Obstacle Avoidance for Unmanned Aerial Vehicles

This work is framed within the PITVANT project and aims to contribute to the development of obstacle avoidance techniques for unmanned aerial vehicles (UAVs). The paper describes the design, implementation and experimental evaluation of a potential field obstacle avoidance algorithm based on the fluid mechanics panel methods. Obstacles and the UAV goal position are modeled by harmonic functions thus avoiding the presence of local minima. Adaptations are made to apply the method to the automatic control of a fixed wing aircraft, relying only on a local map of the environment that is updated with information from sensors onboard the aircraft. Hardware-In-Loop simulations show the good performance of the proposed algorithm in the envisioned mission scenarios for the PITVANT vehicles.     

UAV中图像处理系统的研究

对UAV中的图像处理系统进行了探讨,给出了一个切实可行的图像处理系统,包括系统结构、硬件组成、软件设计等。其中,软件设计利用了Intel公司的开放源代码图像处理工具包OpenCV,并且在目标检测上取得了较好的效果。     

Formation control of VTOL Unmanned Aerial Vehicles with communication delays

The formation control problem of a team of Vertical Take-Off and Landing (VTOL) Unmanned Aerial Vehicles (UAVs) with communication delays is addressed. Based on the extraction algorithm presented in Abdessameud and Tayebi (2010a), we propose a new design methodology that simplifies the design of formation control laws with delayed communication for this class of under-actuated systems. Three control schemes are presented that provide delay-dependent and delay-independent results with constant and time-varying communication delays. The stability of the overall closed loop system in each scheme is established using Lyapunov–Krasovskii functionals. The proposed design methodology achieves global results in terms of the position and removes the requirement of the linear-velocity measurements. Simulation results are provided to show the effectiveness of the proposed control schemes.     

A Flocking-Based on Demand Routing Protocol for Unmanned Aerial Vehicles

研究人员的某社区显示出到自治雄蜂或 UAV (无人的天线车辆) 的兴趣与无线通讯网络的来临增加了。这些网络允许 UAV 以一种特定的方式更高效地合作以便在特定的环境完成特定的任务。到那么,当保持经由收音机连接在它的组与另外的节点连接了时,每只雄蜂独立地遨游。这个连接能故意被维持一会儿抑制雄蜂的活动性。这将对涉及在来源和一个目的地之间的给定的传播的一条给定的路径的雄蜂合适。这限制能在传播过程的结束被移开,每只担心的雄蜂的活动性从其它变得再独立。在这个工作,我们建议为 UAV 的一个基于成群的路由协议叫了 BR-AODV。协议为当数据正在被播送时,维持的连接和线路为雷纳兹机制的按需的线路计算,和 Boids 利用一个众所周知的特定的路由协议。而且,自动扎根的基础车站发现机制为为即时应用程序的上下文需要的一个积极雄蜂和地面网络协会被介绍了。BR-AODV 的表演被评估,与古典 AODV 路由的相比,协议和结果证明 BR-AODV 以延期,产量和包损失超过 AODV。     

四旋翼无人机自适应导航控制

研究四旋翼(Quadrotor)无人机导航控制问题。针对传统的四旋翼无人机导航控制方法的目标定位误差和实时性差问题,提出了基于CLOS技术的导航控制方法。采用CLOS技术所开发的导航控制系统使得四旋翼无人机能够在移动停机坪完成自主导航和着陆的任务,并详细研究了导航控制系统的设计和仿真。仿真结果显示了所设计的导航控制系统的性能和有效性,可应用于四旋翼无人机的实时导航。     

