Astrophysics Data System (ADS)

Efremov, Denis; Khaykin, Sergey; Lykov, Alexey; Berezhko, Yaroslav; Lunin, Aleksey

High-resolution measurements of climate-relevant trace gases and aerosols in the upper troposphere and stratosphere (UTS) have been and remain technically challenging. The high cost of measurements onboard airborne platforms or heavy stratospheric balloons results in a lack of accurate information on vertical distribution of atmospheric constituents. Whereas light-weight instruments carried by meteorological balloons are becoming progressively available, their usage is constrained by the cost of the equipment or the recovery operations. The evolving need in cost-efficient observations for UTS process studies has led to development of small airborne platforms - unmanned aerial vehicles (UAV), capable of carrying small sensors for in-situ measurements. We present a new UAV-based stratospheric sounding platform capable of carrying scientific payload of up to 2 kg. The airborne platform comprises of a latex meteorological balloon and detachable flying wing type UAV with internal measurement controller. The UAV is launched on a balloon to stratospheric altitudes up to 20 km, where it can be automatically released by autopilot or by a remote command sent from the ground control. Having been released from the balloon the UAV glides down and returns to the launch position. Autopilot using 3-axis gyro, accelerometer, barometer, compas and GPS navigation provides flight stabilization and optimal way back trajectory. Backup manual control is provided for emergencies. During the flight the onboard measurement controller stores the data into internal memory and transmits current flight parameters to the ground station via telemetry. Precise operation of the flight control systems ensures safe landing at the launch point. A series of field tests of the detachable stratospheric UAV has been conducted. The scientific payload included the following instruments involved in different flights: a) stratospheric Lyman-alpha hygrometer (FLASH); b) backscatter sonde; c) electrochemical

Sapphire: Canada's Answer to Space-Based Surveillance of Orbital Objects

NASA Astrophysics Data System (ADS)

Maskell, P.; Oram, L.

The Canadian Department of National Defence is in the process of developing the Canadian Space Surveillance System (CSSS) as the main focus of the Surveillance of Space (SofS) Project. The CSSS consists of two major elements: the Sapphire System and the Sensor System Operations Centre (SSOC). The space segment of the Sapphire System is comprised of the Sapphire Satellite - an autonomous spacecraft with an electro-optical payload which will act as a contributing sensor to the United States (US) Space Surveillance Network (SSN). It will operate in a circular, sunsynchronous orbit at an altitude of approximately 750 kilometers and image a minimum of 360 space objects daily in orbits ranging from 6,000 to 40,000 kilometers in altitude. The ground segment of the Sapphire System is composed of a Spacecraft Control Center (SCC), a Satellite Processing and Scheduling Facility (SPSF), and the Sapphire Simulator. The SPSF will be responsible for data transmission, reception, and processing while the SCC will serve to control and monitor the Sapphire Satellite. Surveillance data will be received from Sapphire through two ground stations. Following processing by the SPSF, the surveillance data will then be forwarded to the SSOC. The SSOC will function as the interface between the Sapphire System and the US Joint Space Operations Center (JSpOC). The JSpOC coordinates input from various sensors around the world, all of which are a part of the SSN. The SSOC will task the Sapphire System daily and provide surveillance data to the JSpOC for correlation with data from other SSN sensors. This will include orbital parameters required to predict future positions of objects to be tracked. The SSOC receives daily tasking instructions from the JSpOC to determine which objects the Sapphire spacecraft is required to observe. The advantage of this space-based sensor over ground-based telescopes is that weather and time of day are not factors affecting observation. Thus, space-based optical

Surveillance of ground vehicles for airport security

NASA Astrophysics Data System (ADS)

Blasch, Erik; Wang, Zhonghai; Shen, Dan; Ling, Haibin; Chen, Genshe

2014-06-01

Future surveillance systems will work in complex and cluttered environments which require systems engineering solutions for such applications such as airport ground surface management. In this paper, we highlight the use of a L1 video tracker for monitoring activities at an airport. We present methods of information fusion, entity detection, and activity analysis using airport videos for runway detection and airport terminal events. For coordinated airport security, automated ground surveillance enhances efficient and safe maneuvers for aircraft, unmanned air vehicles (UAVs) and unmanned ground vehicles (UGVs) operating within airport environments.

Uav Positioning and Collision Avoidance Based on RSS Measurements

NASA Astrophysics Data System (ADS)

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.

Design of UAV high resolution image transmission system

NASA Astrophysics Data System (ADS)

Gao, Qiang; Ji, Ming; Pang, Lan; Jiang, Wen-tao; Fan, Pengcheng; Zhang, Xingcheng

2017-02-01

In order to solve the problem of the bandwidth limitation of the image transmission system on UAV, a scheme with image compression technology for mini UAV is proposed, based on the requirements of High-definition image transmission system of UAV. The video codec standard H.264 coding module and key technology was analyzed and studied for UAV area video communication. Based on the research of high-resolution image encoding and decoding technique and wireless transmit method, The high-resolution image transmission system was designed on architecture of Android and video codec chip; the constructed system was confirmed by experimentation in laboratory, the bit-rate could be controlled easily, QoS is stable, the low latency could meets most applied requirement not only for military use but also for industrial applications.

Control Design and Performance Analysis for Autonomous Formation Flight Experimentss

NASA Astrophysics Data System (ADS)

Rice, Caleb Michael

Autonomous Formation Flight is a key approach for reducing greenhouse gas emissions and managing traffic in future high density airspace. Unmanned Aerial Vehicles (UAV's) have made it possible for the physical demonstration and validation of autonomous formation flight concepts inexpensively and eliminates the flight risk to human pilots. This thesis discusses the design, implementation, and flight testing of three different formation flight control methods, Proportional Integral and Derivative (PID); Fuzzy Logic (FL); and NonLinear Dynamic Inversion (NLDI), and their respective performance behavior. Experimental results show achievable autonomous formation flight and performance quality with a pair of low-cost unmanned research fixed wing aircraft and also with a solo vertical takeoff and landing (VTOL) quadrotor.

Vertical Accuracy Evaluation of Aster GDEM2 Over a Mountainous Area Based on Uav Photogrammetry

NASA Astrophysics Data System (ADS)

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

2018-05-01

Global digital elevation models (GDEM) provide elementary information on heights of the Earth's surface and objects on the ground. GDEMs have become an important data source for a range of applications. The vertical accuracy of a GDEM is critical for its applications. Nowadays UAVs has been widely used for large-scale surveying and mapping. Compared with traditional surveying techniques, UAV photogrammetry are more convenient and more cost-effective. UAV photogrammetry produces the DEM of the survey area with high accuracy and high spatial resolution. As a result, DEMs resulted from UAV photogrammetry can be used for a more detailed and accurate evaluation of the GDEM product. This study investigates the vertical accuracy (in terms of elevation accuracy and systematic errors) of the ASTER GDEM Version 2 dataset over a complex terrain based on UAV photogrammetry. Experimental results show that the elevation errors of ASTER GDEM2 are in normal distribution and the systematic error is quite small. The accuracy of the ASTER GDEM2 coincides well with that reported by the ASTER validation team. The accuracy in the research area is negatively correlated to both the slope of the terrain and the number of stereo observations. This study also evaluates the vertical accuracy of the up-sampled ASTER GDEM2. Experimental results show that the accuracy of the up-sampled ASTER GDEM2 data in the research area is not significantly reduced by the complexity of the terrain. The fine-grained accuracy evaluation of the ASTER GDEM2 is informative for the GDEM-supported UAV photogrammetric applications.

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

DTIC Science & Technology

2013-09-01

IMU Inertial Measurement Units INCOSE International Council on Systems Engineering ISR Intelligence Surveillance and Reconnaissance ISTAR...light-weight and low-cost inertial measurement units ( IMUs ) are widely adopted for navigation of small- scale UAVs. Low-costs IMUs are characterized...by high measurement noises and large measurement biases. Hence pure initial navigation using low-cost IMUs drifts rapidly. In practice, inertial

Multi-UAV Collaborative Sensor Management for UAV Team Survivability

DTIC Science & Technology

2006-08-01

Multi-UAV Collaborative Sensor Management for UAV Team Survivability Craig Stoneking, Phil DiBona , and Adria Hughes Lockheed Martin Advanced...Command, Aviation Applied Technology Directorate. REFERENCES [1] DiBona , P., Belov, N., Pawlowski, A. (2006). “Plan-Driven Fusion: Shaping the

Integrated long-range UAV/UGV collaborative target tracking

NASA Astrophysics Data System (ADS)

Moseley, Mark B.; Grocholsky, Benjamin P.; Cheung, Carol; Singh, Sanjiv

2009-05-01

Coordinated operations between unmanned air and ground assets allow leveraging of multi-domain sensing and increase opportunities for improving line of sight communications. While numerous military missions would benefit from coordinated UAV-UGV operations, foundational capabilities that integrate stove-piped tactical systems and share available sensor data are required and not yet available. iRobot, AeroVironment, and Carnegie Mellon University are working together, partially SBIR-funded through ARDEC's small unit network lethality initiative, to develop collaborative capabilities for surveillance, targeting, and improved communications based on PackBot UGV and Raven UAV platforms. We integrate newly available technologies into computational, vision, and communications payloads and develop sensing algorithms to support vision-based target tracking. We first simulated and then applied onto real tactical platforms an implementation of Decentralized Data Fusion, a novel technique for fusing track estimates from PackBot and Raven platforms for a moving target in an open environment. In addition, system integration with AeroVironment's Digital Data Link onto both air and ground platforms has extended our capabilities in communications range to operate the PackBot as well as in increased video and data throughput. The system is brought together through a unified Operator Control Unit (OCU) for the PackBot and Raven that provides simultaneous waypoint navigation and traditional teleoperation. We also present several recent capability accomplishments toward PackBot-Raven coordinated operations, including single OCU display design and operation, early target track results, and Digital Data Link integration efforts, as well as our near-term capability goals.

Budget Uav Systems for the Prospection of - and Medium-Scale Archaeological Sites

NASA Astrophysics Data System (ADS)

Ostrowski, W.; Hanus, K.

2016-06-01

One of the popular uses of UAVs in photogrammetry is providing an archaeological documentation. A wide offer of low-cost (consumer) grade UAVs, as well as the popularity of user-friendly photogrammetric software allowing obtaining satisfying results, contribute to facilitating the process of preparing documentation for small archaeological sites. However, using solutions of this kind is much more problematic for larger areas. The limited possibilities of autonomous flight makes it significantly harder to obtain data for areas too large to be covered during a single mission. Moreover, sometimes the platforms used are not equipped with telemetry systems, which makes navigating and guaranteeing a similar quality of data during separate flights difficult. The simplest solution is using a better UAV, however the cost of devices of such type often exceeds the financial capabilities of archaeological expeditions. The aim of this article is to present methodology allowing obtaining data for medium scale areas using only a basic UAV. The proposed methodology assumes using a simple multirotor, not equipped with any flight planning system or telemetry. Navigating of the platform is based solely on live-view images sent from the camera attached to the UAV. The presented survey was carried out using a simple GoPro camera which, from the perspective of photogrammetric use, was not the optimal configuration due to the fish eye geometry of the camera. Another limitation is the actual operational range of UAVs which in the case of cheaper systems, rarely exceeds 1 kilometre and is in fact often much smaller. Therefore the surveyed area must be divided into sub-blocks which correspond to the range of the drone. It is inconvenient since the blocks must overlap, so that they will later be merged during their processing. This increases the length of required flights as well as the computing power necessary to process a greater number of images. These issues make prospection highly

Spectral Imaging from Uavs Under Varying Illumination Conditions

NASA Astrophysics Data System (ADS)

Hakala, T.; Honkavaara, E.; Saari, H.; Mäkynen, J.; Kaivosoja, J.; Pesonen, L.; Pölönen, I.

2013-08-01

Rapidly developing unmanned aerial vehicles (UAV) have provided the remote sensing community with a new rapidly deployable tool for small area monitoring. The progress of small payload UAVs has introduced greater demand for light weight aerial payloads. For applications requiring aerial images, a simple consumer camera provides acceptable data. For applications requiring more detailed spectral information about the surface, a new Fabry-Perot interferometer based spectral imaging technology has been developed. This new technology produces tens of successive images of the scene at different wavelength bands in very short time. These images can be assembled in spectral data cubes with stereoscopic overlaps. On field the weather conditions vary and the UAV operator often has to decide between flight in sub optimal conditions and no flight. Our objective was to investigate methods for quantitative radiometric processing of images taken under varying illumination conditions, thus expanding the range of weather conditions during which successful imaging flights can be made. A new method that is based on insitu measurement of irradiance either in UAV platform or in ground was developed. We tested the methods in a precision agriculture application using realistic data collected in difficult illumination conditions. Internal homogeneity of the original image data (average coefficient of variation in overlapping images) was 0.14-0.18. In the corrected data, the homogeneity was 0.10-0.12 with a correction based on broadband irradiance measured in UAV, 0.07-0.09 with a correction based on spectral irradiance measurement on ground, and 0.05-0.08 with a radiometric block adjustment based on image data. Our results were very promising, indicating that quantitative UAV based remote sensing could be operational in diverse conditions, which is prerequisite for many environmental remote sensing applications.

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

NASA Astrophysics Data System (ADS)

Dörtbudak, Mehmet F.

2015-05-01

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

Heterogeneous CPU-GPU moving targets detection for UAV video

NASA Astrophysics Data System (ADS)

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

NASA Astrophysics Data System (ADS)

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.

The Altus Cumulus Electrification Study (ACES): A UAV-based Investigation of Thunderstorms

NASA Technical Reports Server (NTRS)

Blakeslee, Richard; Arnold, James E. (Technical Monitor)

2001-01-01

The Altus Cumulus Electrification Study (ACES) is a NASA-sponsored and -led science investigation that utilizes an uninhabited aerial vehicle (UAV) to investigate thunderstorms in the vicinity of the NASA Kennedy Space Center, Florida. As part of NASA's UAV-based science demonstration program, ACES will provide a scientifically useful demonstration of the utility and promise of UAV platforms for Earth science and applications observations. ACES will employ the Altus 11 aircraft, built by General Atomics-Aeronautical Systems, Inc. By taking advantage of its slow flight speed (70 to 100 knots), long endurance, and high-altitude flight (up to 55,000 feet), the Altus will be flown near, and when possible, above (but never into) thunderstorms for long periods of time, allowing investigations to be conducted over entire storm life cycles. Key science objectives simultaneously addressed by ACES are to: (1) investigate lightning-storm relationships, (2) study storm electrical budgets, and (3) provide Lightning Imaging Sensor validation. The ACES payload, already developed and flown on Altus, includes electrical, magnetic, and optical sensors to remotely characterize the lightning activity and the electrical environment within and around thunderstorms. The ACES field campaign will be conducted during July 2002 with a goal of performing 8 to 10 UAV flights. Each flight will require about 4 to 5 hours on station at altitudes from 40,000 ft to 55,000 ft. The ACES team is comprised of scientists from the NASA Marshall Space Flight Center and NASA Goddard Space Flight Centers partnered with General Atomics and IDEA, LLC.

An Integrative Object-Based Image Analysis Workflow for Uav Images

NASA Astrophysics Data System (ADS)

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.

Achieving an Optimal Medium Altitude UAV Force Balance in Support of COIN Operations

DTIC Science & Technology

2009-02-02

and execute operations. UAS with common data links and remote video terminals (RVTs) provide input to the common operational picture (COP) and...full-motion video (FMV) is intuitive to many tactical warfighters who have used similar sensors in manned aircraft. Modern data links allow the video ...Document (AFDD) 2-9. Intelligence, Surveillance, and Reconnaissance Operations, 17 July 2007. Baldor, Lolita C. “Increased UAV reliance evident in

UAV Cooperation Architectures for Persistent Sensing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roberts, R S; Kent, C A; Jones, E D

2003-03-20

With the number of small, inexpensive Unmanned Air Vehicles (UAVs) increasing, it is feasible to build multi-UAV sensing networks. In particular, by using UAVs in conjunction with unattended ground sensors, a degree of persistent sensing can be achieved. With proper UAV cooperation algorithms, sensing is maintained even though exceptional events, e.g., the loss of a UAV, have occurred. In this paper a cooperation technique that allows multiple UAVs to perform coordinated, persistent sensing with unattended ground sensors over a wide area is described. The technique automatically adapts the UAV paths so that on the average, the amount of time thatmore » any sensor has to wait for a UAV revisit is minimized. We also describe the Simulation, Tactical Operations and Mission Planning (STOMP) software architecture. This architecture is designed to help simulate and operate distributed sensor networks where multiple UAVs are used to collect data.« less

Autonomous Control Modes and Optimized Path Guidance for Shipboard Landing in High Sea States

DTIC Science & Technology

2017-04-15

50 0 50 Singular Values Frequency (rad/s) S in g u la r V a lu e s ( d B ) controller . The non -output variables can be estimated by reliable linear...Contract # N00014-14-C-0004 Autonomous Control Modes and Optimized Path Guidance for Shipboard Landing in High Sea States Progress Report...recovery of a VTOL UAV. There is a clear need for additional levels of stability and control augmentation and, ultimately, fully autonomous landing

Application of GIS-based models for delineating the UAV flight region to support Search and Rescue activities

NASA Astrophysics Data System (ADS)

Jurecka, Miroslawa; Niedzielski, Tomasz

2017-04-01

The objective of the approach presented in this paper is to demonstrate a potential of using the combination of two GIS-based models - mobility model and ring model - for delineating a region above which an Unmanned Aerial Vehicle (UAV) should fly to support the Search and Rescue (SAR) activities. The procedure is based on two concepts, both describing a possible distance/path that lost person could travel from the initial planning point (being either the point last seen, or point last known). The first approach (the ring model) takes into account the crow's flight distance traveled by a lost person and its probability distribution. The second concept (the mobility model) is based on the estimated travel speed and the associated features of the geographical environment of the search area. In contrast to the ring model covering global (hence more general) SAR perspective, the mobility model represents regional viewpoint by taking into consideration local impedance. Both models working together can serve well as a starting point for the UAV flight planning to strengthen the SAR procedures. We present the method of combining the two above-mentioned models in order to delineate UAVs flight region and increase the Probability of Success for future SAR missions. The procedure is a part of a larger Search and Rescue (SAR) system which is being developed at the University of Wrocław, Poland (research project no. IP2014 032773 financed by the Ministry of Science and Higher Education of Poland). The mobility and ring models have been applied to the Polish territory, and they act in concert to provide the UAV operator with the optimal search region. This is attained in real time so that the UAV-based SAR mission can be initiated quickly.

Why Computer-Based Systems Should be Autonomic

NASA Technical Reports Server (NTRS)

Sterritt, Roy; Hinchey, Mike

2005-01-01

The objective of this paper is to discuss why computer-based systems should be autonomic, where autonomicity implies self-managing, often conceptualized in terms of being self-configuring, self-healing, self-optimizing, self-protecting and self-aware. We look at motivations for autonomicity, examine how more and more systems are exhibiting autonomic behavior, and finally look at future directions.

