General fight rule-based trajectory planning for pairwise collision avoidance in a known environment

This paper presents a general flight rule-based autonomous trajectory planning scheme for two aerial vehicles to avoid obstacles and collisions in known environments in low-altitude airspace for general aviation. Flight rules in low-altitude airspace are first introduced based on the general flight rules in US, UK and China, and then the suitable flight rules are embedded into the trajectory planning algorithm. It is supposed that the flight parameters, such as positions and velocities, are all available to the aerial vehicles involved in the possible conflict. Then the trajectory of each aerial vehicle is calculated by optimizing an objective function, such as distance and fuel consumption, with the constraints corresponding to the airspace traffic rules. The optimization problem is solved by receding horizon control (RHC) based mixed integer linear programming (MILP). Compared with other collision avoidance algorithms, the proposed algorithm can be adapted to plan the autonomous trajectory to avoid pairwise collision and obstacles as proposed general flight rules. Simulations show the feasibility of the proposed scheme.     

多运动目标的多无人机协同搜索追踪策略

针对多无人机协同搜索追踪区域内多运动目标问题,考虑无人机的传感器与避撞等约束和目标随机运动等特征,提出了以垂线搜索为基础的多无人机协同搜索追踪策略.策略包含任务分配和航迹规划两部分.在任务分配部分,设计了航道均分垂线搜索算法,将搜索资源在区域内均匀分配,提高协同搜索效能.在航迹规划部分,设计了改进的人工势场算法,避免发...     

Decentralized cooperative control of heterogeneous vehicle groups

We coordinate in discrete time the interaction of two heterogeneous groups of mobile agents: a group of ground vehicles (ugvs) and a group of aerial vehicles (uavs). The ground agents interact with each other through time-invariant, nearest-neighbour rules. They synchronize their velocities through a specific communication protocol, and maintain cohesion and separation behaviour by means of interagent potential forces. Ground vehicles estimate their formation’s centroid using only locally available delayed information. That same information is transmitted to the aerial group, which orbits above the ground formation’s centroid, while avoiding midair collisions. Stability of the ground group motion is established in a Lyapunov framework. A Lyapunov analysis is also used to ensure that uavs track the ground group’s centroid.     

Continuous Airborne Communication Relay Approach Using Unmanned Aerial Vehicles

As a result of unmanned aerial vehicles being widely used in different areas, studies about increasing the autonomous capabilities of unmanned aerial vehicles are gaining momentum. Today, unmanned aerial vehicle platforms are especially used in reconnaissance, surveillance and communications areas. In this study, in order to achieve continuous long-range communication relay infrastructure, artificial potential field based path planning of Unmanned Aerial Vehicles is discussed. A novel dynamic approach to relay-chain concept is proposed to maintain the communication between vehicles. Besides dynamically keeping vehicles in range and appropriate position to maintain communication relay, artificial potential field based path planning also provides collision avoidance system. The performance of the proposed system is measured by applying a simulation under the Matlab Simulink and Network Simulator environment. Artificial potential field based flight patterns are generated in Matlab, and performance of the communication between vehicles is measured in Network Simulation environment. Finally the simulation results show that an airborne communication relay can be established autonomously by using artificial potential filed based autonomous path planning approach. Continues state communication is provided by obtaining a resistant communication relay which depends on artificial potential field based positioning algorithm.     

A 3D Collision Avoidance Strategy for UAVs in a Non-Cooperative Environment

This paper presents a feasible 3D collision avoidance approach for fixed-wing unmanned aerial vehicles (UAVs). The proposed strategy aims to achieve the desired relative bearing in the horizontal plane and relative elevation in the vertical plane so that the host aircraft is able to avoid collision with the intruder aircraft in 3D. The host aircraft will follow a desired trajectory in the collision avoidance course and resume the pre-arranged trajectory after collision is avoided. The approaching stopping condition is determined for the host aircraft to trigger an evasion maneuver to avoid collision in terms of measured heading. A switching controller is designed to achieve the spatial collision avoidance strategy. Simulation results demonstrate that the proposed approach can effectively avoid spatial collision, making it suitable for integration into flight control systems of UAVs.     