Temporal Range Registration for Unmanned Ground and Aerial Vehicles

An iterative temporal registration algorithm is presented in this article for registering 3D range images obtained from unmanned ground and aerial vehicles traversing unstructured environments. We are primarily motivated by the development of 3D registration algorithms to overcome both the unavailability and unreliability of Global Positioning System (GPS) within required accuracy bounds for Unmanned Ground Vehicle (UGV) navigation. After suitable modifications to the well-known Iterative Closest Point (ICP) algorithm, the modified algorithm is shown to be robust to outliers and false matches during the registration of successive range images obtained from a scanning LAser Detection And Ranging (LADAR) rangefinder on the UGV. Towards registering LADAR images from the UGV with those from an Unmanned Aerial Vehicle (UAV) that flies over the terrain being traversed, we then propose a hybrid registration approach. In this approach to air to ground registration to estimate and update the position of the UGV, we register range data from two LADARs by combining a feature-based method with the aforementioned modified ICP algorithm. Registration of range data guarantees an estimate of the vehicle's position even when only one of the vehicles has GPS information. Temporal range registration enables position information to be continually maintained even when both vehicles can no longer maintain GPS contact. We present results of the registration algorithm in rugged terrain and urban environments using real field data acquired from two different LADARs on the UGV. ★Commercial equipment and materials are identified in this article in order to adequately specify certain procedures. Such identification does not imply recommendation or endorsement by the National Institute of Standards and Technology, nor does it imply that the materials or equipment identified are necessarily the best available for the purpose.     

基于虚拟仪器的无人机舵面负载模拟器

设计与实现了一种基于虚拟仪器的无人机舵面负载模拟器.针对无人机舵面负截模拟器的测试需求,给出了基于虚拟仪器的无人机舵面负载模拟器的基本功能、硬件配置、试验平台搭建、软件设计和系统测试结果.系统的测试结果很好地验证了系统设计的有效性.     

A terrain-following control approach for a VTOL Unmanned Aerial Vehicle using average optical flow

This paper presents a nonlinear controller for terrain following of a vertical take-off and landing vehicle (VTOL). The VTOL vehicle is assumed to be a rigid body, equipped with a minimum sensor suite (camera, IMU and barometric altimeter) maneuvering over a textured rough terrain made of a concatenation of planar surfaces. Assuming that the forward velocity is separately regulated to a desired value, the proposed control approach ensures terrain following and guarantees that the vehicle does not collide with the ground during the task. The proposed control acquires an optical flow from multiple spatially separate observation points, typically obtained via multiple cameras or non collinear directions in a unique camera. The proposed control algorithm has been tested extensively in simulation and then implemented on a quadrotor UAV to demonstrate the performance of the closed-loop system.     

基于PH曲线的无人机路径规划算法

研究了无人机可飞行路径规划问题,传统路径规划算法不能生成满足无人机运动学约束的可飞行路径.为解决上述问题,提出了将曲率连续的Pythagorean Hodograph (PH)曲线(又称勾股速端曲线)直接用于无人机路径规划的方法,利用PH曲线曲率连续、曲线平滑以及有理特性,在已知威胁的环境中可直接得到满足最大曲率约束且曲率连续的无人机可飞行路径.采用遗传模拟退火算法搜索避开环境中威胁体,并满足约束条件的最优PH路径,使仿真过程结合遗传算法和模拟退火算法的优点,取长补短,提高搜索效率,加强全局搜索能力.仿真结果表明,遗传模拟退火算法能在较少的进化代数下得到最优路径解,且所得的满足约束条件的PH路径曲率连续,为无人机飞行控制提供了依据.     

Autonomous Swarm of Low-Cost Commercial Unmanned Aerial Vehicles for Surveillance

Programming and Computer Software -     

Energy Management in Swarm of Unmanned Aerial Vehicles

Automated maintenance has become a necessity for Unmanned Aerial Vehicle (UAV) systems to function in remote environments for an extended period of time with a higher number of vehicles. Once removed from the energy management loop, the human operator is free to concentrate on higher level task management and data analysis. This paper firstly describes the design, test and construction of an autonomous Ground Recharge Stations (GRS) for battery-powered quadrotor helicopter. In order to incorporate the charging of the quadrotors in the overall swarm behaviour, the focus of the research presented here has been to reduce the charging phase of a single vehicle by developing safer electrical contacts and using a balancer in the charging process. The amount of extra current available from the new design easily pushed the flying-time/charging-time ratio of the quadrotors over 1. The paper then describes a novel approach for the integration of this technology into an energy efficient multi-agent system. The development of a prioritisation function and queuing protocols between the UAVs and GRSs demonstrate an optimised solution to the assignment problem dependent on the mission profile. Numerical experiments show that the system’s energy management remains efficient regardless of number and position of the platforms, or nature of the environment.     