Thermal Imaging of Subsurface Coal Fires by means of an Unmanned Aerial Vehicle (UAV) in the Autonomous Province Xinjiang, PRC

NASA Astrophysics Data System (ADS)

Vasterling, Margarete; Schloemer, Stefan; Fischer, Christian; Ehrler, Christoph

2010-05-01

Spontaneous combustion of coal and resulting coal fires lead to very high temperatures in the subsurface. To a large amount the heat is transferred to the surface by convective and conductive transport inducing a more or less pronounced thermal anomaly. During the past decade satellite-based infrared-imaging (ASTER, MODIS) was the method of choice for coal fire detection on a local and regional scale. However, the resolution is by far too low for a detailed analysis of single coal fires which is essential prerequisite for corrective measures (i.e. fire fighting) and calculation of carbon dioxide emission based on a complex correlation between energy release and CO2 generation. Consequently, within the framework of the Sino-German research project "Innovative Technologies for Exploration, Extinction and Monitoring of Coal Fires in Northern China", a new concept was developed and successfully tested. An unmanned aerial vehicle (UAV) was equipped with a lightweight camera for thermografic (resolution 160 by 120 pixel, dynamic range -20 to 250°C) and for visual imaging. The UAV designed as an octocopter is able to hover at GPS controlled waypoints during predefined flight missions. The application of a UAV has several advantages. Compared to point measurements on the ground the thermal imagery quickly provides the spatial distribution of the temperature anomaly with a much better resolution. Areas otherwise not accessible (due to topography, fire induced cracks, etc.) can easily be investigated. The results of areal surveys on two coal fires in Xinjiang are presented. Georeferenced thermal and visual images were mosaicked together and analyzed. UAV-born data do well compared to temperatures measured directly on the ground and cover large areas in detail. However, measuring surface temperature alone is not sufficient. Simultaneous measurements made at the surface and in roughly 15cm depth proved substantial temperature gradients in the upper soil. Thus the temperature

A Programmable SDN+NFV Architecture for UAV Telemetry Monitoring

NASA Technical Reports Server (NTRS)

White, Kyle J. S.; Pezaros, Dimitrios P.; Denney, Ewen; Knudson, Matt D.

2017-01-01

With the explosive growth in UAV numbers forecast worldwide, a core concern is how to manage the ad-hoc network configuration required for mobility management. As UAVs migrate among ground control stations, associated network services, routing and operational control must also rapidly migrate to ensure a seamless transition. In this paper, we present a novel, lightweight and modular architecture which supports high mobility, resilience and flexibility through the application of SDN and NFV principles on top of the UAV infrastructure. By combining SDN programmability and Network Function Virtualization we can achieve resilient infrastructure migration of network services, such as network monitoring and anomaly detection, coupled with migrating UAVs to enable high mobility management. Our container-based monitoring and anomaly detection Network Functions (NFs) can be tuned to specific UAV models providing operators better insight during live, high-mobility deployments. We evaluate our architecture against telemetry from over 80flights from a scientific research UAV infrastructure.

Optimal trajectory planning for a UAV glider using atmospheric thermals

NASA Astrophysics Data System (ADS)

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.

Vertical and Horizontal Measurements of Ambient Ozone over a Gas and Oil Production Area using a UAV Platform

NASA Astrophysics Data System (ADS)

Jensen, A.; Gowing, I.; Martin, R. S.

2013-12-01

During the 2013 wintertime Uintah Basin Ozone Study (UBOS13), an autonomous unmanned aerial vehicle (UAV) platform, coupled with an on-board UV ozone monitor, flew several spatial profiles near the location (Horse Pool) of other concentrated measurements by other co-investigators. The airframe, part of the Utah Water Research Laboratory's (UWRL) AggieAir UAV program, consisted of a custom-built, battery-operated plane with and 2.4 m (8 ft) wing span and a 12.7 cm x 12.7 cm x 30.5 cm payload bay with a carrying capacity of approximately 2.0 kg. With the current power system, the fully-loaded AggieAir UAV can fly for approximately 45 minutes at a nominal airspeed of 13.4 m/s (30 mph). The system can be operated either in manual control or be flown autonomously following preprogrammed waypoints via a built in GPS system. The AggieAir UAV systems were primarily designed for photographic and telemetry tracking projects. For the UBOS13 flights, a 2B Technologies Model 205 Ozone (O3) monitor was modified for minimal weight optimization, wrapped with lightweight insulation and secured into the UAV payload bay. Additionally, HOBO Model H08-001-02 shielded temperature/datalogger was secured to the exterior of the UAV from parallel thermal profile determination. During the study period, three demonstration flight profiles were obtained on February 17 and 18, 2013: two vertical 'curtain' profiles and a pair of 'stacked' horizontal profiles. As recorded by numerous ground-based monitoring sites, the ozone during the UAV test periods was characterized by initial trends of daytime O3 maximums over 130 ppb, followed by a meteorological front partially ventilating the Basin on the evening of Feb. 17th leading to decreased O3 minimums around 40 ppb. However, the ground level O3 rebuilt quickly to ground level maximums approaching 100 ppb. The vertical 'curtain' flown on the evening of Feb. 17th only reached a maximum elevation of about 2160 m ASL (600 m AGL) due to encountering

A Discussion of Aerodynamic Control Effectors (ACEs) for Unmanned Air Vehicles (UAVs)

NASA Technical Reports Server (NTRS)

Wood, Richard M.

2002-01-01

A Reynolds number based, unmanned air vehicle classification structure has been developed which identifies four classes of unmanned air vehicle concepts. The four unmanned air vehicle (UAV) classes are; Micro UAV, Meso UAV, Macro UAV, and Mega UAV. In a similar fashion a labeling scheme for aerodynamic control effectors (ACE) was developed and eleven types of ACE concepts were identified. These eleven types of ACEs were laid out in a five (5) layer scheme. The final section of the paper correlated the various ACE concepts to the four UAV classes and ACE recommendations are offered for future design activities.

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

PubMed

Ramon Soria, Pablo; Bevec, Robert; Arrue, Begoña C; Ude, Aleš; Ollero, Aníbal

2016-05-14

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.

Optimal design of UAV's pod shape

NASA Astrophysics Data System (ADS)

Wei, Qun; Jia, Hong-guang

2011-08-01

In the modern war, UAV(unmanned aircraft system) plays a more and more important role in the army. UAVs always carry electrical-optical reconnaissance systems. These systems are used to accomplish the missions of observing and reconnaissance the battlefield. For traditional UAV, the shape of the pod on UAV is sphericity. In addition, the pod of UAV not only has the job of observing and reconnaissance the battlefield, but its shape also has impact on the UAV's drag when it flies in the air. In this paper, two different kinds of pod models are set up, one is the traditional sphericity model, the other is a new model. Unstructured grid is used on the flow field. Using CFD(computational fluid dynamic) method, the results of the drags of the different kinds of pod are got. The drag's relationship between the pod and the UAV is obtained by comparing the results of simulations. After analyzing the results we can get: when UAV flies at low speed(0.3Ma{0.7Ma), the drag's difference between the two kinds of pod is little, the pod's drag takes a small part of the UAV's whole drag which is only about 14%. At transonic speed(0.8Ma{1.2Ma), the drag's difference between these two kinds of pod is getting bigger and bigger along with the speed goes higher. The traditional pod's drag is 1/3 of the UAV's whole drag value, but for the new pod, it is only 1/5. At supersonic speed(1.3Ma{2.0Ma), the traditional pod's drag goes up rapidly, but the new kind of pod's drag goes up slowly. This makes the difference between the two kinds of UAVs' total drag comes greater. For example, at 2Ma, the total drag of new UAV is only 2/3 of the traditional UAV. These results show: when the UAV flies at low speed, these two kinds of pod have little difference in drag. But if it flies at supersonic speed, the pod has great impact on the UAV's total drag, so the designer of UAV's pod should pay more attention on the out shape.

Mini-Uav LIDAR for Power Line Inspection

NASA Astrophysics Data System (ADS)

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.

Real-Time 3d Reconstruction from Images Taken from AN Uav

NASA Astrophysics Data System (ADS)

Zingoni, A.; Diani, M.; Corsini, G.; Masini, A.

2015-08-01

We designed a method for creating 3D models of objects and areas from two aerial images acquired from an UAV. The models are generated automatically and in real-time, and consist in dense and true-colour reconstructions of the considered areas, which give the impression to the operator to be physically present within the scene. The proposed method only needs a cheap compact camera, mounted on a small UAV. No additional instrumentation is necessary, so that the costs are very limited. The method consists of two main parts: the design of the acquisition system and the 3D reconstruction algorithm. In the first part, the choices for the acquisition geometry and for the camera parameters are optimized, in order to yield the best performance. In the second part, a reconstruction algorithm extracts the 3D model from the two acquired images, maximizing the accuracy under the real-time constraint. A test was performed in monitoring a construction yard, obtaining very promising results. Highly realistic and easy-to-interpret 3D models of objects and areas of interest were produced in less than one second, with an accuracy of about 0.5m. For its characteristics, the designed method is suitable for video-surveillance, remote sensing and monitoring, especially in those applications that require intuitive and reliable information quickly, as disasters monitoring, search and rescue and area surveillance.

Targeted Applications of Unmanned Aerial Vehicles (Drones) in Telemedicine.

PubMed

Bhatt, Kunj; Pourmand, Ali; Sikka, Neal

2018-02-28

Advances in technology have revolutionized the medical field and changed the way healthcare is delivered. Unmanned aerial vehicles (UAVs) are the next wave of technological advancements that have the potential to make a huge splash in clinical medicine. UAVs, originally developed for military use, are making their way into the public and private sector. Because they can be flown autonomously and can reach almost any geographical location, the significance of UAVs are becoming increasingly apparent in the medical field. We conducted a comprehensive review of the English language literature via the PubMed and Google Scholar databases using search terms "unmanned aerial vehicles," "UAVs," and "drone." Preference was given to clinical trials and review articles that addressed the keywords and clinical medicine. Potential applications of UAVs in medicine are broad. Based on articles identified, we grouped UAV application in medicine into three categories: (1) Prehospital Emergency Care; (2) Expediting Laboratory Diagnostic Testing; and (3) Surveillance. Currently, UAVs have been shown to deliver vaccines, automated external defibrillators, and hematological products. In addition, they are also being studied in the identification of mosquito habitats as well as drowning victims at beaches as a public health surveillance modality. These preliminary studies shine light on the possibility that UAVs may help to increase access to healthcare for patients who may be otherwise restricted from proper care due to cost, distance, or infrastructure. As with any emerging technology and due to the highly regulated healthcare environment, the safety and effectiveness of this technology need to be thoroughly discussed. Despite the many questions that need to be answered, the application of drones in medicine appears to be promising and can both increase the quality and accessibility of healthcare.

Photovoltaic electric power applied to Unmanned Aerial Vehicles (UAV)

NASA Astrophysics Data System (ADS)

Geis, Jack; Arnold, Jack H.

1994-09-01

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

Photovoltaic electric power applied to Unmanned Aerial Vehicles (UAV)

NASA Technical Reports Server (NTRS)

Geis, Jack; Arnold, Jack H.

1994-01-01

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

Autonomous landing and ingress of micro-air-vehicles in urban environments based on monocular vision

NASA Astrophysics Data System (ADS)

Brockers, Roland; Bouffard, Patrick; Ma, Jeremy; Matthies, Larry; Tomlin, Claire

2011-06-01

Unmanned micro air vehicles (MAVs) will play an important role in future reconnaissance and search and rescue applications. In order to conduct persistent surveillance and to conserve energy, MAVs need the ability to land, and they need the ability to enter (ingress) buildings and other structures to conduct reconnaissance. To be safe and practical under a wide range of environmental conditions, landing and ingress maneuvers must be autonomous, using real-time, onboard sensor feedback. To address these key behaviors, we present a novel method for vision-based autonomous MAV landing and ingress using a single camera for two urban scenarios: landing on an elevated surface, representative of a rooftop, and ingress through a rectangular opening, representative of a door or window. Real-world scenarios will not include special navigation markers, so we rely on tracking arbitrary scene features; however, we do currently exploit planarity of the scene. Our vision system uses a planar homography decomposition to detect navigation targets and to produce approach waypoints as inputs to the vehicle control algorithm. Scene perception, planning, and control run onboard in real-time; at present we obtain aircraft position knowledge from an external motion capture system, but we expect to replace this in the near future with a fully self-contained, onboard, vision-aided state estimation algorithm. We demonstrate autonomous vision-based landing and ingress target detection with two different quadrotor MAV platforms. To our knowledge, this is the first demonstration of onboard, vision-based autonomous landing and ingress algorithms that do not use special purpose scene markers to identify the destination.

Autonomous Landing and Ingress of Micro-Air-Vehicles in Urban Environments Based on Monocular Vision

NASA Technical Reports Server (NTRS)

Brockers, Roland; Bouffard, Patrick; Ma, Jeremy; Matthies, Larry; Tomlin, Claire

2011-01-01

Unmanned micro air vehicles (MAVs) will play an important role in future reconnaissance and search and rescue applications. In order to conduct persistent surveillance and to conserve energy, MAVs need the ability to land, and they need the ability to enter (ingress) buildings and other structures to conduct reconnaissance. To be safe and practical under a wide range of environmental conditions, landing and ingress maneuvers must be autonomous, using real-time, onboard sensor feedback. To address these key behaviors, we present a novel method for vision-based autonomous MAV landing and ingress using a single camera for two urban scenarios: landing on an elevated surface, representative of a rooftop, and ingress through a rectangular opening, representative of a door or window. Real-world scenarios will not include special navigation markers, so we rely on tracking arbitrary scene features; however, we do currently exploit planarity of the scene. Our vision system uses a planar homography decomposition to detect navigation targets and to produce approach waypoints as inputs to the vehicle control algorithm. Scene perception, planning, and control run onboard in real-time; at present we obtain aircraft position knowledge from an external motion capture system, but we expect to replace this in the near future with a fully self-contained, onboard, vision-aided state estimation algorithm. We demonstrate autonomous vision-based landing and ingress target detection with two different quadrotor MAV platforms. To our knowledge, this is the first demonstration of onboard, vision-based autonomous landing and ingress algorithms that do not use special purpose scene markers to identify the destination.

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

NASA Astrophysics Data System (ADS)

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

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

NASA Astrophysics Data System (ADS)

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 Ground-Based Near Infrared Camera Array System for UAV Auto-Landing in GPS-Denied Environment.

PubMed

Yang, Tao; Li, Guangpo; Li, Jing; Zhang, Yanning; Zhang, Xiaoqiang; Zhang, Zhuoyue; Li, Zhi

2016-08-30

This paper proposes a novel infrared camera array guidance system with capability to track and provide real time position and speed of a fixed-wing Unmanned air vehicle (UAV) during a landing process. The system mainly include three novel parts: (1) Infrared camera array and near infrared laser lamp based cooperative long range optical imaging module; (2) Large scale outdoor camera array calibration module; and (3) Laser marker detection and 3D tracking module. Extensive automatic landing experiments with fixed-wing flight demonstrate that our infrared camera array system has the unique ability to guide the UAV landing safely and accurately in real time. Moreover, the measurement and control distance of our system is more than 1000 m. The experimental results also demonstrate that our system can be used for UAV automatic accurate landing in Global Position System (GPS)-denied environments.

Aerial monitoring in active mud volcano by UAV technique

NASA Astrophysics Data System (ADS)

Pisciotta, Antonino; Capasso, Giorgio; Madonia, Paolo

2016-04-01

UAV photogrammetry opens various new applications in the close range domain, combining aerial and terrestrial photogrammetry, but also introduces low-cost alternatives to the classical manned aerial photogrammetry. Between 2014 and 2015 tree aerial surveys have been carried out. Using a quadrotor drone, equipped with a compact camera, it was possible to generate high resolution elevation models and orthoimages of The "Salinelle", an active mud volcanoes area, located in territory of Paternò (South Italy). The main risks are related to the damages produced by paroxysmal events. Mud volcanoes show different cyclic phases of activity, including catastrophic events and periods of relative quiescence characterized by moderate activity. Ejected materials often are a mud slurry of fine solids suspended in liquids which may include water and hydrocarbon fluids, the bulk of released gases are carbon dioxide, with some methane and nitrogen, usually pond-shaped of variable dimension (from centimeters to meters in diameter). The scope of the presented work is the performance evaluation of a UAV system that was built to rapidly and autonomously acquire mobile three-dimensional (3D) mapping data in a volcanic monitoring scenario.

Precise Positioning of Uavs - Dealing with Challenging Rtk-Gps Measurement Conditions during Automated Uav Flights

NASA Astrophysics Data System (ADS)

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.

Development of autonomous multirotor platform for exploration missions

NASA Astrophysics Data System (ADS)

Czyba, Roman; Janik, Marcin; Kurgan, Oliver; Niezabitowski, Michał; Nocoń, Marek

2016-06-01

This paper outlines development process of unmanned multirotor aerial vehicle HF-4X, which consists of design and manufacturing semi-autonomous UAV dedicated for indoor flight, which would be capable of stable and controllable mission flight. A micro air vehicle was designed to participate in the International Micro Air Vehicle Conference and Flight Competition. In this paper much attention was paid to the structure of flight control system, stabilization algorithms, analysis of IMU sensors, fusion algorithms.

Development of autonomous multirotor platform for exploration missions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Czyba, Roman; Janik, Marcin; Kurgan, Oliver

This paper outlines development process of unmanned multirotor aerial vehicle HF-4X, which consists of design and manufacturing semi-autonomous UAV dedicated for indoor flight, which would be capable of stable and controllable mission flight. A micro air vehicle was designed to participate in the International Micro Air Vehicle Conference and Flight Competition. In this paper much attention was paid to the structure of flight control system, stabilization algorithms, analysis of IMU sensors, fusion algorithms.

Autonomous agricultural remote sensing systems with high spatial and temporal resolutions

NASA Astrophysics Data System (ADS)

Xiang, Haitao

In this research, two novel agricultural remote sensing (RS) systems, a Stand-alone Infield Crop Monitor RS System (SICMRS) and an autonomous Unmanned Aerial Vehicles (UAV) based RS system have been studied. A high-resolution digital color and multi-spectral camera was used as the image sensor for the SICMRS system. An artificially intelligent (AI) controller based on artificial neural network (ANN) and an adaptive neuro-fuzzy inference system (ANFIS) was developed. Morrow Plots corn field RS images in the 2004 and 2006 growing seasons were collected by the SICMRS system. The field site contained 8 subplots (9.14 m x 9.14 m) that were planted with corn and three different fertilizer treatments were used among those subplots. The raw RS images were geometrically corrected, resampled to 10cm resolution, removed soil background and calibrated to real reflectance. The RS images from two growing seasons were studied and 10 different vegetation indices were derived from each day's image. The result from the image processing demonstrated that the vegetation indices have temporal effects. To achieve high quality RS data, one has to utilize the right indices and capture the images at the right time in the growing season. Maximum variations among the image data set are within the V6-V10 stages, which indicated that these stages are the best period to identify the spatial variability caused by the nutrient stress in the corn field. The derived vegetation indices were also used to build yield prediction models via the linear regression method. At that point, all of the yield prediction models were evaluated by comparing the R2-value and the best index model from each day's image was picked based on the highest R 2-value. It was shown that the green normalized difference vegetation (GNDVI) based model is more sensitive to yield prediction than other indices-based models. During the VT-R4 stages, the GNDVI based models were able to explain more than 95% potential corn yield

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

NASA Astrophysics Data System (ADS)

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

PubMed

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

NASA Astrophysics Data System (ADS)

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.