Vision‐aided Guidance and Navigation for Close Formation Flight

Close formation flight can extend an unmanned aerial vehicle's (UAV) range and endurance by utilizing lift from a wingman's wake vortices and by autonomous midair refueling or recharging. The prohibitive challenge in each of these applications is the highly accurate and reliable relative positioning that is required to station‐keep in the wingman's wake and to dock, amid external disturbances. Global navigation satellite systems are well‐suited to reliable absolute positioning, but they fall short for accurate relative positioning. This work proposes a relative positioning solution for UAV rendezvous and close formation flight that has been verified in multiple flight tests. A nonlinear estimation framework uses precise air‐to‐air measurements to correct onboard sensor measurements and produce an accurate relative state estimate that is resilient to intermittent relative measurement outages and degrades gracefully during extended outages. A guidance strategy compensates for wingman turn dynamics, acts explicitly on the estimated relative state, and is applicable to both rendezvous and formation flight. Ground testing showed a relative position estimate accuracy that is 2% of the separation distance, with successful detection and correspondence at up to 36 m. Autonomous close formation flight tests verified the relative positioning solution over extended periods, as close as two wingspans, in winds that were 30%–40% of the cruise airspeed, and at altitudes as low as 15 m. Root‐mean‐square relative position errors were 1.2 m horizontally and 0.44 m vertically during flights at the closest separation.     

A Multi-Point Distance-Bounding Protocol for Securing Automatic Dependent Surveillance-Broadcast in Unmanned Aerial Vehicle Applications

The Automatic Dependent Surveillance-Broadcast (ADS-B) protocol is being adopted for use in unmanned aerial vehicles (UAVs) as the primary source of information for emerging multi-UAV collision avoidance algorithms. The lack of security features in ADS-B leaves any processes dependent upon the information vulnerable to a variety of threats from compromised and dishonest UAVs. This could result in substantial losses or damage to properties. This research proposes a new distance-bounding scheme for verifying the distance and flight trajectory in the ADS-B broadcast data from surrounding UAVs. The proposed scheme enables UAVs or ground stations to identify fraudulent UAVs and avoid collisions. The scheme was implemented and tested in the ArduPilot SITL (Software In The Loop) simulator to verify its ability to detect fraudulent UAVs. The experiments showed that the scheme achieved the desired accuracy in both flight trajectory measurement and attack detection.

     

Unmanned Aerial Vehicles Formation Using Learning Based Model Predictive Control

This paper presents a solution for the formation flight problem for multiple unmanned aerial vehicles (UAVs) cooperating to execute a required mission. Learning Based Model Predictive Control (LBMPC) is implemented on the team of UAVs in order to accomplish the required formation. All flight simulations respect Reynold's rules of flocking to avoid UAV collisions with nearby flockmates, match the team members velocity and stay close to each other during the formation. The main contribution of this paper lies in the application of LBMPC to solve the problem of formation for an autonomous team of UAVs. The proposed solution is theoretically, by the application of analysis to the problem, demonstrated to be stable. Moreover, simulations support the findings of the paper. The main contributions of this paper are the proposed LBMPC formulation for formation of vehicles with uncertainty in their models, and the theoretical analysis of the solution.     

Collision avoidance command governor for multi‐vehicle unmanned systems

In this paper, we consider the problem of coordinating a collection of autonomous unmanned vehicles while guaranteeing collision avoidance. Each vehicle is regulated by a local controller that ensures stability and provides desired path tracking performance in the absence of constraints. The fulfillment of coordination tasks (e.g., collision avoidance) and local constraints (e.g., input saturation constraints) is achieved through a command governor (CG) strategy that, whenever necessary, modifies the nominal paths of the vehicles. First, a centralized CG approach is proposed and fully analyzed. Then, a more interesting distributed implementation requiring low communication rates is discussed. Both approaches make use of a receding horizon strategy and require the on‐line solution of mixed‐integer optimization programs. Finally, an example is given for illustration purposes. Copyright © 2013 John Wiley & Sons, Ltd.     