Conflict Detection and Resolution Method for Cooperating Unmanned Aerial Vehicles

This paper presents a Conflict Detection and Resolution (CDR) method for cooperating Unmanned Aerial Vehicles (UAVs) sharing airspace. The proposed method detects conflicts using an algorithm based on axis-aligned minimum bounding box and solves the detected conflicts cooperatively using a genetic algorithm that modifies the trajectories of the UAVs with an overall minimum cost. The method changes the initial flight plan of each UAV by adding intermediate waypoints that define the solution flight plan while maintaining their velocities. The method has been validated with many simulations and experimental results with multiple aerial vehicles platforms based on quadrotors in a common airspace. The experiments have been carried out in the multi-UAV aerial testbed of the Center for Advanced Aerospace Technologies (CATEC).     

A Multiagent Swarming System for Distributed Automatic Target Recognition Using Unmanned Aerial Vehicles

Over the past few years, automatic target recognition (ATR) has emerged as an essential image analysis tool to identify objects from temporally and spatially disjoint possibly noisy image data. For many current applications, ATR is performed by unmanned aerial vehicles (UAVs) that fly within a reconnaissance area to collect image data through sensors and upload the data to a central ground control station for analyzing and identifying potential targets. The centralized approach to ATR introduces several problems, including scalability with the number of UAVs, network delays in communicating with the central location, and the susceptibility of the system to malicious attacks on the central location. These challenges can be addressed by using a distributed system for performing ATR. In this paper, we describe a multiagent-based prototype system that uses swarming techniques inspired from insect colonies to perform ATR using UAVs in a distributed manner within simulated scenarios. We assume that UAVs are constrained in the resources available onboard and in their capabilities for performing ATR due to payload limitations. Our focus in this paper is on the coordination aspects between UAVs to efficiently decide how they are to act by using a swarming mechanism. We describe algorithms for the different operations performed by the UAVs in the system and for different swarming strategies, which are embedded within software agents located on the UAVs. We provide empirical simulations of our system within a simulated area of interest to determine its behavior in different scenarios with varying operational constraints. Our experimental results indicate that swarming strategies for distributed ATR perform favorably compared with centralized ATR strategies.     

A Visual Global Positioning System for Unmanned Aerial Vehicles Used in Photogrammetric Applications

The combination of photogrammetric aerial and terrestrial recording methods can provide new opportunities for photogrammetric applications. A UAV (Unmanned Aerial Vehicle), in our case a helicopter system, can cover both the aerial and quasi-terrestrial image acquisition methods. A UAV can be equipped with an on-board high resolution camera and a priori knowledge of the operating area where to perform photogrammetric tasks. In this general scenario our paper proposes vision-based techniques for localizing a UAV. Only natural landmarks provided by a feature tracking algorithm will be considered, without the help of visual beacons or landmarks with known positions. The novel idea is to perform global localization, position tracking and localization failure recovery (kidnapping) based only on visual matching between current view and available georeferenced satellite images. The matching is based on SIFT features and the system estimates the position of the UAV and its altitude on the base of the reference image. The vision system replaces the GPS signal combining position information from visual odometry and georeferenced imagery. Georeferenced satellite or aerial images must be available on-board beforehand or downloaded during the flight. The growing availability of high resolution satellite images (e.g., provided by Google Earth or other local information sources) makes this topic very interesting and timely. Experiments with both synthetic (i.e., taken from satellites or datasets and pre elaborated) and real world images have been performed to test the accuracy and the robustness of our method. Results show sufficient performance if compared with common GPS systems and give a good performance also in the altitude estimation, even if in this last case there are only preliminary results.     