Towards FAA Certification of UAVs

NASA Technical Reports Server (NTRS)

Nelson, Stacy

2003-01-01

As of June 30, 2003, all Unmanned Aerial Vehicles (UAV), no matter how small, must adhere to the same FAA regulations as human-piloted aircraft. These regulations include certification for flying in controlled airspace and certification of flight software based on RTCA DO-178B. This paper provides an overview of the steps necessary to obtain certification, as well as a discussion about the challenges UAV's face when trying to meet these requirements. It is divided into two parts: 1) Certifications for Flying in Controlled Airspace; 2) Certification of Flight Software per RTCA DO-178B.

Bringing UAVs to the fight: recent army autonomy research and a vision for the future

NASA Astrophysics Data System (ADS)

Moorthy, Jay; Higgins, Raymond; Arthur, Keith

2008-04-01

The Unmanned Autonomous Collaborative Operations (UACO) program was initiated in recognition of the high operational burden associated with utilizing unmanned systems by both mounted and dismounted, ground and airborne warfighters. The program was previously introduced at the 62nd Annual Forum of the American Helicopter Society in May of 20061. This paper presents the three technical approaches taken and results obtained in UACO. All three approaches were validated extensively in contractor simulations, two were validated in government simulation, one was flight tested outside the UACO program, and one was flight tested in Part 2 of UACO. Results and recommendations are discussed regarding diverse areas such as user training and human-machine interface, workload distribution, UAV flight safety, data link bandwidth, user interface constructs, adaptive algorithms, air vehicle system integration, and target recognition. Finally, a vision for UAV As A Wingman is presented.

Natural Language Based Multimodal Interface for UAV Mission Planning

NASA Technical Reports Server (NTRS)

Chandarana, Meghan; Meszaros, Erica L.; Trujillo, Anna; Allen, B. Danette

2017-01-01

As the number of viable applications for unmanned aerial vehicle (UAV) systems increases at an exponential rate, interfaces that reduce the reliance on highly skilled engineers and pilots must be developed. Recent work aims to make use of common human communication modalities such as speech and gesture. This paper explores a multimodal natural language interface that uses a combination of speech and gesture input modalities to build complex UAV flight paths by defining trajectory segment primitives. Gesture inputs are used to define the general shape of a segment while speech inputs provide additional geometric information needed to fully characterize a trajectory segment. A user study is conducted in order to evaluate the efficacy of the multimodal interface.

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

NASA Astrophysics Data System (ADS)

Gudmundsson, Snorri

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

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

NASA Astrophysics Data System (ADS)

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.

Development and testing of instrumentation for ship-based UAV measurements of ocean surface processes and the marine atmospheric boundary layer

NASA Astrophysics Data System (ADS)

Reineman, B. D.; Lenain, L.; Statom, N.; Melville, W. K.

2012-12-01

We have developed instrumentation packages for unmanned aerial vehicles (UAVs) to measure ocean surface processes along with momentum fluxes and latent, sensible, and radiative heat fluxes in the marine atmospheric boundary layer (MABL). The packages have been flown over land on BAE Manta C1s and over water on Boeing-Insitu ScanEagles. The low altitude required for accurate surface flux measurements (< 30 m) is below the typical safety limit of manned research aircraft; however, with advances in laser altimeters, small-aircraft flight control, and real-time kinematic differential GPS, low-altitude flight is now within the capability of small UAV platforms. Fast-response turbulence, hygrometer, and temperature probes permit turbulent flux measurements, and short- and long-wave radiometers allow the determination of net radiation, surface temperature, and albedo. Onboard laser altimetry and high-resolution visible and infrared video permit observations of surface waves and fine-scale (O(10) cm) ocean surface temperature structure. Flight tests of payloads aboard ScanEagle UAVs were conducted in April 2012 at the Naval Surface Warfare Center Dahlgren Division (Dahlgren, VA), where measurements of water vapor, heat, and momentum fluxes were made from low-altitude (31-m) UAV flights over water (Potomac River). ScanEagles are capable of ship-based launch and recovery, which can extend the reach of research vessels and enable scientific measurements out to ranges of O(10-100) km and altitudes up to 5 km. UAV-based atmospheric and surface observations can complement observations of surface and subsurface phenomena made from a research vessel and avoid the well-known problems of vessel interference in MABL measurements. We present a description of the instrumentation, summarize results from flight tests, and discuss potential applications of these UAVs for ship-based MABL studies.

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

NASA Astrophysics Data System (ADS)

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.

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

PubMed Central

Ramon Soria, Pablo; Bevec, Robert; Arrue, Begoña C.; Ude, Aleš; Ollero, Aníbal

2016-01-01

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. PMID:27187413

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

NASA Astrophysics Data System (ADS)

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

The NASA/Army Autonomous Rotorcraft Project

NASA Technical Reports Server (NTRS)

Whalley, M.; Freed, M.; Takahashi, M.; Christian, D.; Patterson-Hine, A.; Schulein, G.; Harris, R.

2002-01-01

An overview of the NASA Ames Research Center Autonomous Rotorcraft Project (ARP) is presented. The project brings together several technologies to address NASA and US Army autonomous vehicle needs, including a reactive planner for mission planning and execution, control system design incorporating a detailed understanding of the platform dynamics, and health monitoring and diagnostics. A candidate reconnaissance and surveillance mission is described. The autonomous agent architecture and its application to the candidate mission are presented. Details of the vehicle hardware and software development are provided.

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

PubMed

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.

Multiple Views on Safety-Critical Automation: Aircraft, Autonomous Vehicles, Air Traffic Management and Satellite Ground Segments Perspectives

NASA Technical Reports Server (NTRS)

Feary, Michael S.; Palanque, Philippe Andre Rolan; Martinie, De Almeida; Tscheligi, Manfred

2016-01-01

This SIG focuses on the engineering of automation in interactive critical systems. Automation has already been studied in a number of (sub-) disciplines and application fields: design, human factors, psychology, (software) engineering, aviation, health care, games. One distinguishing feature of the area we are focusing on is that in the field of interactive critical systems properties such as reliability, dependability, fault-tolerance are as important as usability, user experience or overall acceptance issues. The SIG targets at two problem areas: first the engineering of the user interaction with (partly-) autonomous systems: how to design, build and assess autonomous behavior, especially in cases where there is a need to represent on the user interface both autonomous and interactive objects. An example of such integration is the representation of an unmanned aerial vehicle (UAV) (where no direct interaction is possible), together with aircrafts (that have to be instructed by an air traffic controller to avoid the UAV). Second the design and engineering of user interaction in general for autonomous objects systems (for example a cruise control in a car or an autopilot in an aircraft). The goal of the SIG is to raise interest in the CHI community on the general aspects of automation and to identify a community of researchers and practitioners interested in those increasingly prominent issues of interfaces towards (semi)-autonomous systems. The expected audience should be interested in addressing the issues of integration of mainly unconnected research domains to formulate a new joint research agenda.

Uav Borne Low Altitude Photogrammetry System

NASA Astrophysics Data System (ADS)

Lin, Z.; Su, G.; Xie, F.

2012-07-01

In this paper，the aforementioned three major aspects related to the Unmanned Aerial Vehicles (UAV) system for low altitude aerial photogrammetry, i.e., flying platform, imaging sensor system and data processing software, are discussed. First of all, according to the technical requirements about the least cruising speed, the shortest taxiing distance, the level of the flight control and the performance of turbulence flying, the performance and suitability of the available UAV platforms (e.g., fixed wing UAVs, the unmanned helicopters and the unmanned airships) are compared and analyzed. Secondly, considering the restrictions on the load weight of a platform and the resolution pertaining to a sensor, together with the exposure equation and the theory of optical information, the principles of designing self-calibration and self-stabilizing combined wide-angle digital cameras (e.g., double-combined camera and four-combined camera) are placed more emphasis on. Finally, a software named MAP-AT, considering the specialty of UAV platforms and sensors, is developed and introduced. Apart from the common functions of aerial image processing, MAP-AT puts more effort on automatic extraction, automatic checking and artificial aided adding of the tie points for images with big tilt angles. Based on the recommended process for low altitude photogrammetry with UAVs in this paper, more than ten aerial photogrammetry missions have been accomplished, the accuracies of Aerial Triangulation, Digital orthophotos(DOM)and Digital Line Graphs(DLG) of which meet the standard requirement of 1:2000, 1:1000 and 1:500 mapping.

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

NASA Astrophysics Data System (ADS)

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

Spurious RF signals emitted by mini-UAVs

NASA Astrophysics Data System (ADS)

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

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

NASA Astrophysics Data System (ADS)

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.

Aerial surveillance vehicles augment security at shipping ports

NASA Astrophysics Data System (ADS)

Huck, Robert C.; Al Akkoumi, Muhammad K.; Cheng, Samuel; Sluss, James J., Jr.; Landers, Thomas L.

2008-10-01

With the ever present threat to commerce, both politically and economically, technological innovations provide a means to secure the transportation infrastructure that will allow efficient and uninterrupted freight-flow operations for trade. Currently, freight coming into United States ports is "spot checked" upon arrival and stored in a container yard while awaiting the next mode of transportation. For the most part, only fences and security patrols protect these container storage yards. To augment these measures, the authors propose the use of aerial surveillance vehicles equipped with video cameras and wireless video downlinks to provide a birds-eye view of port facilities to security control centers and security patrols on the ground. The initial investigation described in this paper demonstrates the use of unmanned aerial surveillance vehicles as a viable method for providing video surveillance of container storage yards. This research provides the foundation for a follow-on project to use autonomous aerial surveillance vehicles coordinated with autonomous ground surveillance vehicles for enhanced port security applications.

French MALE UAV Program

DTIC Science & Technology

2003-09-02

ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) MoD- France 8...1French Air Force MINISTÈRE DE LA DÉFENSE 1 SIDM CONOPS 2 FAF IMAGERY ARCHITECTURE 3 FUTURE FRENCH MALE UAV PROGRAM FRENCH MALE UAV PROGRAM Report...2. REPORT TYPE N/A 3. DATES COVERED - 4. TITLE AND SUBTITLE French Male UAV Program 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM

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

NASA Astrophysics Data System (ADS)

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.

Flexible Wing Base Micro Aerial Vehicles: Micro Air Vehicles (MAVs) for Surveillance and Remote Sensor Delivery

NASA Technical Reports Server (NTRS)

Ifju, Peter

2002-01-01

Micro Air Vehicles (MAVs) will be developed for tracking individuals, locating terrorist threats, and delivering remote sensors, for surveillance and chemical/biological agent detection. The tasks are: (1) Develop robust MAV platform capable of carrying sensor payload. (2) Develop fully autonomous capabilities for delivery of sensors to remote and distant locations. The current capabilities and accomplishments are: (1) Operational electric (inaudible) 6-inch MAVs with novel flexible wing, providing superior aerodynamic efficiency and control. (2) Vision-based flight stability and control (from on-board cameras).

'Fly Like This': Natural Language Interface for UAV Mission Planning

NASA Technical Reports Server (NTRS)

Chandarana, Meghan; Meszaros, Erica L.; Trujillo, Anna; Allen, B. Danette

2017-01-01

With the increasing presence of unmanned aerial vehicles (UAVs) in everyday environments, the user base of these powerful and potentially intelligent machines is expanding beyond exclusively highly trained vehicle operators to include non-expert system users. Scientists seeking to augment costly and often inflexible methods of data collection historically used are turning towards lower cost and reconfigurable UAVs. These new users require more intuitive and natural methods for UAV mission planning. This paper explores two natural language interfaces - gesture and speech - for UAV flight path generation through individual user studies. Subjects who participated in the user studies also used a mouse-based interface for a baseline comparison. Each interface allowed the user to build flight paths from a library of twelve individual trajectory segments. Individual user studies evaluated performance, efficacy, and ease-of-use of each interface using background surveys, subjective questionnaires, and observations on time and correctness. Analysis indicates that natural language interfaces are promising alternatives to traditional interfaces. The user study data collected on the efficacy and potential of each interface will be used to inform future intuitive UAV interface design for non-expert users.

New Concepts and Perspectives on Micro-Rotorcraft and Small Autonomous Rotary-Wing Vehicles

NASA Technical Reports Server (NTRS)

Young, Larry A.; Aiken, E. W.; Johnson, J. L.; Demblewski, R.; Andrews, J.; Aiken, Irwin W. (Technical Monitor)

2001-01-01

A key part of the strategic vision for rotorcraft research as identified by senior technologists within the Army/NASA Rotorcraft Division at NASA Ames Research Center is the development and use of small autonomous rotorcraft. Small autonomous rotorcraft are defined for the purposes of this paper to be a class of vehicles that range in size from rotary-wing micro air vehicles (MAVs) to larger, more conventionally sized, rotorcraft uninhabited aerial vehicles (UAVs) - i.e. vehicle gross weights ranging from hundreds of grams to thousands of kilograms. The development of small autonomous rotorcraft represents both a technology challenge and a potential new vehicle class that will have substantial societal impact for: national security, personal transport, planetary science, and public service.

Automated ortho-rectification of UAV-based hyperspectral data over an agricultural field using frame RGB imagery

DOE PAGES

Habib, Ayman; Han, Youkyung; Xiong, Weifeng; ...

2016-09-24

Low-cost Unmanned Airborne Vehicles (UAVs) equipped with consumer-grade imaging systems have emerged as a potential remote sensing platform that could satisfy the needs of a wide range of civilian applications. Among these applications, UAV-based agricultural mapping and monitoring have attracted significant attention from both the research and professional communities. The interest in UAV-based remote sensing for agricultural management is motivated by the need to maximize crop yield. Remote sensing-based crop yield prediction and estimation are primarily based on imaging systems with different spectral coverage and resolution (e.g., RGB and hyperspectral imaging systems). Due to the data volume, RGB imaging ismore » based on frame cameras, while hyperspectral sensors are primarily push-broom scanners. To cope with the limited endurance and payload constraints of low-cost UAVs, the agricultural research and professional communities have to rely on consumer-grade and light-weight sensors. However, the geometric fidelity of derived information from push-broom hyperspectral scanners is quite sensitive to the available position and orientation established through a direct geo-referencing unit onboard the imaging platform (i.e., an integrated Global Navigation Satellite System (GNSS) and Inertial Navigation System (INS). This paper presents an automated framework for the integration of frame RGB images, push-broom hyperspectral scanner data and consumer-grade GNSS/INS navigation data for accurate geometric rectification of the hyperspectral scenes. The approach relies on utilizing the navigation data, together with a modified Speeded-Up Robust Feature (SURF) detector and descriptor, for automating the identification of conjugate features in the RGB and hyperspectral imagery. The SURF modification takes into consideration the available direct geo-referencing information to improve the reliability of the matching procedure in the presence of repetitive texture within a

Automated ortho-rectification of UAV-based hyperspectral data over an agricultural field using frame RGB imagery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Habib, Ayman; Han, Youkyung; Xiong, Weifeng

Low-cost Unmanned Airborne Vehicles (UAVs) equipped with consumer-grade imaging systems have emerged as a potential remote sensing platform that could satisfy the needs of a wide range of civilian applications. Among these applications, UAV-based agricultural mapping and monitoring have attracted significant attention from both the research and professional communities. The interest in UAV-based remote sensing for agricultural management is motivated by the need to maximize crop yield. Remote sensing-based crop yield prediction and estimation are primarily based on imaging systems with different spectral coverage and resolution (e.g., RGB and hyperspectral imaging systems). Due to the data volume, RGB imaging ismore » based on frame cameras, while hyperspectral sensors are primarily push-broom scanners. To cope with the limited endurance and payload constraints of low-cost UAVs, the agricultural research and professional communities have to rely on consumer-grade and light-weight sensors. However, the geometric fidelity of derived information from push-broom hyperspectral scanners is quite sensitive to the available position and orientation established through a direct geo-referencing unit onboard the imaging platform (i.e., an integrated Global Navigation Satellite System (GNSS) and Inertial Navigation System (INS). This paper presents an automated framework for the integration of frame RGB images, push-broom hyperspectral scanner data and consumer-grade GNSS/INS navigation data for accurate geometric rectification of the hyperspectral scenes. The approach relies on utilizing the navigation data, together with a modified Speeded-Up Robust Feature (SURF) detector and descriptor, for automating the identification of conjugate features in the RGB and hyperspectral imagery. The SURF modification takes into consideration the available direct geo-referencing information to improve the reliability of the matching procedure in the presence of repetitive texture within a

SIG: Multiple Views on Safety-Critical Automation: Aircraft, Autonomous Vehicles, Air Traffic Management and Satellite Ground Segments Perspectives

NASA Technical Reports Server (NTRS)

Feary, Michael; Palanque, Philippe; Martinie, Célia; Tscheligi, Manfred

2016-01-01

This SIG focuses on the engineering of automation in interactive critical systems. Automation has already been studied in a number of (sub-) disciplines and application fields: design, human factors, psychology, (software) engineering, aviation, health care, games. One distinguishing feature of the area we are focusing on is that in the field of interactive critical systems properties such as reliability, dependability, fault tolerance are as important as usability, user experience or overall acceptance issues. The SIG targets at two problem areas: first the engineering of the user interaction with (partly-) autonomous systems: how to design, build and assess autonomous behavior, especially in cases where there is a need to represent on the user interface both autonomous and interactive objects. An example of such integration is the representation of an unmanned aerial vehicle (UAV) (where no direct interaction is possible), together with aircrafts (that have to be instructed by an air traffic controller to avoid the UAV). Second the design and engineering of user interaction in general for autonomous objects/systems (for example a cruise control in a car or an autopilot in an aircraft). The goal of the SIG is to raise interest in the CHI community on the general aspects of automation and to identify a community of researchers and practitioners interested in those increasingly prominent issues of interfaces towards (semi)-autonomous systems. The expected audience should be interested in addressing the issues of integration of mainly unconnected research domains to formulate a new joint research agenda.

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

PubMed Central

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

2016-01-01

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. PMID:27171091

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

PubMed

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.

UAV-based high-throughput phenotyping in legume crops

NASA Astrophysics Data System (ADS)

Sankaran, Sindhuja; Khot, Lav R.; Quirós, Juan; Vandemark, George J.; McGee, Rebecca J.

2016-05-01

In plant breeding, one of the biggest obstacles in genetic improvement is the lack of proven rapid methods for measuring plant responses in field conditions. Therefore, the major objective of this research was to evaluate the feasibility of utilizing high-throughput remote sensing technology for rapid measurement of phenotyping traits in legume crops. The plant responses of several chickpea and peas varieties to the environment were assessed with an unmanned aerial vehicle (UAV) integrated with multispectral imaging sensors. Our preliminary assessment showed that the vegetation indices are strongly correlated (p<0.05) with seed yield of legume crops. Results endorse the potential of UAS-based sensing technology to rapidly measure those phenotyping traits.

