基于自适应粒子群算法的多无人机混合编队技术

为了解决无人机群体在复杂战场环境下的编队、避障、避碰问题,提出了一种将基于行为法和虚拟领航者法相结合的混合编队技术;为无人机编队设计了奔向目标、队形保持、避碰及避障共4种基本行为,通过对编队无人机的行为权重参数进行调整控制无人机编队的机动,编队无人机的行为权重参数通过自适应粒子群算法进行优化,然后对编队无人机的基本行为进行矢量合成,归一化处理后控制无人机的机动;仿真实验测试证明了该方法能使无人机群体保持期望的队形,实现了编队避障和内部避碰,进而更有效地完成编队任务,提高了多无人机编队的机动性能,促进了多无人机混合技术的发展。     

基于信息图的多无人机三维协同搜索动目标方法

针对多无人机协同搜索区域内多运动目标问题,考虑传感器的探测概率与虚警概率、无人机的飞行与避撞约束和目标随机运动等特征,提出基于信息图的多无人机三维协同搜索方法.以无人机搜索的短期收益、长期收益和协调收益的平衡为核心,考虑无人机三维运动的特征,构建多无人机协同搜索的数学规划模型,并设计包含目标存在概率、环境不确定度、重访信息素和搜索增益4个因子的搜索信息图.基于滚动规划架构,整合新提出的剪枝方法进行模型的求解.在典型的协同搜索场景下,通过数值仿真验证所提方法的有效性.仿真结果表明,所提出的方法可以在秒级的时间内做出每架无人机的三维航迹决策,重访信息素和搜索增益因子可以引导无人机捕获更多的目标.对比仿真结果表明,所提出的方法可以在捕获更多目标的同时具有更少的误判次数,有效提升了多无人机协同搜索的任务效能.     

基于分布式一致性的无人机编队控制方法

多无人机系统中,系统状态的一致性是实现多无人机协同控制的基础,针对多无人机中存在的三维空间编队控制问题,提出一种分布式一致性的无人机编队协同控制方法。在主机-从机组成的多无人机系统的基础上,引入分布式结构,设计无人机控制系统模型并建立无人机编队协同机制。根据协同机制设计基于一致性算法的协同编队控制器、基于匈牙利算法的任务分配策略以及避障策略。分别在简易模拟器和基于ROS-Gazebo的实景模拟器中仿真验证了协同控制方法的有效性。结果表明：无人机群能够有效地完成协同编队任务,并且可以通过调整层次结构进行有效编队重构。     

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,避免发生机间碰撞,保障飞行安全.在典型场景下,仿真验证了策略的有效性,相比传统垂线搜索方法,本策略能在保证安全的前提下,引导无人机群捕获更多的目标,有效提升了多无人机协同搜索追踪的效果.     

一种多约束下无人机编队的模型预测控制算法

针对多无人机在编队飞行过程中需满足机间避碰、通信、避障等约束的问题,设计一种考虑多约束的分布式模型预测控制算法,使无人机编队在满足上述约束的前提下,实现轨迹跟踪、队形保持.首先,在不考虑通信时延、外界干扰、噪声的情况下,以四旋翼为控制对象,建立线性时不变的单机及编队运动模型;然后,在考虑状态约束、输入约束、机间避碰、机间通信、避障等多种约束的情况下,以轨迹跟踪、队形保持为控制目标,基于虚拟领航策略设计一种分布式模型预测控制算法;接着,对优化问题的可行性以及编队系统的渐近稳定性进行分析,其中算法的终端部分设计、相容性约束设计是保证系统稳定的关键;最后,利用6架无人机仿真验证所提出控制算法的有效性.     

面向无人机自主防碰撞的认知博弈制导控制

针对非隔离空域中的无人机碰撞规避问题,提出一种基于认知博弈制导的无人机自主防碰撞方法.首先,描述了非隔离空域中无人机自主防碰撞控制问题.其次,建立了无人机与入侵机的运动学模型,并构建了无人机的认知安全域,将无人机碰撞规避问题转化为涉及两方的博弈问题.然后,提出了制导策略集的求解方法.最后,仿真结果验证了所提方法的有效性.     

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.     