Three-dimensional Route Planning for Unmanned Aerial Vehicles in a Risk Environment

This paper introduces a new approach for three-dimensional flight path optimization for unmanned aerial vehicles. It considers the performance of the air vehicle as well as mission specific requirements including the avoidance of no-fly areas, risk reduction in threat environments by terrain following flight or terrain masking low-level flight, and other regulations such as fixed release and approach vectors at the start and destination locations. The focus of the approach is on a proper discretization of the airspace by a network which allows the application of standard algorithms of combinatorial optimization. In contrast to conventional discretizations by grids or grid-like graphs, our network is non-regular since created by some random process. Moreover, each path in the network corresponds to a twice continuously differentiable trajectory which obeys the kinematic restrictions of the air vehicle and which is feasible with respect to the operational requirements of the mission. With suitable costs defined on the edges of the network, a minimum-cost path calculation allows to identify a trajectory of shortest length, shortest flight time, minimum flight height, or minimum visibility from the ground. The latter objectives aim to minimize the probability of being detected by hostile forces, hence increasing the survivability of the air vehicle.     

Nonlinear Adaptive Close Formation Control of Unmanned Aerial Vehicles

This paper treats the question of formationflight control of multiple unmanned aerial vehicles (UAVs). Inclose formation the wing UAV motion is affected by the vortexof the adjacent lead aircraft. The forces produced by these vorticesare complex functions of the relative position coordinates ofthe UAVs. In this paper, these forces are treated as unknownfunctions. For simplicity, it is assumed that the UAVs have autopilotsfor heading-, altitude-, and Mach-hold in the inner loops. Anadaptive control law is derived for the position control of thewing aircraft based on a backstepping design technique. In theclosed-loop system, commanded separation trajectories are asymptoticallytracked by each wing aircraft while the lead UAV is maneuvering.It is seen that an overparametrization in the design is essentialfor the decentralization of the control system. These resultsare applied to formation flight control of two UAVs and simulationresults are obtained. These results show that the wing UAV followsprecisely the reference separation trajectories in spite of theuncertainties in the aerodynamic coefficients, while the leadaircraft maneuvers.     

Online Two-Dimensional Route Planning for a Group of Unmanned Aerial Vehicles

Journal of Computer and Systems Sciences International - This paper suggests a novel approach to online two-dimensional route planning for a coordinated flight of a group of unmanned aerial...     

基于粒子群优化算法的无人机航迹规划

无人机作为侦察和作战的重要手段,重要的是保证侦察目标的准确性,对任务/航迹规划系统是无人机实现自主飞行和自主攻击的关键技术。在给出无人机航迹规划问题描述的基础上,提出一种基于粒子群优化算法的无人机航迹规划方法,利用粒子群优化算法,将约束条件和搜索算法相结合,从而有效减小搜索空间,得到一条全局最优路径并进行仿真。仿真结果表明,规划方法能够快速有效地完成规划任务,获得满意的航迹,满足无人机作战要求,具有重要的现实意义。     

Optimization-Based Safety Analysis of Obstacle Avoidance Systems for Unmanned Aerial Vehicles

The integration of Unmanned Aerial Vehicles (UAVs) in airspace requires new methods to certify collision avoidance systems. This paper presents a safety clearance process for obstacle avoidance systems, where worst case analysis is performed using simulation based optimization in the presence of all possible parameter variations. The clearance criterion for the UAV obstacle avoidance system is defined as the minimum distance from the aircraft to the obstacle during the collision avoidance maneuver. Local and global optimization based verification processes are developed to automatically search the worst combinations of the parameters and the worst-case distance between the UAV and an obstacle under all possible variations and uncertainties. Based on a 6 Degree of Freedom (6DoF) kinematic and dynamic model of a UAV, the path planning and collision avoidance algorithms are developed in 3D space. The artificial potential field method is chosen as a path planning and obstacle avoidance candidate technique for verification study as it is a simple and widely used method. Different optimization algorithms are applied and compared in terms of the reliability and efficiency.