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

Treesearch

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...

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

PubMed Central

Arabi, Sara; Sadik, Mohamed

2018-01-01

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. PMID:29751662

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

PubMed

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.

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

PubMed Central

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.

PubMed

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 Design of the Longitudinal Autopilot for the LSU-05 Unmanned Aerial Surveillance Vehicle

NASA Astrophysics Data System (ADS)

Fajar, Muhammad; Arifianto, Ony

2018-04-01

Longitudinal autopilot design for the LAPAN Surveillance Vehicle LSU-05 will be described in this paper. The LSU-05 is the most recent Unmanned Aerial Vehicle (UAV) project of the Aeronautics Technology Center (Pusat Teknologi Penerbangan – Pustekbang), LAPAN. This UAV is expected to be able to carry 30 kg of payload, four surveillance purposes. The longitudinal autopilot described in this paper consists of four modes, those are Pitch damper, Pitch Attitude Hold, Altitude Hold, and Speed Hold. The Autopilot of the UAV will be designed at four operating speeds, namely 15 m/s, 20 m/s, 25 m/s, and 30 m/. The Athena Vortex Lattice software is used to generate the aerodynamic model of the LSU-05. Non-linear longitudinal aircraft dynamics model is then developed in MATLAB/SIMULINK environment. Linearization of the non-linear model is performed using the linearization tool of SIMULINK. The controller is designed, based on the linear model of the aircraft in the state space form. A Proportional-Integral-Derivative (PID) controller structure is chosen, using root locus method to determine mainly the proportional (P) gain. Integral (I) and derivative (D) gain will only be used if the proportional gain can not achieve the desired target or if an overshoot / undershoot reduction is required. The overshoot/undershoot should not exceed 5% and settling time is less than 20 seconds. The controller designed is simulated using MATLAB and SIMULINK. Preliminary analysis of the controller performance shows that the controller can be used to stabilize the aircraft and to automatize the speed and altitude control throughout the considered speed range.

UAV Flight Control Using Distributed Actuation and Sensing

NASA Technical Reports Server (NTRS)

Barnwell, William G.; Heinzen, Stearns N.; Hall, Charles E., Jr.; Chokani, Ndaona; Raney, David L. (Technical Monitor)

2003-01-01

An array of effectors and sensors has been designed, tested and implemented on a Blended Wing Body Uninhabited Aerial Vehicle (UAV). This UAV is modified to serve as a flying, controls research, testbed. This effectorhensor array provides for the dynamic vehicle testing of controller designs and the study of decentralized control techniques. Each wing of the UAV is equipped with 12 distributed effectors that comprise a segmented array of independently actuated, contoured control surfaces. A single pressure sensor is installed near the base of each effector to provide a measure of deflections of the effectors. The UAV wings were tested in the North Carolina State University Subsonic Wind Tunnel and the pressure distribution that result from the deflections of the effectors are characterized. The results of the experiments are used to develop a simple, but accurate, prediction method, such that for any arrangement of the effector array the corresponding pressure distribution can be determined. Numerical analysis using the panel code CMARC verifies this prediction method.

Commercial vs professional UAVs for mapping

NASA Astrophysics Data System (ADS)

Nikolakopoulos, Konstantinos G.; Koukouvelas, Ioannis

2017-09-01

The continuous advancements in the technology behind Unmanned Aerial Vehicles (UAVs), in accordance with the consecutive decrease to their cost and the availability of photogrammetric software, make the use of UAVs an excellent tool for large scale mapping. In addition with the use of UAVs, the problems of increased costs, time consumption and the possible terrain accessibility problems, are significantly reduced. However, despite the growing number of UAV applications there has been a little quantitative assessment of UAV performance and of the quality of the derived products (orthophotos and Digital Surface Models). Here, we present results from field experiments designed to evaluate the accuracy of photogrammetrically-derived digital surface models (DSM) developed from imagery acquired with onboard digital cameras. We also show the comparison of the high resolution vs moderate resolution imagery for largescale geomorphic mapping. The acquired data analyzed in this study comes from a small commercial and a professional UAV. The test area was mapped using the same photogrammetric grid by the two UAVs. 3D models, DSMs and orthophotos were created using special software. Those products were compared to in situ survey measurements and the results are presented in this paper.

Development and evaluation of unmanned aerial vehicle (UAV) magnetometry systems

NASA Astrophysics Data System (ADS)

Parvar, Kiyavash

In this thesis, the procedure of conducting magnetic surveys from a UAV platform is investigated. In the process of evaluating UAVs for such surveys, magnetic sensors capable of operating on a UAV platform were tested using a terrestrial survey, as well as on a UAV-platform. Results were then compared to a model of the area generated using a proton precession magnetometer. Magnetic signature of the UAVs are discussed and impact values are calculated. For a better understanding of the magnetic fields around UAVs some micro-surveys were conducted with the help of a fluxgate magnetometer around two UAVs. Results of such surveys were used to determine a location to mount the magnetometer during the survey. A test survey over a known anomaly (a visible chromite outcrop in Oman) is conducted in order to determine the feasibility of using UAV-based magnetometry for chromite exploration. Observations were taken at two different elevations in order to generate a 3-D model of the magnetic field. Later, after applying upward continuation filters and comparing the calculated results to the real values, the reliability and uncertainty levels of such filters were investigated. Results show that magnetometery on UAV platforms is feasible. Unwanted signals can be noticeable and produce fake anomalies by the end of each line because of the swinging effect of the suspended magnetometer below the UAV. This should be reduced by hardware and software modifications i.e. applying non-linear filters and mounting the sensor on a rigid rod. Also, it was derived that the error level associated with upward continuation filters exceeds 45% and thus, using such filters instead of actual observations is not suggested in gradiometry. Moreover, 3-D magnetic gradient surveys can be beneficial for future inversion problems.

Towards a Transferable UAV-Based Framework for River Hydromorphological Characterization

PubMed Central

González, Rocío Ballesteros; Leinster, Paul; Wright, Ros

2017-01-01

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

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

PubMed

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.

Communication and Control for Fleets of Autonomous Underwater Vehicles

DTIC Science & Technology

2006-10-30

Washington State University (WSU) on fuzzy logic control systems [2-4] and autonomous vehicles [5-10]. The ALWSE-MC program developed at NAVSEA CSS was...rotating head sonar on crawlers as an additional sensor for navigation. We have previously investigated the use of video cameras on autonomous vehicles for...simulates autonomous vehicles performing mine reconnaissance/mapping, clearance, and surveillance in a littoral region. Three simulations were preformed

Intelligent Surveillance Robot with Obstacle Avoidance Capabilities Using Neural Network

PubMed Central

2015-01-01

For specific purpose, vision-based surveillance robot that can be run autonomously and able to acquire images from its dynamic environment is very important, for example, in rescuing disaster victims in Indonesia. In this paper, we propose architecture for intelligent surveillance robot that is able to avoid obstacles using 3 ultrasonic distance sensors based on backpropagation neural network and a camera for face recognition. 2.4 GHz transmitter for transmitting video is used by the operator/user to direct the robot to the desired area. Results show the effectiveness of our method and we evaluate the performance of the system. PMID:26089863

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

NASA Technical Reports Server (NTRS)

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.

Development of a Commercially Viable, Modular Autonomous Robotic Systems for Converting any Vehicle to Autonomous Control

NASA Technical Reports Server (NTRS)

Parish, David W.; Grabbe, Robert D.; Marzwell, Neville I.

1994-01-01

A Modular Autonomous Robotic System (MARS), consisting of a modular autonomous vehicle control system that can be retrofit on to any vehicle to convert it to autonomous control and support a modular payload for multiple applications is being developed. The MARS design is scalable, reconfigurable, and cost effective due to the use of modern open system architecture design methodologies, including serial control bus technology to simplify system wiring and enhance scalability. The design is augmented with modular, object oriented (C++) software implementing a hierarchy of five levels of control including teleoperated, continuous guidepath following, periodic guidepath following, absolute position autonomous navigation, and relative position autonomous navigation. The present effort is focused on producing a system that is commercially viable for routine autonomous patrolling of known, semistructured environments, like environmental monitoring of chemical and petroleum refineries, exterior physical security and surveillance, perimeter patrolling, and intrafacility transport applications.

Direct Georeferencing of Uav Data Based on Simple Building Structures

NASA Astrophysics Data System (ADS)

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

Curvature Continuous and Bounded Path Planning for Fixed-Wing UAVs.

PubMed

Wang, Xiaoliang; Jiang, Peng; Li, Deshi; Sun, Tao

2017-09-19

Unmanned Aerial Vehicles (UAVs) play an important role in applications such as data collection and target reconnaissance. An accurate and optimal path can effectively increase the mission success rate in the case of small UAVs. Although path planning for UAVs is similar to that for traditional mobile robots, the special kinematic characteristics of UAVs (such as their minimum turning radius) have not been taken into account in previous studies. In this paper, we propose a locally-adjustable, continuous-curvature, bounded path-planning algorithm for fixed-wing UAVs. To deal with the curvature discontinuity problem, an optimal interpolation algorithm and a key-point shift algorithm are proposed based on the derivation of a curvature continuity condition. To meet the upper bound for curvature and to render the curvature extrema controllable, a local replanning scheme is designed by combining arcs and Bezier curves with monotonic curvature. In particular, a path transition mechanism is built for the replanning phase using minimum curvature circles for a planning philosophy. Numerical results demonstrate that the analytical planning algorithm can effectively generate continuous-curvature paths, while satisfying the curvature upper bound constraint and allowing UAVs to pass through all predefined waypoints in the desired mission region.

Context-Based Urban Terrain Reconstruction from Uav-Videos for Geoinformation Applications

NASA Astrophysics Data System (ADS)

Bulatov, D.; Solbrig, P.; Gross, H.; Wernerus, P.; Repasi, E.; Heipke, C.

2011-09-01

Urban terrain reconstruction has many applications in areas of civil engineering, urban planning, surveillance and defense research. Therefore the needs of covering ad-hoc demand and performing a close-range urban terrain reconstruction with miniaturized and relatively inexpensive sensor platforms are constantly growing. Using (miniaturized) unmanned aerial vehicles, (M)UAVs, represents one of the most attractive alternatives to conventional large-scale aerial imagery. We cover in this paper a four-step procedure of obtaining georeferenced 3D urban models from video sequences. The four steps of the procedure - orientation, dense reconstruction, urban terrain modeling and geo-referencing - are robust, straight-forward, and nearly fully-automatic. The two last steps - namely, urban terrain modeling from almost-nadir videos and co-registration of models 6ndash; represent the main contribution of this work and will therefore be covered with more detail. The essential substeps of the third step include digital terrain model (DTM) extraction, segregation of buildings from vegetation, as well as instantiation of building and tree models. The last step is subdivided into quasi- intrasensorial registration of Euclidean reconstructions and intersensorial registration with a geo-referenced orthophoto. Finally, we present reconstruction results from a real data-set and outline ideas for future work.

Surveillance and reconnaissance ground system architecture

NASA Astrophysics Data System (ADS)

Devambez, Francois

2001-12-01

Modern conflicts induces various modes of deployment, due to the type of conflict, the type of mission, and phase of conflict. It is then impossible to define fixed architecture systems for surveillance ground segments. Thales has developed a structure for a ground segment based on the operational functions required, and on the definition of modules and networks. Theses modules are software and hardware modules, including communications and networks. This ground segment is called MGS (Modular Ground Segment), and is intended for use in airborne reconnaissance systems, surveillance systems, and U.A.V. systems. Main parameters for the definition of a modular ground image exploitation system are : Compliance with various operational configurations, Easy adaptation to the evolution of theses configurations, Interoperability with NATO and multinational forces, Security, Multi-sensors, multi-platforms capabilities, Technical modularity, Evolutivity Reduction of life cycle cost The general performances of the MGS are presented : type of sensors, acquisition process, exploitation of images, report generation, data base management, dissemination, interface with C4I. The MGS is then described as a set of hardware and software modules, and their organization to build numerous operational configurations. Architectures are from minimal configuration intended for a mono-sensor image exploitation system, to a full image intelligence center, for a multilevel exploitation of multi-sensor.

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

PubMed

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.

Implementation of Autonomous Navigation and Mapping using a Laser Line Scanner on a Tactical Unmanned Aerial Vehicle

DTIC Science & Technology

2011-12-01

study new multi-agent algorithms to avoid collision and obstacles. Others, including Hanford et al. [2], have tried to build low-cost experimental...2007. [2] S. D. Hanford , L. N. Long, and J. F. Horn, “A Small Semi-Autonomous Rotary-Wing Unmanned Air Vehicle ( UAV ),” 2003 AIAA Atmospheric

LUNA: low-flying UAV-based forest monitoring system

NASA Astrophysics Data System (ADS)

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

NASA Astrophysics Data System (ADS)

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.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Performance Evaluation of 3d Modeling Software for Uav Photogrammetry

NASA Astrophysics Data System (ADS)

Yanagi, H.; Chikatsu, H.

2016-06-01

UAV (Unmanned Aerial Vehicle) photogrammetry, which combines UAV and freely available internet-based 3D modeling software, is widely used as a low-cost and user-friendly photogrammetry technique in the fields such as remote sensing and geosciences. In UAV photogrammetry, only the platform used in conventional aerial photogrammetry is changed. Consequently, 3D modeling software contributes significantly to its expansion. However, the algorithms of the 3D modelling software are black box algorithms. As a result, only a few studies have been able to evaluate their accuracy using 3D coordinate check points. With this motive, Smart3DCapture and Pix4Dmapper were downloaded from the Internet and commercial software PhotoScan was also employed; investigations were performed in this paper using check points and images obtained from UAV.

Semantic-based surveillance video retrieval.

PubMed

Hu, Weiming; Xie, Dan; Fu, Zhouyu; Zeng, Wenrong; Maybank, Steve

2007-04-01

Visual surveillance produces large amounts of video data. Effective indexing and retrieval from surveillance video databases are very important. Although there are many ways to represent the content of video clips in current video retrieval algorithms, there still exists a semantic gap between users and retrieval systems. Visual surveillance systems supply a platform for investigating semantic-based video retrieval. In this paper, a semantic-based video retrieval framework for visual surveillance is proposed. A cluster-based tracking algorithm is developed to acquire motion trajectories. The trajectories are then clustered hierarchically using the spatial and temporal information, to learn activity models. A hierarchical structure of semantic indexing and retrieval of object activities, where each individual activity automatically inherits all the semantic descriptions of the activity model to which it belongs, is proposed for accessing video clips and individual objects at the semantic level. The proposed retrieval framework supports various queries including queries by keywords, multiple object queries, and queries by sketch. For multiple object queries, succession and simultaneity restrictions, together with depth and breadth first orders, are considered. For sketch-based queries, a method for matching trajectories drawn by users to spatial trajectories is proposed. The effectiveness and efficiency of our framework are tested in a crowded traffic scene.

High-speed laser communications in UAV scenarios

NASA Astrophysics Data System (ADS)

Griethe, Wolfgang; Gregory, Mark; Heine, Frank; Kämpfner, Hartmut

2011-05-01

Optical links, based on coherent homodyne detection and BPSK modulation with bidirectional data transmission of 5.6 Gbps over distances of about 5,000 km and BER of 10-8, have been sufficiently verified in space. The verification results show that this technology is suitable not only for space applications but also for applications in the troposphere. After a brief description of the Laser Communication Terminal (LCT) for space applications, the paper consequently discusses the future utilization of satellite-based optical data links for Beyond Line of Sight (BLOS) operations of High Altitude Long Endurance (HALE) Unmanned Aerial Vehicles (UAV). It is shown that the use of optical frequencies is the only logical consequence of an ever-increasing demand for bandwidth. In terms of Network Centric Warfare it is highly recommended that Unmanned Aircraft Systems (UAS) of the future should incorporate that technology which allows almost unlimited bandwidth. The advantages of optical communications especially for Intelligence, Surveillance and Reconnaissance (ISR) are underlined. Moreover, the preliminary design concept of an airborne laser communication terminal is described. Since optical bi-directional links have been tested between a LCT in space and a TESAT Optical Ground Station (OGS), preliminary analysis on tracking and BER performance and the impact of atmospheric disturbances on coherent links will be presented.

An automated 3D reconstruction method of UAV images

NASA Astrophysics Data System (ADS)

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.

Autonomous detection of crowd anomalies in multiple-camera surveillance feeds

NASA Astrophysics Data System (ADS)

Nordlöf, Jonas; Andersson, Maria

2016-10-01

A novel approach for autonomous detection of anomalies in crowded environments is presented in this paper. The proposed models uses a Gaussian mixture probability hypothesis density (GM-PHD) filter as feature extractor in conjunction with different Gaussian mixture hidden Markov models (GM-HMMs). Results, based on both simulated and recorded data, indicate that this method can track and detect anomalies on-line in individual crowds through multiple camera feeds in a crowded environment.

Curvature Continuous and Bounded Path Planning for Fixed-Wing UAVs

PubMed Central

Jiang, Peng; Li, Deshi; Sun, Tao

2017-01-01

Unmanned Aerial Vehicles (UAVs) play an important role in applications such as data collection and target reconnaissance. An accurate and optimal path can effectively increase the mission success rate in the case of small UAVs. Although path planning for UAVs is similar to that for traditional mobile robots, the special kinematic characteristics of UAVs (such as their minimum turning radius) have not been taken into account in previous studies. In this paper, we propose a locally-adjustable, continuous-curvature, bounded path-planning algorithm for fixed-wing UAVs. To deal with the curvature discontinuity problem, an optimal interpolation algorithm and a key-point shift algorithm are proposed based on the derivation of a curvature continuity condition. To meet the upper bound for curvature and to render the curvature extrema controllable, a local replanning scheme is designed by combining arcs and Bezier curves with monotonic curvature. In particular, a path transition mechanism is built for the replanning phase using minimum curvature circles for a planning philosophy. Numerical results demonstrate that the analytical planning algorithm can effectively generate continuous-curvature paths, while satisfying the curvature upper bound constraint and allowing UAVs to pass through all predefined waypoints in the desired mission region. PMID:28925960

An autonomous unmanned aerial vehicle sensing system for structural health monitoring of bridges

NASA Astrophysics Data System (ADS)

Reagan, Daniel; Sabato, Alessandro; Niezrecki, Christopher; Yu, Tzuyang; Wilson, Richard

2016-04-01

As civil infrastructure (i.e. bridges, railways, and tunnels) continues to age; the frequency and need to perform inspection more quickly on a broader scale increases. Traditional inspection and monitoring techniques (e.g., visual inspection, mechanical sounding, rebound hammer, cover meter, electrical potential measurements, ultrasound, and ground penetrating radar) may produce inconsistent results, require lane closure, are labor intensive and time-consuming. Therefore, new structural health monitoring systems must be developed that are automated, highly accurate, minimally invasive, and cost effective. Three-dimensional (3D) digital image correlation (DIC) systems have the merits of extracting full-field strain, deformation, and geometry profiles. These profiles can then be stitched together to generate a complete integrity map of the area of interest. Concurrently, unmanned aerial vehicles (UAVs) have emerged as valuable resources for positioning sensing equipment where it is either difficult to measure or poses a risk to human safety. UAVs have the capability to expedite the optical-based measurement process, offer increased accessibility, and reduce interference with local traffic. Within this work, an autonomous unmanned aerial vehicle in conjunction with 3D DIC was developed for monitoring bridges. The capabilities of the proposed system are demonstrated in both laboratory measurements and data collected from bridges currently in service. Potential measurement influences from platform instability, rotor vibration and positioning inaccuracy are also studied in a controlled environment. The results of these experiments show that the combination of autonomous flight with 3D DIC and other non-contact measurement systems provides a valuable and effective civil inspection platform.