Receding horizon control for multi-UAVs close formation control based on differential evolution

Close formation flight is one of the most complicated problems on multi-uninhabited aerial vehicles (UAVs) coordinated control. Based on the nonlinear model of multi-UAVs close formation, a novel type of control strategy of using hybrid receding horizon control (RHC) and differential evolution algorithm is proposed. The issue of multi-UAVs close formation is transformed into several on-line optimization problems at a series of receding horizons, while the differential evolution algorithm is adopted to optim...     

Characterization of Sky‐region Morphological‐temporal Airborne Collision Detection

Automated airborne collision‐detection systems are a key enabling technology for facilitating the integration of unmanned aerial vehicles (UAVs) into the national airspace. These safety‐critical systems must be sensitive enough to provide timely warnings of genuine airborne collision threats, but not so sensitive as to cause excessive false alarms. Hence, an accurate characterization of detection and false‐alarm sensitivity is essential for understanding performance tradeoffs, and system designers can exploit this characterization to help achieve a desired balance in system performance. In this paper, we experimentally evaluate a sky‐region, image‐based, aircraft collision‐detection system that is based on morphological and temporal processing techniques. (Note that the examined detection approaches are not suitable for the detection of potential collision threats against a ground clutter background.) A novel collection methodology for collecting realistic airborne collision‐course target footage in both head‐on and tail‐chase engagement geometries is described. Under (hazy) blue sky conditions, our proposed system achieved detection ranges greater than 1540 m in three flight test cases with no false‐alarm events in 14.14 h of nontarget data (under cloudy conditions, the system achieved detection ranges greater than 1170 m in four flight test cases with no false‐alarm events in 6.63 h of nontarget data). Importantly, this paper is the first documented presentation of detection range versus false‐alarm curves generated from airborne target and nontarget image data. © 2012 Wiley Periodicals, Inc.     

Collision-free formation generation and tracking of unmanned aerial vehicles based on physicomimetics approach

This paper investigates the problem of collision-free leader–follower formation generation and tracking of multiple fixed-wing unmanned aerial vehicles (UAVs). A group of UAVs, described by unicycle-type models subject to velocity constraints, are required to form a desired formation, while tracking a virtual leader and achieving collision-free flight. To handle this problem, a novel control law based on physicomimetics approach is proposed, which integrates the formation generation, formation tracking, and collision avoidance together. Physical forces are imitated to design artificial forces used in control laws that drive multiple UAVs to accomplish desired collaborative behaviors. Further, the virtual repulsion is embedded in the physicomimetics-based control scheme to achieve obstacle avoidance naturally. The artificial forces have similar meaning to the physical forces because of similar forms, which facilitates the design and adjustment of the control strategy. Specially, to deal with the speed constraints of fixed-wing UAVs, a saturation function is applied to modify the control laws and the stability is proved theoretically. Finally, numerical simulations and hardware-in-the-loop experiments are provided to verify the effectiveness of the proposed control scheme.     

面向目标跟踪的多机协同通信保持控制

由于无人机存在通信和测量约束的情况,远程无人机执行持续目标跟踪任务时无法直接与地面站保持通信,需要其他无人机作为通信中继方可与地面站建立可靠的通信连接.基于Dubins曲线,采用最小转弯半径和航向调整相结合的方法对具有初始和终止航向角约束的多无人机进行协同航路规划,确保所有无人机同时到达指定位置,形成多机协同通信保持的初始构型.针对随机移动目标,在多机协同通信保持的动态过程中,考虑平台性能、通信约束、碰撞规避等约束条件,采用非线性模型预测控制(NMPC)实现无人机协同分布式在线优化.在确保无人机通信中继保持的前提下,有效提高了算法的实时性.仿真结果表明了该算法的有效性.     

Modelling of UAV formation flight using 3D potential field

In this paper, we present a solution for formation flight and formation reconfiguration of unmanned aerial vehicles (UAVs). Based on a virtual leader approach, combined with an extended local potential field, the method is universal applicable by driving the vehicle’s auto pilot. The solution is verified, using a group of UAVs based on a simplified small scale helicopter, which is simulated in MATLAB^TM/Simulink^TM. As necessary for helicopters, the potential field approach is realized in 3D including obstacle and collision avoidance. The collision avoidance strategy could be used separately for the sense and avoid problem.     