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

PubMed

Eker, Remzi; Aydın, Abdurrahim; Hübl, Johannes

2017-12-19

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

Aeromagnetic Compensation for UAVs

NASA Astrophysics Data System (ADS)

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.

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

PubMed Central

Guerra, Edmundo

2018-01-01

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. PMID:29701722

Multisensor Equipped Uav/ugv for Automated Exploration

NASA Astrophysics Data System (ADS)

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.

a Comparison of Uav and Tls Data for Soil Roughness Assessment

NASA Astrophysics Data System (ADS)

Milenković, M.; Karel, W.; Ressl, C.; Pfeifer, N.

2016-06-01

Soil roughness represents fine-scale surface geometry which figures in many geophysical models. While static photogrammetric techniques (terrestrial images and laser scanning) have been recently proposed as a new source for deriving roughness heights, there is still need to overcome acquisition scale and viewing geometry issues. By contrast to the static techniques, images taken from unmanned aerial vehicles (UAV) can maintain near-nadir looking geometry over scales of several agricultural fields. This paper presents a pilot study on high-resolution, soil roughness reconstruction and assessment from UAV images over an agricultural plot. As a reference method, terrestrial laser scanning (TLS) was applied on a 10 m x 1.5 m subplot. The UAV images were self-calibrated and oriented within a bundle adjustment, and processed further up to a dense-matched digital surface model (DSM). The analysis of the UAV- and TLS-DSMs were performed in the spatial domain based on the surface autocorrelation function and the correlation length, and in the frequency domain based on the roughness spectrum and the surface fractal dimension (spectral slope). The TLS- and UAV-DSM differences were found to be under ±1 cm, while the UAV DSM showed a systematic pattern below this scale, which was explained by weakly tied sub-blocks of the bundle block. The results also confirmed that the existing TLS methods leads to roughness assessment up to 5 mm resolution. However, for our UAV data, this was not possible to achieve, though it was shown that for spatial scales of 12 cm and larger, both methods appear to be usable. Additionally, this paper suggests a method to propagate measurement errors to the correlation length.

Using UAV data for soil surface change detection at a loess field plot

NASA Astrophysics Data System (ADS)

Eltner, Anette; Baumgart, Philipp

2014-05-01

Application of unmanned aerial vehicles (UAV) denotes an increasing interest in geosciences due to major developments within the last years. Today, UAV are economical, reliable and flexible in usage. They provide a non-invasive method to measure the soil surface and its changes - e.g. due to erosion - with high resolution. Advances in digital photogrammetry and computer vision allow for fast and dense digital surface reconstruction from overlapping images. The study site is located in the Saxonian loess (Germany). The area is fragile due to erodible soils and intense agricultural utilisation. Hence, detectable soil surface changes are expected. The size of the field plot is 20 x 30 meters and the period of investigation lasts from October 2012 till July 2013 at which four surveys were performed. The UAV deployed in this study is equipped with a compact camera which is attached to an active stabilising camera mount. In addition, the micro drone integrates GPS and IMU that enables autonomous surveys with programmed flight patterns. About 100 photos are needed to cover the study site at a minimal flying height of eight metres and 65%/80% image overlap. For multi-temporal comparison a stable local reference system is established. Total station control of the signalised ground control points confirms two mm accuracy for the study period. To estimate the accuracy of the digital surface models (DSM) derived from the UAV images a comparison to DSM from terrestrial laser scanning (TLS) is conducted. The standard deviation of differences amounts five millimetres. To analyse surface changes methods from image processing are applied to the DSM. Erosion rills could be extracted for quantitative and qualitative consideration. Furthermore, volumetric changes are measured. First results indicate levelling processes during the winter season and reveal rill and inter-rill erosion during spring and summer season.

Vision based control of unmanned aerial vehicles with applications to an autonomous four-rotor helicopter, quadrotor

NASA Astrophysics Data System (ADS)

Altug, Erdinc

Our work proposes a vision-based stabilization and output tracking control method for a model helicopter. This is a part of our effort to produce a rotorcraft based autonomous Unmanned Aerial Vehicle (UAV). Due to the desired maneuvering ability, a four-rotor helicopter has been chosen as the testbed. On previous research on flying vehicles, vision is usually used as a secondary sensor. Unlike previous research, our goal is to use visual feedback as the main sensor, which is not only responsible for detecting where the ground objects are but also for helicopter localization. A novel two-camera method has been introduced for estimating the full six degrees of freedom (DOF) pose of the helicopter. This two-camera system consists of a pan-tilt ground camera and an onboard camera. The pose estimation algorithm is compared through simulation to other methods, such as four-point, and stereo method and is shown to be less sensitive to feature detection errors. Helicopters are highly unstable flying vehicles; although this is good for agility, it makes the control harder. To build an autonomous helicopter, two methods of control are studied---one using a series of mode-based, feedback linearizing controllers and the other using a back-stepping control law. Various simulations with 2D and 3D models demonstrate the implementation of these controllers. We also show global convergence of the 3D quadrotor controller even with large calibration errors or presence of large errors on the image plane. Finally, we present initial flight experiments where the proposed pose estimation algorithm and non-linear control techniques have been implemented on a remote-controlled helicopter. The helicopter was restricted with a tether to vertical, yaw motions and limited x and y translations.

Applications of UAVs in row-crop agriculture: advantages and limitations

NASA Astrophysics Data System (ADS)

Basso, B.; Putnam, G.; Price, R.; Zhang, J.

2016-12-01

The application of Unmanned Aerial Vehicles (UAV) to monitor agricultural fields has increased over the last few years due to advances in the technology, sensors, post-processing software for image analysis, along with more favorable regulations that allowed UAVs to be flown for commercial use. UAV have several capabilities depending on the type of sensors that are mounted onboard. The most widely used application remains crop scouting to identify areas within fields where the crops underperform for various reasons (nutritional status and water stress, presence of weeds, poor stands etc). In this talk, we present the preliminary results of UAVs field based research to better understand spatial and temporal variability of crop yield. Their advantage in providing timely information is critical, but adaptive management requires a system approach to account for the interactions occurring between genetics, environment and management.

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

NASA Astrophysics Data System (ADS)

Sayfeddine, Daher

2018-03-01

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

Briefing to University of Porto on NASA Airborne Science Program and Ames UAVs

NASA Technical Reports Server (NTRS)

Fladeland, Matthew

2015-01-01

NASA Ames is exploring a partnership with the University of Portugal to jointly develop and test new autonomous vehicle technologies. As part of the discussions I will be briefing the University of Portugal faculty on the NASA Airborne Science Program (ASP) and associated activities at NASA Ames Research Center. The presentation will communicate the requirements that drive the program, the assets available to NASA researchers, and discuss research projects that have used unmanned aircraft systems including MIZOPEX, Surprise Valley, and Florida Keys Coral Reef assessment. Other topics will include the SIERRA and Dragon Eye UAV projects operated at Ames.

UAV Monitoring for Enviromental Management in Galapagos Islands

NASA Astrophysics Data System (ADS)

Ballari, D.; Orellana, D.; Acosta, E.; Espinoza, A.; Morocho, V.

2016-06-01

In the Galapagos Islands, where 97% of the territory is protected and ecosystem dynamics are highly vulnerable, timely and accurate information is key for decision making. An appropriate monitoring system must meet two key features: on one hand, being able to capture information in a systematic and regular basis, and on the other hand, to quickly gather information on demand for specific purposes. The lack of such a system for geographic information limits the ability of Galapagos Islands' institutions to evaluate and act upon environmental threats such as invasive species spread and vegetation degradation. In this context, the use of UAVs (unmanned aerial vehicles) for capturing georeferenced images is a promising technology for environmental monitoring and management. This paper explores the potential of UAV images for monitoring degradation of littoral vegetation in Puerto Villamil (Isabela Island, Galapagos, Ecuador). Imagery was captured using two camera types: Red Green Blue (RGB) and Infrarred Red Green (NIR). First, vegetation presence was identified through NDVI. Second, object-based classification was carried out for characterization of vegetation vigor. Results demonstrates the feasibility of UAV technology for base-line studies and monitoring on the amount and vigorousness of littoral vegetation in the Galapagos Islands. It is also showed that UAV images are not only useful for visual interpretation and object delineation, but also to timely produce useful thematic information for environmental management.

Autonomous Cryogenic Load Operations: Knowledge-Based Autonomous Test Engineer

NASA Technical Reports Server (NTRS)

Schrading, J. Nicolas

2013-01-01

The Knowledge-Based Autonomous Test Engineer (KATE) program has a long history at KSC. Now a part of the Autonomous Cryogenic Load Operations (ACLO) mission, this software system has been sporadically developed over the past 20 years. Originally designed to provide health and status monitoring for a simple water-based fluid system, it was proven to be a capable autonomous test engineer for determining sources of failure in the system. As part of a new goal to provide this same anomaly-detection capability for a complicated cryogenic fluid system, software engineers, physicists, interns and KATE experts are working to upgrade the software capabilities and graphical user interface. Much progress was made during this effort to improve KATE. A display of the entire cryogenic system's graph, with nodes for components and edges for their connections, was added to the KATE software. A searching functionality was added to the new graph display, so that users could easily center their screen on specific components. The GUI was also modified so that it displayed information relevant to the new project goals. In addition, work began on adding new pneumatic and electronic subsystems into the KATE knowledge base, so that it could provide health and status monitoring for those systems. Finally, many fixes for bugs, memory leaks, and memory errors were implemented and the system was moved into a state in which it could be presented to stakeholders. Overall, the KATE system was improved and necessary additional features were added so that a presentation of the program and its functionality in the next few months would be a success.

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

NASA Astrophysics Data System (ADS)

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.

Short-term change detection for UAV video

NASA Astrophysics Data System (ADS)

Saur, Günter; Krüger, Wolfgang

2012-11-01

In the last years, there has been an increased use of unmanned aerial vehicles (UAV) for video reconnaissance and surveillance. An important application in this context is change detection in UAV video data. Here we address short-term change detection, in which the time between observations ranges from several minutes to a few hours. We distinguish this task from video motion detection (shorter time scale) and from long-term change detection, based on time series of still images taken between several days, weeks, or even years. Examples for relevant changes we are looking for are recently parked or moved vehicles. As a pre-requisite, a precise image-to-image registration is needed. Images are selected on the basis of the geo-coordinates of the sensor's footprint and with respect to a certain minimal overlap. The automatic imagebased fine-registration adjusts the image pair to a common geometry by using a robust matching approach to handle outliers. The change detection algorithm has to distinguish between relevant and non-relevant changes. Examples for non-relevant changes are stereo disparity at 3D structures of the scene, changed length of shadows, and compression or transmission artifacts. To detect changes in image pairs we analyzed image differencing, local image correlation, and a transformation-based approach (multivariate alteration detection). As input we used color and gradient magnitude images. To cope with local misalignment of image structures we extended the approaches by a local neighborhood search. The algorithms are applied to several examples covering both urban and rural scenes. The local neighborhood search in combination with intensity and gradient magnitude differencing clearly improved the results. Extended image differencing performed better than both the correlation based approach and the multivariate alternation detection. The algorithms are adapted to be used in semi-automatic workflows for the ABUL video exploitation system of Fraunhofer

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

PubMed

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.

Long-term monitoring of a large landslide by using an Unmanned Aerial Vehicle (UAV)

NASA Astrophysics Data System (ADS)

Lindner, Gerald; Schraml, Klaus; Mansberger, Reinfried; Hübl, Johannes

2015-04-01

Currently UAVs become more and more important in various scientific areas, including forestry, precision farming, archaeology and hydrology. Using these drones in natural hazards research enables a completely new level of data acquisition being flexible of site, invariant in time, cost-efficient and enabling arbitrary spatial resolution. In this study, a rotary-wing Mini-UAV carrying a DSLR camera was used to acquire time series of overlapping aerial images. These photographs were taken as input to extract Digital Surface Models (DSM) as well as orthophotos in the area of interest. The "Pechgraben" area in Upper Austria has a catchment area of approximately 2 km². Geology is mainly dominated by limestone and sandstone. Caused by heavy rainfalls in the late spring of 2013, an area of about 70 ha began to move towards the village in the valley. In addition to the urgent measures, the slow-moving landslide was monitored approximately every month over a time period of more than 18 months. A detailed documentation of the change process was the result. Moving velocities and height differences were quantified and validated using a dense network of Ground Control Points (GCP). For further analysis, 14 image flights with a total amount of 10.000 photographs were performed to create multi-temporal geodata in in sub-decimeter-resolution for two depicted areas of the landslide. Using a UAV for this application proved to be an excellent choice, as it allows short repetition times, low flying heights and high spatial resolution. Furthermore, the UAV acts almost weather independently as well as highly autonomously. High-quality results can be expected within a few hours after the photo flight. The UAV system performs very well in an alpine environment. Time series of the assessed geodata detect changes in topography and provide a long-term documentation of the measures taken in order to stop the landslide and to prevent infrastructure from damage.

Analyzing the threat of unmanned aerial vehicles (UAV) to nuclear facilities

DOE PAGES

Solodov, Alexander; Williams, Adam; Al Hanaei, Sara; ...

2017-04-18

Unmanned aerial vehicles (UAV) are among the major growing technologies that have many beneficial applications, yet they can also pose a significant threat. Recently, several incidents occurred with UAVs violating privacy of the public and security of sensitive facilities, including several nuclear power plants in France. The threat of UAVs to the security of nuclear facilities is of great importance and is the focus of this work. This paper presents an overview of UAV technology and classification, as well as its applications and potential threats. We show several examples of recent security incidents involving UAVs in France, USA, and Unitedmore » Arab Emirates. Further, the potential threats to nuclear facilities and measures to prevent them are evaluated. The importance of measures for detection, delay, and response (neutralization) of UAVs at nuclear facilities are discussed. An overview of existing technologies along with their strength and weaknesses are shown. Finally, the results of a gap analysis in existing approaches and technologies is presented in the form of potential technological and procedural areas for research and development. Furthermore based on this analysis, directions for future work in the field can be devised and prioritized.« less

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

NASA Technical Reports Server (NTRS)

Dowell, Susan; Morphew, Ephimia; Shively, Jay

2003-01-01

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

Research for new UAV capabilities

DOE Office of Scientific and Technical Information (OSTI.GOV)

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.

Demonstration of UAV deployment and control of mobile wireless sensing networks for modal analysis of structures

NASA Astrophysics Data System (ADS)

Zhou, Hao; Hirose, Mitsuhito; Greenwood, William; Xiao, Yong; Lynch, Jerome; Zekkos, Dimitrios; Kamat, Vineet

2016-04-01

Unmanned aerial vehicles (UAVs) can serve as a powerful mobile sensing platform for assessing the health of civil infrastructure systems. To date, the majority of their uses have been dedicated to vision and laser-based spatial imaging using on-board cameras and LiDAR units, respectively. Comparatively less work has focused on integration of other sensing modalities relevant to structural monitoring applications. The overarching goal of this study is to explore the ability for UAVs to deploy a network of wireless sensors on structures for controlled vibration testing. The study develops a UAV platform with an integrated robotic gripper that can be used to install wireless sensors in structures, drop a heavy weight for the introduction of impact loads, and to uninstall wireless sensors for reinstallation elsewhere. A pose estimation algorithm is embedded in the UAV to estimate the location of the UAV during sensor placement and impact load introduction. The Martlet wireless sensor network architecture is integrated with the UAV to provide the UAV a mobile sensing capability. The UAV is programmed to command field deployed Martlets, aggregate and temporarily store data from the wireless sensor network, and to communicate data to a fixed base station on site. This study demonstrates the integrated UAV system using a simply supported beam in the lab with Martlet wireless sensors placed by the UAV and impact load testing performed. The study verifies the feasibility of the integrated UAV-wireless monitoring system architecture with accurate modal characteristics of the beam estimated by modal analysis.

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

NASA Astrophysics Data System (ADS)

Haubeck, K.; Prinz, T.

2013-08-01

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

Uav for Geodata Acquisition in Agricultureal and Forestal Applications

NASA Astrophysics Data System (ADS)

Reidelstürz, P.; Schrenk, L.; Littmann, W.

2011-09-01

In the field of precision-farming research, solutions are worked out to combine ecological and economical requirements in a harmonic way. Integrating hightech in agricultural machinery, natural differences in the fields (biodiversity) can be detected and considered to economize agricultural resources and to give respect to natural ecological variability at the same time. Using precision farming resources, machining - and labour time can be economized, productivness can be improved, environmental burden can be discharged and documentation of production processes can be improved. To realize precision farming it is essential to make contemporary large scale data of the biodiversity in the field available. In the last years effectual traktor based equipment for real time precision farming applications was developed. Using remote sensing, biomass diversity of the field can be considered while applicating operating ressources economicly. Because these large scale data aquisition depends on expensive tractor based inspections, capable Unmanned Aerial Vehicles (UAVs) could complement or in special situations even replace such tractor based data aquisition needed for the realization of precision farming strategies. The specific advantages and application slots of UAVs seems to be ideal for the usage in the field of precision farming. For example the size of even large agricultural fields in germany can be managed even by smaller UAVs. Data can be captured spontaneously, promptly, in large scale, with less respect of weather conditions. In agricultural regions UAV flights can be arranged in visual range as actually the legislator requires in germany, especially because the use of autopilotsystems in fact is nessecary to assure regular area-wide data without gaps but not to fly in non-visible regions. Also a minimized risk of hazard is given, flying UAVs over deserted agricultural areas. In a first stage CIS GmbH cooperated with "Institute For Flightsystems" of the University

Development of High Altitude UAV Weather Radars for Hurricane Research

NASA Technical Reports Server (NTRS)

Heymsfield, Gerald; Li, Li-Hua

2005-01-01

A proposed effort within NASA called (ASHE) over the past few years was aimed at studying the genesis of tropical disturbances off the east coast of Africa. This effort was focused on using an instrumented Global Hawk UAV with high altitude (%Ok ft) and long duration (30 h) capability. While the Global Hawk availability remains uncertain, development of two relevant instruments, a Doppler radar (URAD - UAV Radar) and a backscatter lidar (CPL-UAV - Cloud Physics Lidar), are in progress. The radar to be discussed here is based on two previous high-altitude, autonomously operating radars on the NASA ER-2 aircraft, the ER-2 Doppler Radar (EDOP) at X-band (9.6 GHz), and the Cloud Radar System (CRS) at W- band (94 GHz). The nadir-pointing EDOP and CRS radars profile vertical reflectivity structure and vertical Doppler winds in precipitation and clouds, respectively. EDOP has flown in all of the CAMEX flight series to study hurricanes over storms such as Hurricanes Bonnie, Humberto, Georges, Erin, and TS Chantal. These radars were developed at Goddard over the last decade and have been used for satellite algorithm development and validation (TRMM and Cloudsat), and for hurricane and convective storm research. We describe here the development of URAD that will measure wind and reflectivity in hurricanes and other weather systems from a top down, high-altitude view. URAD for the Global Hawk consists of two subsystems both of which are at X-band (9.3-9.6 GHz) and Doppler: a nadir fixed-beam Doppler radar for vertical motion and precipitation measurement, and a Conical scanning radar for horizontal winds in cloud and at the surface, and precipitation structure. These radars are being designed with size, weight, and power consumption suitable for the Global Hawk and other UAV's. The nadir radar uses a magnetron transmitter and the scanning radar uses a TWT transmitter. With conical scanning of the radar at a 35" incidence angle over an ocean surface in the absence of

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

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

UAV magnetometry in mineral exploration and infrastructure detection

NASA Astrophysics Data System (ADS)

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.

Technology Challenges in Small UAV Development

NASA Technical Reports Server (NTRS)

Logan, Michael J.; Vranas, Thomas L.; Motter, Mark; Shams, Qamar; Pollock, Dion S.

2005-01-01

Development of highly capable small UAVs present unique challenges for technology protagonists. Size constraints, the desire for ultra low cost and/or disposable platforms, lack of capable design and analysis tools, and unique mission requirements all add to the level of difficulty in creating state-of-the-art small UAVs. This paper presents the results of several small UAV developments, the difficulties encountered, and proposes a list of technology shortfalls that need to be addressed.

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

PubMed

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

2017-09-29

The use of Unmanned Aerial Vehicles (UAVs) has increased significantly in recent years. On-board integrated navigation sensors are a key component of UAVs' flight control systems and are essential for flight safety. In order to ensure flight safety, timely and effective navigation sensor fault detection capability is required. In this paper, a novel data-driven Adaptive Neuron Fuzzy Inference System (ANFIS)-based approach is presented for the detection of on-board navigation sensor faults in UAVs. Contrary to the classic UAV sensor fault detection algorithms, based on predefined or modelled faults, the proposed algorithm combines an online data training mechanism with the ANFIS-based decision system. The main advantages of this algorithm are that it allows real-time model-free residual analysis from Kalman Filter (KF) estimates and the ANFIS to build a reliable fault detection system. In addition, it allows fast and accurate detection of faults, which makes it suitable for real-time applications. Experimental results have demonstrated the effectiveness of the proposed fault detection method in terms of accuracy and misdetection rate.

Extended Range Aerial Delivery Using an Unpowered Autonomous Tailless UAV

NASA Astrophysics Data System (ADS)

Kraft, Tyler E.

An alternative approach for precision aerial delivery utilizing a flying wing for controllable forward glide is presented. Although effective, current delivery methods either display a lack of control, or require close standoff distances, potentially endangering aircraft personnel as well as bystanders. Hardware-in-the-loop simulations provide an efficient method for evaluating various wing designs and actuation configurations. Four control surface configurations are presented and evaluated, encompassing traditional aircraft and ram-air parafoil control approaches. Fixed-wing and multirotor unmanned aircraft-based flight tests were conducted to evaluate the controllability and handling performance of the various configurations of both a fixed wing model and a model with collapsing wings. A manufacturing process was developed to allow repeatable results in the field using cheap, mostly disposable materials. A powered flying wing model was used to maximize data collection in later stages of software development. Data collected during flight tests was used to create a model of the system and develop a Nonlinear Dynamic Inversion controller for autonomous flight. The NDI controller was able to provide stable flight in pitch, but will need more development to control yaw, instead an intentional bias was built in to show proof of concept for direct yaw control. The results demonstrate the feasibility of the flying wing-based aerial delivery; however, significant challenges remain regarding the stability and scalability of the system.

UAV-LiDAR accuracy and comparison to Structure from Motion photogrammetry

NASA Astrophysics Data System (ADS)

Kucharczyk, M.; Hugenholtz, C.; Zou, X.; Nesbit, P. R.; Barchyn, T.

2016-12-01

We compare the spatial accuracy of a UAV-LiDAR system with Structure from Motion (SfM) photogrammetry. UAV-based LiDAR remote sensing potentially offers advantages over SfM photogrammetry in vegetated terrain, particularly with respect to canopy penetration and related measurements of ground surface elevation and vegetation height; however, little quantitative evidence has been presented to date. To address this, we performed a case study at a field site in Alberta, Canada with six different land cover types: short grass, tall grass, short shrubs, tall shrubs, deciduous trees, and coniferous trees. Both UAV datasets were acquired on the same day. The SfM dataset was derived from images acquired by a senseFly eBee fixed-wing UAV equipped with a 16.1 megapixel RGB camera. The UAV-LiDAR system is a proprietary design that consists of a single-rotor helicopter (2-m rotor diameter) equipped with a Riegl VUX-1UAV laser scanner, KVH 1750 inertial measurement unit, and dual NovAtel GNSS receivers. We measured vegetation height from at least 30 samples in each land cover type and acquired check point measurements to determine horizontal and vertical accuracy. Vegetation height was measured manually for grasses and shrubs with a level staff, and with a total station for trees. Coordinates of horizontal and vertical check points were surveyed with real-time kinematic (RTK) GNSS. We followed standard methods for computing horizontal and vertical accuracies based on the 2015 guidelines from the American Society of Photogrammetry and Remote Sensing. Results will be presented at the AGU Fall Meeting.

Automatic detection of blurred images in UAV image sets

NASA Astrophysics Data System (ADS)

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

D Reconstruction from Uav-Based Hyperspectral Images

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Distributed pheromone-based swarming control of unmanned air and ground vehicles for RSTA

NASA Astrophysics Data System (ADS)

Sauter, John A.; Mathews, Robert S.; Yinger, Andrew; Robinson, Joshua S.; Moody, John; Riddle, Stephanie

2008-04-01

The use of unmanned vehicles in Reconnaissance, Surveillance, and Target Acquisition (RSTA) applications has received considerable attention recently. Cooperating land and air vehicles can support multiple sensor modalities providing pervasive and ubiquitous broad area sensor coverage. However coordination of multiple air and land vehicles serving different mission objectives in a dynamic and complex environment is a challenging problem. Swarm intelligence algorithms, inspired by the mechanisms used in natural systems to coordinate the activities of many entities provide a promising alternative to traditional command and control approaches. This paper describes recent advances in a fully distributed digital pheromone algorithm that has demonstrated its effectiveness in managing the complexity of swarming unmanned systems. The results of a recent demonstration at NASA's Wallops Island of multiple Aerosonde Unmanned Air Vehicles (UAVs) and Pioneer Unmanned Ground Vehicles (UGVs) cooperating in a coordinated RSTA application are discussed. The vehicles were autonomously controlled by the onboard digital pheromone responding to the needs of the automatic target recognition algorithms. UAVs and UGVs controlled by the same pheromone algorithm self-organized to perform total area surveillance, automatic target detection, sensor cueing, and automatic target recognition with no central processing or control and minimal operator input. Complete autonomy adds several safety and fault tolerance requirements which were integrated into the basic pheromone framework. The adaptive algorithms demonstrated the ability to handle some unplanned hardware failures during the demonstration without any human intervention. The paper describes lessons learned and the next steps for this promising technology.

Accuracy evaluation of 3D lidar data from small UAV

NASA Astrophysics Data System (ADS)

Tulldahl, H. M.; Bissmarck, Fredrik; Larsson, Hâkan; Grönwall, Christina; Tolt, Gustav

2015-10-01

A UAV (Unmanned Aerial Vehicle) with an integrated lidar can be an efficient system for collection of high-resolution and accurate three-dimensional (3D) data. In this paper we evaluate the accuracy of a system consisting of a lidar sensor on a small UAV. High geometric accuracy in the produced point cloud is a fundamental qualification for detection and recognition of objects in a single-flight dataset as well as for change detection using two or several data collections over the same scene. Our work presented here has two purposes: first to relate the point cloud accuracy to data processing parameters and second, to examine the influence on accuracy from the UAV platform parameters. In our work, the accuracy is numerically quantified as local surface smoothness on planar surfaces, and as distance and relative height accuracy using data from a terrestrial laser scanner as reference. The UAV lidar system used is the Velodyne HDL-32E lidar on a multirotor UAV with a total weight of 7 kg. For processing of data into a geographically referenced point cloud, positioning and orientation of the lidar sensor is based on inertial navigation system (INS) data combined with lidar data. The combination of INS and lidar data is achieved in a dynamic calibration process that minimizes the navigation errors in six degrees of freedom, namely the errors of the absolute position (x, y, z) and the orientation (pitch, roll, yaw) measured by GPS/INS. Our results show that low-cost and light-weight MEMS based (microelectromechanical systems) INS equipment with a dynamic calibration process can obtain significantly improved accuracy compared to processing based solely on INS data.

Application Possibility of Smartphone as Payload for Photogrammetric Uav System

NASA Astrophysics Data System (ADS)

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.

Three-dimensional estimates of tree canopies: Scaling from high-resolution UAV data to satellite observations

NASA Astrophysics Data System (ADS)

Sankey, T.; Donald, J.; McVay, J.

2015-12-01

High resolution remote sensing images and datasets are typically acquired at a large cost, which poses big a challenge for many scientists. Northern Arizona University recently acquired a custom-engineered, cutting-edge UAV and we can now generate our own images with the instrument. The UAV has a unique capability to carry a large payload including a hyperspectral sensor, which images the Earth surface in over 350 spectral bands at 5 cm resolution, and a lidar scanner, which images the land surface and vegetation in 3-dimensions. Both sensors represent the newest available technology with very high resolution, precision, and accuracy. Using the UAV sensors, we are monitoring the effects of regional forest restoration treatment efforts. Individual tree canopy width and height are measured in the field and via the UAV sensors. The high-resolution UAV images are then used to segment individual tree canopies and to derive 3-dimensional estimates. The UAV image-derived variables are then correlated to the field-based measurements and scaled to satellite-derived tree canopy measurements. The relationships between the field-based and UAV-derived estimates are then extrapolated to a larger area to scale the tree canopy dimensions and to estimate tree density within restored and control forest sites.

Uav Cameras: Overview and Geometric Calibration Benchmark

NASA Astrophysics Data System (ADS)

Cramer, M.; Przybilla, H.-J.; Zurhorst, A.

2017-08-01

Different UAV platforms and sensors are used in mapping already, many of them equipped with (sometimes) modified cameras as known from the consumer market. Even though these systems normally fulfil their requested mapping accuracy, the question arises, which system performs best? This asks for a benchmark, to check selected UAV based camera systems in well-defined, reproducible environments. Such benchmark is tried within this work here. Nine different cameras used on UAV platforms, representing typical camera classes, are considered. The focus is laid on the geometry here, which is tightly linked to the process of geometrical calibration of the system. In most applications the calibration is performed in-situ, i.e. calibration parameters are obtained as part of the project data itself. This is often motivated because consumer cameras do not keep constant geometry, thus, cannot be seen as metric cameras. Still, some of the commercial systems are quite stable over time, as it was proven from repeated (terrestrial) calibrations runs. Already (pre-)calibrated systems may offer advantages, especially when the block geometry of the project does not allow for a stable and sufficient in-situ calibration. Especially for such scenario close to metric UAV cameras may have advantages. Empirical airborne test flights in a calibration field have shown how block geometry influences the estimated calibration parameters and how consistent the parameters from lab calibration can be reproduced.

Energy-Efficient Systems Eliminate Icing Danger for UAVs

NASA Technical Reports Server (NTRS)

2010-01-01

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

Autonomous and Autonomic Swarms

NASA Technical Reports Server (NTRS)

Hinchey, Michael G.; Rash, James L.; Truszkowski, Walter F.; Rouff, Christopher A.; Sterritt, Roy

2005-01-01

A watershed in systems engineering is represented by the advent of swarm-based systems that accomplish missions through cooperative action by a (large) group of autonomous individuals each having simple capabilities and no global knowledge of the group s objective. Such systems, with individuals capable of surviving in hostile environments, pose unprecedented challenges to system developers. Design and testing and verification at much higher levels will be required, together with the corresponding tools, to bring such systems to fruition. Concepts for possible future NASA space exploration missions include autonomous, autonomic swarms. Engineering swarm-based missions begins with understanding autonomy and autonomicity and how to design, test, and verify systems that have those properties and, simultaneously, the capability to accomplish prescribed mission goals. Formal methods-based technologies, both projected and in development, are described in terms of their potential utility to swarm-based system developers.

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

PubMed

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.

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

PubMed Central

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

2016-01-01

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. PMID:27171084

Cloud-Assisted UAV Data Collection for Multiple Emerging Events in Distributed WSNs.

PubMed

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.

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

NASA Astrophysics Data System (ADS)

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

2016-05-01

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

Prognostics Applied to Electric Propulsion UAV

NASA Technical Reports Server (NTRS)

Goebel, Kai; Saha, Bhaskar

2013-01-01

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

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

PubMed

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

2015-11-27

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

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

PubMed Central

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

2015-01-01

The article presents an approach to the control of a UAV on the basis of 3D landmark observations. The novelty of the work is the usage of the 3D RANSAC algorithm developed on the basis of the landmarks’ position prediction with the aid of a modified Kalman-type filter. Modification of the filter based on the pseudo-measurements approach permits obtaining unbiased UAV position estimation with quadratic error characteristics. Modeling of UAV flight on the basis of the suggested algorithm shows good performance, even under significant external perturbations. PMID:26633394

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

NASA Astrophysics Data System (ADS)

Larrabee, Trenton Jameson

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

Extending Quad-Rotor UAV Autonomy with Onboard Image Processing

DTIC Science & Technology

2015-03-01

of this collection of information, including suggestions for reducing this burden, to Washington headquarters Services , Directorate for Information...vehicles perform a variety of tasks, from strike to surveillance to communications . Some vehicles, like the MQ-1 Predator, are operated remotely by...a human operator; others, like the BGM-109 Tomahawk cruise missile, can maneuver autonomously by following pre-programmed control law . Unmanned

Analysis of MLS Based Surveillance System (MLSS) Concepts

DOT National Transportation Integrated Search

1989-04-01

This report examines a number of surveillance system concepts to support safe independent runway approaches and converging runways under weather conditons. All surveillance conepts are based on the use of MLS signals. The resultin surveillance is ava...

Air Force UAVs: The Secret History

DTIC Science & Technology

2010-07-01

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

The remote sensing data from your UAV probably isn't scientific, but it should be!

NASA Astrophysics Data System (ADS)

McKee, Mac

2017-05-01

The application of unmanned autonomous vehicles (UAVs), or "drones", to generate data to support better decisions for agricultural management and farm operations is a relatively new technology that is now beginning to enter the market. This potentially disruptive technology is still in its infancy and must mature in ways that the current market cannot clearly foresee and probably does not fully understand. Major technical and regulatory hurdles must be overcome before the full potential of this remote sensing technology can be realized in agricultural applications. Further, and most importantly, buyers and sellers in today's market must both gain a deeper understanding of the potential that this technology might achieve and the technical challenges that must be met before advances that will bring significant market value will be possible. A lack of understanding of some of the basic concepts of remote sensing can translate into poor decisions regarding the acquisition and deployment of UAVs in agriculture. This paper focuses on some of the details of remote sensing that few growers, and, indeed, few university researchers fully understand.

Air Force UAV’s: The Secret History

DTIC Science & Technology

2010-07-01

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

Wetland Assessment Using Unmanned Aerial Vehicle (uav) Photogrammetry

NASA Astrophysics Data System (ADS)

Boon, M. A.; Greenfield, R.; Tesfamichael, S.

2016-06-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

Egnos-Based Multi-Sensor Accurate and Reliable Navigation in Search-And Missions with Uavs

NASA Astrophysics Data System (ADS)

Molina, P.; Colomina, I.; Vitoria, T.; Silva, P. F.; Stebler, Y.; Skaloud, J.; Kornus, W.; Prades, R.

2011-09-01

This paper will introduce and describe the goals, concept and overall approach of the European 7th Framework Programme's project named CLOSE-SEARCH, which stands for 'Accurate and safe EGNOS-SoL Navigation for UAV-based low-cost SAR operations'. The goal of CLOSE-SEARCH is to integrate in a helicopter-type unmanned aerial vehicle, a thermal imaging sensor and a multi-sensor navigation system (based on the use of a Barometric Altimeter (BA), a Magnetometer (MAGN), a Redundant Inertial Navigation System (RINS) and an EGNOS-enabled GNSS receiver) with an Autonomous Integrity Monitoring (AIM) capability, to support the search component of Search-And-Rescue operations in remote, difficult-to-access areas and/or in time critical situations. The proposed integration will result in a hardware and software prototype that will demonstrate an end-to-end functionality, that is to fly in patterns over a region of interest (possibly inaccessible) during day or night and also under adverse weather conditions and locate there disaster survivors or lost people through the detection of the body heat. This paper will identify the technical challenges of the proposed approach, from navigating with a BA/MAGN/RINS/GNSS-EGNOSbased integrated system to the interpretation of thermal images for person identification. Moreover, the AIM approach will be described together with the proposed integrity requirements. Finally, this paper will show some results obtained in the project during the first test campaign performed on November 2010. On that day, a prototype was flown in three different missions to assess its high-level performance and to observe some fundamental mission parameters as the optimal flying height and flying speed to enable body recognition. The second test campaign is scheduled for the end of 2011.

Feasibility of Using Synthetic Aperture Radar to Aid UAV Navigation

PubMed Central

Nitti, Davide O.; Bovenga, Fabio; Chiaradia, Maria T.; Greco, Mario; Pinelli, Gianpaolo

2015-01-01

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 estimate UAV coordinates with errors bounded within ±12 m, thus making feasible the proposed SAR-based backup system. PMID:26225977

Feasibility of Using Synthetic Aperture Radar to Aid UAV Navigation.

PubMed

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.

UAV path planning using artificial potential field method updated by optimal control theory

NASA Astrophysics Data System (ADS)

Chen, Yong-bo; Luo, Guan-chen; Mei, Yue-song; Yu, Jian-qiao; Su, Xiao-long

2016-04-01

The unmanned aerial vehicle (UAV) path planning problem is an important assignment in the UAV mission planning. Based on the artificial potential field (APF) UAV path planning method, it is reconstructed into the constrained optimisation problem by introducing an additional control force. The constrained optimisation problem is translated into the unconstrained optimisation problem with the help of slack variables in this paper. The functional optimisation method is applied to reform this problem into an optimal control problem. The whole transformation process is deduced in detail, based on a discrete UAV dynamic model. Then, the path planning problem is solved with the help of the optimal control method. The path following process based on the six degrees of freedom simulation model of the quadrotor helicopters is introduced to verify the practicability of this method. Finally, the simulation results show that the improved method is more effective in planning path. In the planning space, the length of the calculated path is shorter and smoother than that using traditional APF method. In addition, the improved method can solve the dead point problem effectively.