Robust attitude control for tail‐sitter unmanned aerial vehicles in flight mode transitions

Tail‐sitter unmanned aerial vehicles (UAVs) can flight as rotorcrafts as well as fixed‐wing aircrafts, but it is hard to control the flight mode transition. The vehicle dynamics involves serious parametric uncertainties, highly nonlinear dynamics, and is easy to be affected by external disturbances, especially during the mode transition. This paper presents a robust control method for a kind of tail‐sitter UAVs to achieve the flight mode transition. The robust controller is proposed based on the state‐feedback control scheme and the robust compensation method. The proposed control method does not need to switch the coordinate system, the controller structure, or the controller parameters during the mode transitions. Theoretical analysis is given to guarantee the robustness stability of the designed flight control system. Numerical simulation results are presented to show the advantages of the proposed control method compared with the state‐feedback control method and the sliding mode control approach.     

An improved constrained differential evolution algorithm for unmanned aerial vehicle global route planning

This paper formulates the global route planning problem for the unmanned aerial vehicles (UAVs) as a constrained optimization problem in the three-dimensional environment and proposes an improved constrained differential evolution (DE) algorithm to generate an optimal feasible route. The flight route is designed to have a short length and a low flight altitude. The multiple constraints based on the realistic scenarios are taken into account, including maximum turning angle, maximum climbing/gliding slope, terrain, forbidden flying areas, map and threat area constraints. The proposed DE-based route planning algorithm combines the standard DE with the level comparison method and an improved strategy is proposed to control the satisfactory level. To show the high performance of the proposed method, we compare the proposed algorithm with six existing constrained optimization algorithms and five penalty function based methods. Numerical experiments in two test cases are carried out. Our proposed algorithm demonstrates a good performance in terms of the solution quality, robustness, and the constraint-handling ability.     

城市车载自组织网络中带有冲突估计的节点转发策略

针对目前城市环境中车载自组织网络车辆节点分布不均衡引起的消息传递冲突率高、传递效率低、路由可靠性差等问题,在IF(Irresponsible Forwarding)算法的基础上提出一种带有冲突估计的节点转发策略(NFCE算法)。收到消息的车辆节点首先确定自身的转发冲突概率,在不超过一定门限值的条件下,再根据节点的密度、通信半径大小以及到源节点的距离来确定自己的转发概率,最终概率大的节点优先转发消息。仿真结果表明,相比于其他算法,NFCE算法降低了节点传递冲突率,其路由有更高的效率和可靠性,特别在车辆密度较大时NFCE算法有明显的优势,更适合应用在城市环境中。     

Efficient Flight Control via Mechanical Impedance Manipulation: Energy Analyses for Hummingbird-Inspired MAVs

Within the growing family of unmanned aerial vehicles (UAV), flapping-wing micro aerial vehicles (MAV) are a relatively new field of research. Inspired by small size and agile flight of insects and birds, these systems offer a great potential for applications such as reconnaissance, surveillance, search and rescue, mapping, etc. Nevertheless, practicality of these vehicles depends on how we address various challenges ranging from control methodology to morphological construction and power supply design. A reasonable approach to resolving such problems is to acquire further inspiration from solutions in nature. Through modeling synchronous muscles in insects, we have shown that manipulation of mechanical impedance properties at wing joints can be a very efficient method for controlling lift and thrust production in flapping-wing MAVs. In the present work, we describe how this approach can be used to decouple lift/thrust regulation, thus reducing the complexity of flight controller. Although of simple design, this controller is still capable of demonstrating a high degree of precision and maneuverability throughout various simulated flight experiments with different types of trajectories. Furthermore, we use these flight simulations to investigate the power requirements of our control approach. The results indicate that these characteristics are considerably lower compared to when conventional control strategies—methods that often rely on manipulating stroke properties such as frequency or magnitude of the flapping motion—are employed. With less power demands, we believe our proposed control strategy is able to significantly improve flight time in future flapping-wing MAVs.