Formation flight and collision avoidance for multiple UAVs based on modified tentacle algorithm in unstructured environments

PubMed Central

2017-01-01

This paper presents a method for formation flight and collision avoidance of multiple UAVs. Due to the shortcomings such as collision avoidance caused by UAV’s high-speed and unstructured environments, this paper proposes a modified tentacle algorithm to ensure the high performance of collision avoidance. Different from the conventional tentacle algorithm which uses inverse derivation, the modified tentacle algorithm rapidly matches the radius of each tentacle and the steering command, ensuring that the data calculation problem in the conventional tentacle algorithm is solved. Meanwhile, both the speed sets and tentacles in one speed set are reduced and reconstructed so as to be applied to multiple UAVs. Instead of path iterative optimization, the paper selects the best tentacle to obtain the UAV collision avoidance path quickly. The simulation results show that the method presented in the paper effectively enhances the performance of flight formation and collision avoidance for multiple high-speed UAVs in unstructured environments. PMID:28763498

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

USDA-ARS?s Scientific Manuscript database

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

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

USDA-ARS?s Scientific Manuscript database

Unmanned aerial vehicles (UAVs) hold significant promise for agriculture. Currently, UAVs are being employed for various reconnaissance purposes (“eyes in the sky”), but not as pest control delivery systems. Research in Wisconsin cranberries is taking UAVs in a new direction. The Steffan and Luck La...

Applications of UAV Photogrammetric Surveys to Natural Hazard Detection and Cultural Heritage Documentation

NASA Astrophysics Data System (ADS)

Trizzino, Rosamaria; Caprioli, Mauro; Mazzone, Francesco; Scarano, Mario

2017-04-01

Unmanned Aerial Vehicle (UAV) systems are increasingly seen as an attractive low-cost alternative or supplement to aerial and terrestrial photogrammetry due to their low cost, flexibility, availability and readiness for duty. In addition, UAVs can be operated in hazardous or temporarily inaccessible locations. The combination of photogrammetric aerial and terrestrial recording methods using a mini UAV (also known as "drone") opens a broad range of applications, such as surveillance and monitoring of the environment and infrastructural assets. In particular, these methods and techniques are of paramount interest for the documentation of cultural heritage sites and areas of natural importance, facing threats from natural deterioration and hazards. In order to verify the reliability of these technologies an UAV survey and a LIDAR survey have been carried out along about 1 km of coast in the Salento peninsula, near the towns of San Foca, Torre dell' Orso and SantAndrea ( Lecce, Southern Italy). This area is affected by serious environmental hazards due to the presence of dangerous rocky cliffs named "falesie". The UAV platform was equipped with a photogrammetric measurement system that allowed us to obtain a mobile mapping of the fractured fronts of dangerous rocky cliffs. UAV-images data have been processed using dedicated software (Agisoft Photoscan). The point clouds obtained from both the UAV and LIDAR surveys have been processed using Cloud Compare software, with the aim of testing the UAV results with respect to the LIDAR ones. The analysis were done using the C2C algorithm which provides good results in terms of Euclidian distances, highlighting differences between the 3D models obtained from both the survey techiques. The total error obtained was of centimeter-order that is a very satisfactory result. In the the 2nd study area, the opportunities of obtaining more detailed documentation of cultural goods throughout UAV survey have been investigated. The study

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

NASA Astrophysics Data System (ADS)

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 (uav-survey/"target="_blank">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.

Automated UAV-based mapping for airborne reconnaissance and video exploitation

NASA Astrophysics Data System (ADS)

Se, Stephen; Firoozfam, Pezhman; Goldstein, Norman; Wu, Linda; Dutkiewicz, Melanie; Pace, Paul; Naud, J. L. Pierre

2009-05-01

Airborne surveillance and reconnaissance are essential for successful military missions. Such capabilities are critical for force protection, situational awareness, mission planning, damage assessment and others. UAVs gather huge amount of video data but it is extremely labour-intensive for operators to analyse hours and hours of received data. At MDA, we have developed a suite of tools towards automated video exploitation including calibration, visualization, change detection and 3D reconstruction. The on-going work is to improve the robustness of these tools and automate the process as much as possible. Our calibration tool extracts and matches tie-points in the video frames incrementally to recover the camera calibration and poses, which are then refined by bundle adjustment. Our visualization tool stabilizes the video, expands its field-of-view and creates a geo-referenced mosaic from the video frames. It is important to identify anomalies in a scene, which may include detecting any improvised explosive devices (IED). However, it is tedious and difficult to compare video clips to look for differences manually. Our change detection tool allows the user to load two video clips taken from two passes at different times and flags any changes between them. 3D models are useful for situational awareness, as it is easier to understand the scene by visualizing it in 3D. Our 3D reconstruction tool creates calibrated photo-realistic 3D models from video clips taken from different viewpoints, using both semi-automated and automated approaches. The resulting 3D models also allow distance measurements and line-of- sight analysis.

X-Band Radar for Studies of Tropical Storms from High Altitude UAV Platform

NASA Technical Reports Server (NTRS)

Rodriquez, Shannon; Heymsfield, Gerald; Li, Lihua; Bradley, Damon

2007-01-01

modified from a marine radar transceiver. It is capable of measuring vertical reflectivity and velocity profile while being a lower-cost, smaller size, and lighter weight version of the NASA ER-2 Doppler Radar (EDOP), which has flown during many NASA field campaigns and has provided valuable scientific information on hurricanes and weather phenomena. Unfortunately, EDOP is too large and heavy for most UAV platforms, but the experience gained with this instrument provided us with the heritage to build a new low-cost, light-weight, smaller system that will be capable of flying on UAVs. The scanning subsystem uses a TWT transmitter and provides measurements of 3D reflectivity/wind fields in-clouds. Conical scanning of the radar beam at a 35 deg. incidence angle will also provide information of surface wind speed and direction derived from the surface return over a single 360 deg. sweep. URAD data system will be Linux based with the capability of autonomous operation. It will utilize cutting edge digital receiver and FPGA technologies to carry out the data acquisition and processing tasks. High speed navigation data from the aircraft will also be captured and saved along with radar data for 3D measurement field reconstruction and aircraft motion correction. There is a tremendous potential for UAVs to carry down-looking weather radars for measurements of reflectivity, horizontal and vertical winds from tropical storms. With operation from HUAV platforms, the dual beam X-band radar under development promises to provide greatly needed information for tropical storm research.

New distributed radar technology based on UAV or UGV application

NASA Astrophysics Data System (ADS)

Molchanov, Pavlo A.; Contarino, Vincent M.

2013-05-01

Regular micro and nano radars cannot provide reliable tracking of low altitude low profile aerial targets in urban and mountain areas because of reflection and re-reflections from buildings and terrain. They become visible and vulnerable to guided missiles if positioned on a tower or blimp. Doppler radar cannot distinguish moving cars and small low altitude aerial targets in an urban area. A new concept of pocket size distributed radar technology based on the application of UAV (Unmanned Air Vehicles), UGV (Unmanned Ground Vehicles) is proposed for tracking of low altitude low profile aerial targets at short and medium distances for protection of stadium, camp, military facility in urban or mountain areas.

Improved Seam-Line Searching Algorithm for UAV Image Mosaic with Optical Flow

PubMed Central

Zhang, Weilong; Guo, Bingxuan; Liao, Xuan; Li, Wenzhuo

2018-01-01

Ghosting and seams are two major challenges in creating unmanned aerial vehicle (UAV) image mosaic. In response to these problems, this paper proposes an improved method for UAV image seam-line searching. First, an image matching algorithm is used to extract and match the features of adjacent images, so that they can be transformed into the same coordinate system. Then, the gray scale difference, the gradient minimum, and the optical flow value of pixels in adjacent image overlapped area in a neighborhood are calculated, which can be applied to creating an energy function for seam-line searching. Based on that, an improved dynamic programming algorithm is proposed to search the optimal seam-lines to complete the UAV image mosaic. This algorithm adopts a more adaptive energy aggregation and traversal strategy, which can find a more ideal splicing path for adjacent UAV images and avoid the ground objects better. The experimental results show that the proposed method can effectively solve the problems of ghosting and seams in the panoramic UAV images. PMID:29659526

Improved Seam-Line Searching Algorithm for UAV Image Mosaic with Optical Flow.

PubMed

Zhang, Weilong; Guo, Bingxuan; Li, Ming; Liao, Xuan; Li, Wenzhuo

2018-04-16

Ghosting and seams are two major challenges in creating unmanned aerial vehicle (UAV) image mosaic. In response to these problems, this paper proposes an improved method for UAV image seam-line searching. First, an image matching algorithm is used to extract and match the features of adjacent images, so that they can be transformed into the same coordinate system. Then, the gray scale difference, the gradient minimum, and the optical flow value of pixels in adjacent image overlapped area in a neighborhood are calculated, which can be applied to creating an energy function for seam-line searching. Based on that, an improved dynamic programming algorithm is proposed to search the optimal seam-lines to complete the UAV image mosaic. This algorithm adopts a more adaptive energy aggregation and traversal strategy, which can find a more ideal splicing path for adjacent UAV images and avoid the ground objects better. The experimental results show that the proposed method can effectively solve the problems of ghosting and seams in the panoramic UAV images.

Semantic Segmentation and Unregistered Building Detection from Uav Images Using a Deconvolutional Network

NASA Astrophysics Data System (ADS)

Ham, S.; Oh, Y.; Choi, K.; Lee, I.

2018-05-01

Detecting unregistered buildings from aerial images is an important task for urban management such as inspection of illegal buildings in green belt or update of GIS database. Moreover, the data acquisition platform of photogrammetry is evolving from manned aircraft to UAVs (Unmanned Aerial Vehicles). However, it is very costly and time-consuming to detect unregistered buildings from UAV images since the interpretation of aerial images still relies on manual efforts. To overcome this problem, we propose a system which automatically detects unregistered buildings from UAV images based on deep learning methods. Specifically, we train a deconvolutional network with publicly opened geospatial data, semantically segment a given UAV image into a building probability map and compare the building map with existing GIS data. Through this procedure, we could detect unregistered buildings from UAV images automatically and efficiently. We expect that the proposed system can be applied for various urban management tasks such as monitoring illegal buildings or illegal land-use change.

Preliminary Study on Earthquake Surface Rupture Extraction from Uav Images

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Kestrel: force protection and Intelligence, Surveillance, and Reconnaissance (ISR) persistent surveillance on aerostats

NASA Astrophysics Data System (ADS)

Luber, David R.; Marion, John E.; Fields, David

2012-05-01

Logos Technologies has developed and fielded the Kestrel system, an aerostat-based, wide area persistent surveillance system dedicated to force protection and ISR mission execution operating over forward operating bases. Its development included novel imaging and stabilization capability for day/night operations on military aerostat systems. The Kestrel system's contribution is a substantial enhancement to aerostat-based, force protection systems which to date have relied on narrow field of view ball gimbal sensors to identify targets of interest. This inefficient mechanism to conduct wide area field of view surveillance is greatly enhanced by Kestrel's ability to maintain a constant motion imagery stare of the entire forward operating base (FOB) area. The Kestrel airborne sensor enables 360° coverage out to extended ranges which covers a city sized area at moderate resolution, while cueing a narrow field of view sensor to provide high resolution imagery of targets of interest. The ground station exploitation system enables operators to autonomously monitor multiple regions of interest in real time, and allows for backtracking through the recorded imagery, while continuing to monitor ongoing activity. Backtracking capability allows operators to detect threat networks, their CONOPS, and locations of interest. Kestrel's unique advancement has already been utilized successfully in OEF operations.

Autonomous Aerial Refueling Ground Test Demonstration—A Sensor-in-the-Loop, Non-Tracking Method

PubMed Central

Chen, Chao-I; Koseluk, Robert; Buchanan, Chase; Duerner, Andrew; Jeppesen, Brian; Laux, Hunter

2015-01-01

An essential capability for an unmanned aerial vehicle (UAV) to extend its airborne duration without increasing the size of the aircraft is called the autonomous aerial refueling (AAR). This paper proposes a sensor-in-the-loop, non-tracking method for probe-and-drogue style autonomous aerial refueling tasks by combining sensitivity adjustments of a 3D Flash LIDAR camera with computer vision based image-processing techniques. The method overcomes the inherit ambiguity issues when reconstructing 3D information from traditional 2D images by taking advantage of ready to use 3D point cloud data from the camera, followed by well-established computer vision techniques. These techniques include curve fitting algorithms and outlier removal with the random sample consensus (RANSAC) algorithm to reliably estimate the drogue center in 3D space, as well as to establish the relative position between the probe and the drogue. To demonstrate the feasibility of the proposed method on a real system, a ground navigation robot was designed and fabricated. Results presented in the paper show that using images acquired from a 3D Flash LIDAR camera as real time visual feedback, the ground robot is able to track a moving simulated drogue and continuously narrow the gap between the robot and the target autonomously. PMID:25970254

UAV Annual Report, FY 1996.

DTIC Science & Technology

1996-11-06

Tracor; Vector; Cl Fiberite; Hexcel; Honeywell Cannon; Tamam; IntegriNautics; Lockheed Martin; Carlyle Gp; Northrop Grumman (SAR); Hbroux; Hughes...Aerospace; Group; Teftec Inc. Northrop Grumman ; Williams Internations Developmental estimates Developmental estimates 09 31 UAV ANNUAL REPORT UAV Tier 11...Rosemount Aerospace; Northrop Grumman ; Williams International Developmental estimates 31 UAVANNUAL REPORT A U.S. Customs Service P-3 AEW and Predator

Holarchical Systems and Emotional Holons : Biologically-Inspired System Designs for Control of Autonomous Aerial Vehicles

NASA Technical Reports Server (NTRS)

Ippolito, Corey; Plice, Laura; Pisanich, Greg

2003-01-01

The BEES (Bio-inspired Engineering for Exploration Systems) for Mars project at NASA Ames Research Center has the goal of developing bio-inspired flight control strategies to enable aerial explorers for Mars scientific investigations. This paper presents a summary of our ongoing research into biologically inspired system designs for control of unmanned autonomous aerial vehicle communities for Mars exploration. First, we present cooperative design considerations for robotic explorers based on the holarchical nature of biological systems and communities. Second, an outline of an architecture for cognitive decision making and control of individual robotic explorers is presented, modeled after the emotional nervous system of cognitive biological systems. Keywords: Holarchy, Biologically Inspired, Emotional UAV Flight Control

Commercial UAV operations in civil airspace

NASA Astrophysics Data System (ADS)

Newcome, Laurence R.

2000-11-01

The Federal Aviation Administration is often portrayed as the major impediment to unmanned aerial vehicle expansion into civil government and commercial markets. This paper describes one company's record for successfully negotiating the FAA regulations and obtaining authorizations for several types of UAVs to fly commercial reconnaissance missions in civil airspace. The process and criteria for obtaining such authorizations are described. The mishap records of the Pioneer, Predator and Hunter UAVs are examined in regard to their impact on FAA rule making. The paper concludes with a discussion of the true impediments to UAV penetration of commercial markets to date.

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

PubMed

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

2014-01-01

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

A Multi-Disciplinary Approach to Remote Sensing through Low-Cost UAVs.

PubMed

Calvario, Gabriela; Sierra, Basilio; Alarcón, Teresa E; Hernandez, Carmen; Dalmau, Oscar

2017-06-16

The use of Unmanned Aerial Vehicles (UAVs) based on remote sensing has generated low cost monitoring, since the data can be acquired quickly and easily. This paper reports the experience related to agave crop analysis with a low cost UAV. The data were processed by traditional photogrammetric flow and data extraction techniques were applied to extract new layers and separate the agave plants from weeds and other elements of the environment. Our proposal combines elements of photogrammetry, computer vision, data mining, geomatics and computer science. This fusion leads to very interesting results in agave control. This paper aims to demonstrate the potential of UAV monitoring in agave crops and the importance of information processing with reliable data flow.

Vision-Based Precision Landings of a Tailsitter UAV

DTIC Science & Technology

2010-04-01

2.2: Schematic of the controller used in simulation. The block diagram shown in Figure 2.2 shows the simulation structure used to simulate the vision...the structure of the flight facility walls, any vibration applied to the structure would potentially change the pose of the cameras. Each camera’s pose...relative to the target in Chap- ter 4, a flat earth assumption was made. In several situations the approximation that the ground over which the UAV is

Trust Management in Swarm-Based Autonomic Computing Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maiden, Wendy M.; Haack, Jereme N.; Fink, Glenn A.

2009-07-07

Reputation-based trust management techniques can address issues such as insider threat as well as quality of service issues that may be malicious in nature. However, trust management techniques must be adapted to the unique needs of the architectures and problem domains to which they are applied. Certain characteristics of swarms such as their lightweight ephemeral nature and indirect communication make this adaptation especially challenging. In this paper we look at the trust issues and opportunities in mobile agent swarm-based autonomic systems and find that by monitoring the trustworthiness of the autonomic managers rather than the swarming sensors, the trust managementmore » problem becomes much more scalable and still serves to protect the swarms. We also analyze the applicability of trust management research as it has been applied to architectures with similar characteristics. Finally, we specify required characteristics for trust management mechanisms to be used to monitor the trustworthiness of the entities in a swarm-based autonomic computing system.« less

Actions, Observations, and Decision-Making: Biologically Inspired Strategies for Autonomous Aerial Vehicles

NASA Technical Reports Server (NTRS)

Pisanich, Greg; Ippolito, Corey; Plice, Laura; Young, Larry A.; Lau, Benton

2003-01-01

This paper details the development and demonstration of an autonomous aerial vehicle embodying search and find mission planning and execution srrategies inspired by foraging behaviors found in biology. It begins by describing key characteristics required by an aeria! explorer to support science and planetary exploration goals, and illustrates these through a hypothetical mission profile. It next outlines a conceptual bio- inspired search and find autonomy architecture that implements observations, decisions, and actions through an "ecology" of producer, consumer, and decomposer agents. Moving from concepts to development activities, it then presents the results of mission representative UAV aerial surveys at a Mars analog site. It next describes hardware and software enhancements made to a commercial small fixed-wing UAV system, which inc!nde a ncw dpvelopnent architecture that also provides hardware in the loop simulation capability. After presenting the results of simulated and actual flights of bioinspired flight algorithms, it concludes with a discussion of future development to include an expansion of system capabilities and field science support.

a Light-Weight Laser Scanner for Uav Applications

NASA Astrophysics Data System (ADS)

Tommaselli, A. M. G.; Torres, F. M.

2016-06-01

Unmanned Aerial Vehicles (UAV) have been recognized as a tool for geospatial data acquisition due to their flexibility and favourable cost benefit ratio. The practical use of laser scanning devices on-board UAVs is also developing with new experimental and commercial systems. This paper describes a light-weight laser scanning system composed of an IbeoLux scanner, an Inertial Navigation System Span-IGM-S1, from Novatel, a Raspberry PI portable computer, which records data from both systems and an octopter UAV. The performance of this light-weight system was assessed both for accuracy and with respect to point density, using Ground Control Points (GCP) as reference. Two flights were performed with the UAV octopter carrying the equipment. In the first trial, the flight height was 100 m with six strips over a parking area. The second trial was carried out over an urban park with some buildings and artificial targets serving as reference Ground Control Points. In this experiment a flight height of 70 m was chosen to improve target response. Accuracy was assessed based on control points the coordinates of which were measured in the field. Results showed that vertical accuracy with this prototype is around 30 cm, which is acceptable for forest applications but this accuracy can be improved using further refinements in direct georeferencing and in the system calibration.

A Stereo Dual-Channel Dynamic Programming Algorithm for UAV Image Stitching.

PubMed

Li, Ming; Chen, Ruizhi; Zhang, Weilong; Li, Deren; Liao, Xuan; Wang, Lei; Pan, Yuanjin; Zhang, Peng

2017-09-08

Dislocation is one of the major challenges in unmanned aerial vehicle (UAV) image stitching. In this paper, we propose a new algorithm for seamlessly stitching UAV images based on a dynamic programming approach. Our solution consists of two steps: Firstly, an image matching algorithm is used to correct the images so that they are in the same coordinate system. Secondly, a new dynamic programming algorithm is developed based on the concept of a stereo dual-channel energy accumulation. A new energy aggregation and traversal strategy is adopted in our solution, which can find a more optimal seam line for image stitching. Our algorithm overcomes the theoretical limitation of the classical Duplaquet algorithm. Experiments show that the algorithm can effectively solve the dislocation problem in UAV image stitching, especially for the cases in dense urban areas. Our solution is also direction-independent, which has better adaptability and robustness for stitching images.

Bioinspired polarization navigation sensor for autonomous munitions systems

NASA Astrophysics Data System (ADS)

Giakos, G. C.; Quang, T.; Farrahi, T.; Deshpande, A.; Narayan, C.; Shrestha, S.; Li, Y.; Agarwal, M.

2013-05-01

Small unmanned aerial vehicles UAVs (SUAVs), micro air vehicles (MAVs), Automated Target Recognition (ATR), and munitions guidance, require extreme operational agility and robustness which can be partially offset by efficient bioinspired imaging sensor designs capable to provide enhanced guidance, navigation and control capabilities (GNC). Bioinspired-based imaging technology can be proved useful either for long-distance surveillance of targets in a cluttered environment, or at close distances limited by space surroundings and obstructions. The purpose of this study is to explore the phenomenology of image formation by different insect eye architectures, which would directly benefit the areas of defense and security, on the following four distinct areas: a) fabrication of the bioinspired sensor b) optical architecture, c) topology, and d) artificial intelligence. The outcome of this study indicates that bioinspired imaging can impact the areas of defense and security significantly by dedicated designs fitting into different combat scenarios and applications.

A satellite based telemetry link for a UAV application

NASA Technical Reports Server (NTRS)

Bloise, Anthony

1995-01-01

The requirements for a satellite based communication facility to service the needs of the Geographical Information System (GIS) data collection community are addressed in this paper. GIS data is supplied in the form of video imagery at sub-television rates in one or more spectral bands / polarizations laced with a position correlated data stream. The limitations and vicissitudes of using a terrestrial based telecommunications link to collect GIS data are illustrated from actual mission scenarios. The expectations from a satellite based communications link by the geophysical data collection community concerning satellite architecture, operating bands, bandwidth, footprint agility, up link and down link hardware configurations on the UAV, the Mobile Control Vehicle and at the Central Command and Data Collection Facility comprise the principle issues discussed in the first section of this paper. The final section of the paper discusses satellite based communication links would have an increased volume and scope of services the GIS data collection community could make available to the GIS user community, and the price the data collection community could afford to pay for access to the communication satellite described in the paper.

Detection of flood effects in montane streams based on fusion of 2D and 3D information from UAV imagery

NASA Astrophysics Data System (ADS)

Langhammer, Jakub; Vacková, Tereza

2017-04-01

In the contribution, we are presenting a novel method, enabling objective detection and classification of the alluvial features resulting from flooding, based on the imagery, acquired by the unmanned aerial vehicles (UAVs, drones). We have proposed and tested a workflow, using two key data products of the UAV photogrammetry - the 2D orthoimage and 3D digital elevation model, together with derived information on surface texture for the consequent classification of erosional and depositional features resulting from the flood. The workflow combines the photogrammetric analysis of the UAV imagery, texture analysis of the DEM, and the supervised image classification. Application of the texture analysis and use of DEM data is aimed to enhance 2D information, resulting from the high-resolution orthoimage by adding the newly derived bands, which enhance potential for detection and classification of key types of fluvial features in the stream and the floodplain. The method was tested on the example of a snowmelt-driven flood in a montane stream in Sumava Mts., Czech Republic, Central Europe, that occurred in December 2015. Using the UAV platform DJI Inspire 1 equipped with the RGB camera there was acquired imagery covering a 1 km long stretch of a meandering creek with elevated fluvial dynamics. Agisoft Photoscan Pro was used to derive a point cloud and further the high-resolution seamless orthoimage and DEM, Orfeo toolkit and SAGA GIS tools were used for DEM analysis. From the UAV-based data inputs, a multi-band dataset was derived as a source for the consequent classification of fluvial landforms. The RGB channels of the derived orthoimage were completed by the selected texture feature layers and the information on 3D properties of the riverscape - the normalized DEM and terrain ruggedness. Haralick features, derived from the RGB channels, are used for extracting information on the surface texture, the terrain ruggedness index is used as a measure of local topographical

Using crowd sourcing to combat potentially illegal or dangerous UAV operations

NASA Astrophysics Data System (ADS)

Tapsall, Brooke T.

2016-10-01

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

Extended image differencing for change detection in UAV video mosaics

NASA Astrophysics Data System (ADS)

Saur, Günter; Krüger, Wolfgang; Schumann, Arne

2014-03-01

Change detection is one of the most important tasks when using unmanned aerial vehicles (UAV) for video reconnaissance and surveillance. We address changes of short time scale, i.e. the observations are taken in time distances from several minutes up to a few hours. Each observation is a short video sequence acquired by the UAV in near-nadir view and the relevant changes are, e.g., recently parked or moved vehicles. In this paper we extend our previous approach of image differencing for single video frames to video mosaics. A precise image-to-image registration combined with a robust matching approach is needed to stitch the video frames to a mosaic. Additionally, this matching algorithm is applied to mosaic pairs in order to align them to a common geometry. The resulting registered video mosaic pairs are the input of the change detection procedure based on extended image differencing. A change mask is generated by an adaptive threshold applied to a linear combination of difference images of intensity and gradient magnitude. The change detection algorithm has to distinguish between relevant and non-relevant changes. Examples for non-relevant changes are stereo disparity at 3D structures of the scene, changed size of shadows, and compression or transmission artifacts. The special effects of video mosaicking such as geometric distortions and artifacts at moving objects have to be considered, too. In our experiments we analyze the influence of these effects on the change detection results by considering several scenes. The results show that for video mosaics this task is more difficult than for single video frames. Therefore, we extended the image registration by estimating an elastic transformation using a thin plate spline approach. The results for mosaics are comparable to that of single video frames and are useful for interactive image exploitation due to a larger scene coverage.

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

NASA Astrophysics Data System (ADS)

Sotier, Bernadette; Adams, Marc; Lechner, Veronika

2015-04-01

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

Laboratory-based Salmonella surveillance in Fiji, 2004-2005.

PubMed

Dunn, John; Pryor, Jan; Saketa, Salanieta; Delai, Wasale; Buadromo, Eka; Kishore, Kamal; Naidu, Shakila; Greene, Sharon; Varma, Jay; Chiller, Tom

2005-09-01

Although foodborne diseases are an important public health problem worldwide, the burden of foodborne illness is not well described in most Pacific Island Countries and Territories. Laboratory-based surveillance programs can detect trends and outbreaks, estimate burden of illness, and allow subtyping of enteric pathogens (e.g. Salmonella serotyping), which is critical for linking illness to food vehicles and animal reservoirs. To enhance public health capacity in Fiji for foodborne disease surveillance, we developed the Salmonella Surveillance Project (SSP), a collaboration to pilot laboratory-based surveillance for Salmonella. A network of national and international partners was formed including epidemiologists, microbiologists, and environmental health personnel. Ministry of Health personnel were trained in foodborne disease surveillance and outbreak investigation. Three clinical microbiology laboratories from different parts of the country functioned as sentinel sites, reporting all laboratory-confirmed Salmonella infections using a standardized case report form. Non-Typhi Salmonella isolates were collected for serotyping. In 2004-2005, 86 non-Typhi Salmonella and 275 S. Typhi laboratory-confirmed infections were reported. Salmonella enterica serotype I 3,10: r:- and Salmonella enterica serotype Weltevreden were the most commonly isolated non-Typhi serotypes. In Fiji, the SSP utilized international partnerships to facilitate training, and to enhance laboratory capacity and surveillance for salmonellosis. Incorporating laboratory-based foodborne disease reporting into national disease surveillance will enable public health officials to describe the burden of foodborne illness, identify outbreaks, conduct analytic epidemiology studies, and improve food safety.

SAMURAI: Polar AUV-Based Autonomous Dexterous Sampling

NASA Astrophysics Data System (ADS)

Akin, D. L.; Roberts, B. J.; Smith, W.; Roderick, S.; Reves-Sohn, R.; Singh, H.

2006-12-01

While autonomous undersea vehicles are increasingly being used for surveying and mapping missions, as of yet there has been little concerted effort to create a system capable of performing physical sampling or other manipulation of the local environment. This type of activity has typically been performed under teleoperated control from ROVs, which provides high-bandwidth real-time human direction of the manipulation activities. Manipulation from an AUV will require a completely autonomous sampling system, which implies both advanced technologies such as machine vision and autonomous target designation, but also dexterous robot manipulators to perform the actual sampling without human intervention. As part of the NASA Astrobiology Science and Technology for Exploring the Planets (ASTEP) program, the University of Maryland Space Systems Laboratory has been adapting and extending robotics technologies developed for spacecraft assembly and maintenance to the problem of autonomous sampling of biologicals and soil samples around hydrothermal vents. The Sub-polar ice Advanced Manipulator for Universal Sampling and Autonomous Intervention (SAMURAI) system is comprised of a 6000-meter capable six-degree-of-freedom dexterous manipulator, along with an autonomous vision system, multi-level control system, and sampling end effectors and storage mechanisms to allow collection of samples from vent fields. SAMURAI will be integrated onto the Woods Hole Oceanographic Institute (WHOI) Jaguar AUV, and used in Arctic during the fall of 2007 for autonomous vent field sampling on the Gakkel Ridge. Under the current operations concept, the JAGUAR and PUMA AUVs will survey the water column and localize on hydrothermal vents. Early mapping missions will create photomosaics of the vents and local surroundings, allowing scientists on the mission to designate desirable sampling targets. Based on physical characteristics such as size, shape, and coloration, the targets will be loaded into the

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Formation Flight of Multiple UAVs via Onboard Sensor Information Sharing.

PubMed

Park, Chulwoo; Cho, Namhoon; Lee, Kyunghyun; Kim, Youdan

2015-07-17

To monitor large areas or simultaneously measure multiple points, multiple unmanned aerial vehicles (UAVs) must be flown in formation. To perform such flights, sensor information generated by each UAV should be shared via communications. Although a variety of studies have focused on the algorithms for formation flight, these studies have mainly demonstrated the performance of formation flight using numerical simulations or ground robots, which do not reflect the dynamic characteristics of UAVs. In this study, an onboard sensor information sharing system and formation flight algorithms for multiple UAVs are proposed. The communication delays of radiofrequency (RF) telemetry are analyzed to enable the implementation of the onboard sensor information sharing system. Using the sensor information sharing, the formation guidance law for multiple UAVs, which includes both a circular and close formation, is designed. The hardware system, which includes avionics and an airframe, is constructed for the proposed multi-UAV platform. A numerical simulation is performed to demonstrate the performance of the formation flight guidance and control system for multiple UAVs. Finally, a flight test is conducted to verify the proposed algorithm for the multi-UAV system.

Formation Flight of Multiple UAVs via Onboard Sensor Information Sharing

PubMed Central

Park, Chulwoo; Cho, Namhoon; Lee, Kyunghyun; Kim, Youdan

2015-01-01

To monitor large areas or simultaneously measure multiple points, multiple unmanned aerial vehicles (UAVs) must be flown in formation. To perform such flights, sensor information generated by each UAV should be shared via communications. Although a variety of studies have focused on the algorithms for formation flight, these studies have mainly demonstrated the performance of formation flight using numerical simulations or ground robots, which do not reflect the dynamic characteristics of UAVs. In this study, an onboard sensor information sharing system and formation flight algorithms for multiple UAVs are proposed. The communication delays of radiofrequency (RF) telemetry are analyzed to enable the implementation of the onboard sensor information sharing system. Using the sensor information sharing, the formation guidance law for multiple UAVs, which includes both a circular and close formation, is designed. The hardware system, which includes avionics and an airframe, is constructed for the proposed multi-UAV platform. A numerical simulation is performed to demonstrate the performance of the formation flight guidance and control system for multiple UAVs. Finally, a flight test is conducted to verify the proposed algorithm for the multi-UAV system. PMID:26193281

A Multi-Disciplinary Approach to Remote Sensing through Low-Cost UAVs

PubMed Central

Calvario, Gabriela; Sierra, Basilio; Alarcón, Teresa E.; Hernandez, Carmen; Dalmau, Oscar

2017-01-01

The use of Unmanned Aerial Vehicles (UAVs) based on remote sensing has generated low cost monitoring, since the data can be acquired quickly and easily. This paper reports the experience related to agave crop analysis with a low cost UAV. The data were processed by traditional photogrammetric flow and data extraction techniques were applied to extract new layers and separate the agave plants from weeds and other elements of the environment. Our proposal combines elements of photogrammetry, computer vision, data mining, geomatics and computer science. This fusion leads to very interesting results in agave control. This paper aims to demonstrate the potential of UAV monitoring in agave crops and the importance of information processing with reliable data flow. PMID:28621740

Efficient structure from motion for oblique UAV images based on maximal spanning tree expansion

NASA Astrophysics Data System (ADS)

Jiang, San; Jiang, Wanshou

2017-10-01

The primary contribution of this paper is an efficient Structure from Motion (SfM) solution for oblique unmanned aerial vehicle (UAV) images. First, an algorithm, considering spatial relationship constraints between image footprints, is designed for match pair selection with the assistance of UAV flight control data and oblique camera mounting angles. Second, a topological connection network (TCN), represented by an undirected weighted graph, is constructed from initial match pairs, which encodes the overlap areas and intersection angles into edge weights. Then, an algorithm, termed MST-Expansion, is proposed to extract the match graph from the TCN, where the TCN is first simplified by a maximum spanning tree (MST). By further analysis of the local structure in the MST, expansion operations are performed on the vertices of the MST for match graph enhancement, which is achieved by introducing critical connections in the expansion directions. Finally, guided by the match graph, an efficient SfM is proposed. Under extensive analysis and comparison, its performance is verified by using three oblique UAV datasets captured with different multi-camera systems. Experimental results demonstrate that the efficiency of image matching is improved, with speedup ratios ranging from 19 to 35, and competitive orientation accuracy is achieved from both relative bundle adjustment (BA) without GCPs (Ground Control Points) and absolute BA with GCPs. At the same time, images in the three datasets are successfully oriented. For the orientation of oblique UAV images, the proposed method can be a more efficient solution.

Slic Superpixels for Object Delineation from Uav Data

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

Informal settlement classification using point-cloud and image-based features from UAV data

NASA Astrophysics Data System (ADS)

Gevaert, C. M.; Persello, C.; Sliuzas, R.; Vosselman, G.

2017-03-01

Unmanned Aerial Vehicles (UAVs) are capable of providing very high resolution and up-to-date information to support informal settlement upgrading projects. In order to provide accurate basemaps, urban scene understanding through the identification and classification of buildings and terrain is imperative. However, common characteristics of informal settlements such as small, irregular buildings with heterogeneous roof material and large presence of clutter challenge state-of-the-art algorithms. Furthermore, it is of interest to analyse which fundamental attributes are suitable for describing these objects in different geographic locations. This work investigates how 2D radiometric and textural features, 2.5D topographic features, and 3D geometric features obtained from UAV imagery can be integrated to obtain a high classification accuracy in challenging classification problems for the analysis of informal settlements. UAV datasets from informal settlements in two different countries are compared in order to identify salient features for specific objects in heterogeneous urban environments. Findings show that the integration of 2D and 3D features leads to an overall accuracy of 91.6% and 95.2% respectively for informal settlements in Kigali, Rwanda and Maldonado, Uruguay.

A Stereo Dual-Channel Dynamic Programming Algorithm for UAV Image Stitching

PubMed Central

Chen, Ruizhi; Zhang, Weilong; Li, Deren; Liao, Xuan; Zhang, Peng

2017-01-01

Dislocation is one of the major challenges in unmanned aerial vehicle (UAV) image stitching. In this paper, we propose a new algorithm for seamlessly stitching UAV images based on a dynamic programming approach. Our solution consists of two steps: Firstly, an image matching algorithm is used to correct the images so that they are in the same coordinate system. Secondly, a new dynamic programming algorithm is developed based on the concept of a stereo dual-channel energy accumulation. A new energy aggregation and traversal strategy is adopted in our solution, which can find a more optimal seam line for image stitching. Our algorithm overcomes the theoretical limitation of the classical Duplaquet algorithm. Experiments show that the algorithm can effectively solve the dislocation problem in UAV image stitching, especially for the cases in dense urban areas. Our solution is also direction-independent, which has better adaptability and robustness for stitching images. PMID:28885547

Earth Observations and the Role of UAVs: A Capabilities Assessment

NASA Technical Reports Server (NTRS)

Cox, Timothy H.

2006-01-01

This three-volume document, based on the draft document located on the website given on page 6, presents the findings of a NASA-led capabilities assessment of Uninhabited Aerial Vehicles (UAVs) for civil (defined as non-DoD) use in Earth observations. Volume 1 is the report that presents the overall assessment and summarizes the data. The second volume contains the appendices and references to address the technologies and capabilities required for viable UAV missions. The third volume is the living portion of this effort and contains the outputs from each of the Technology Working Groups (TWGs) along with the reviews conducted by the Universities Space Research Association (USRA). The focus of this report, intended to complement the Office of the Secretary of Defense UAV Roadmap, is four-fold: 1) To determine and document desired future Earth observation missions for all UAVs based on user-defined needs; 2) To determine and document the technologies necessary to support those missions; 3) To discuss the present state of the art platform capabilities and required technologies, including identifying those in progress, those planned, and those for which no current plans exist; 4) Provide the foundations for development of a comprehensive civil UAV roadmap. It is expected that the content of this report will be updated periodically and used to assess the feasibility of future missions. In addition, this report will provide the foundation to help influence funding decisions to develop those technologies that are considered enabling or necessary but are not contained within approved funding plans. This document is written such that each section will be supported by an Appendix that will give the reader a more detailed discussion of that section's topical materials.