面向多无人飞行器的有界跟踪控制方法的设计与验证

针对多无人机跟踪轨迹时的控制问题和安全问题,本文提出了一种四旋翼无人飞行器的有界跟踪控制方法.该方法能够保证多台无人机在进行轨迹跟踪的同时将自身运动限制在指定范围内.本文通过能量分析的方法设计了具体形式的控制器,并基于Lyapunov稳定性分析证明了系统误差的有界和收敛特性.在此基础上,通过设计和搭建室内多无人飞行器实验平台,完成了多无人飞行器实时轨迹跟踪的实验,验证了该控制器的实际性能.实验结论表明,无人飞行器的有界跟踪方法不但拥有良好的动态特性,而且能够有效地避免无人飞行器越过安全边界造成碰撞等问题,具有较好的安全性和鲁棒性.     

无人机协同控制研究综述

无人机（UAV）协同控制是指一组UAV以机间通信为基础、群体智能为核心,合作分工完成某一共同任务的控制方式。UAV集群是拥有一定自主能力的大量UAV基于局部规则执行各项任务的多智能体系统,与单架UAV相比,UAV集群有着高效率、高灵活性和高可靠性等优点。针对近几年UAV协同控制技术的最新发展动态,首先,从民用和军事两个角度举例说明多UAV技术的应用前景;接着,对比分析一致性控制、蜂拥控制和编队控制这三种主流协同控制方式的区别与发展现状;最后,对协同控制面临的时延、避障和续航等问题提出几点建议,为未来UAV协同控制研究发展提供一定帮助。     

基于柱状空间和改进A*算法的无人机规避方法

针对无人机避障问题,提出了基于改进A~*算法和柱状空间的无人机规避方法。首先,根据无人机飞行区域的障碍物分布情况,建立飞行区域的柱状空间;然后将障碍物对无人机的影响引入到估价函数中,重新设计启发函数;最后将基于柱状空间和改进A~*算法的无人机规避方法应用于无人机的规避中,并对规划的路径进行平滑处理。仿真结果表明,该算法能够有效地实现无人机的规避。     

Artificial Force Field for Haptic Feedback in UAV Teleoperation

The feedback upon which operators in teleoperation tasks base their control actions differs substantially from the feedback to the driver of a vehicle. On the one hand, there is often a lack of sensory information; on the other hand, there is additional status information presented via the visual channel. Haptic feedback could be used to unload the visual channel and to compensate for the lack of feedback in other modalities. For collision avoidance, haptic feedback could provide repulsive forces via the control inceptor. Haptic feedback allows operators to interpret the repulsive forces as impedance to their control deflections when a potential for collision exists. Haptic information can be generated from an artificial force field (AFF) that maps environment constraints to repulsive forces. This paper describes the design and theoretical evaluation of a novel AFF, i.e., the parametric risk field, for teleoperation of an uninhabited aerial vehicle (UAV). The field allows adjustments of the size, shape, and force gradient by means of parameter settings, which determine the sensitivity of the field. Computer simulations were conducted to evaluate the effectiveness of the field for collision avoidance for various parameter settings. Results indicate that the novel AFF more effectively performs the collision avoidance function than potential fields known from literature. Because of its smaller size, the field yields lower repulsive forces, results in less force cancellation effects, and allows for larger UAV velocities. This indicates less operator control demand and more effective UAV operations, both expected to lead to lower operator workload, while, at the same time, increasing safety.     

Design and implementation of a leader-follower cooperative control system for unmanned helicopters

In this paper, we present a full scheme for the cooperative control of multiple unmanned aerial vehicle (UAV) helicopters. We adopt the leader-follower pattern to maintain a fixed geometrical formation while navigating the UAVs following certain trajectories. More specifically, the leader is commanded to fly on some predefined trajectories, and each follower is controlled to maintain its position in formation using the measurement of its inertial position and the information of the leader position and velocity, obtained through a wireless modem. More specifications are made for multiple UAV formation flight. In order to avoid possible collisions of UAV helicopters in the actual formation flight test, a collision avoidance scheme based on some predefined alert zones and protected zones is employed. Simulations and experimental results are presented to verify our design.     

Repulsive force control based on distance computation algorithm

Computer-aided repulsive force control of collision avoidance is presented in this paper. A repulsive force is artificially created using the distances between the robot links and obstacles, which are generated by a simplified distance computation algorithm. This distance computation algorithm is based on the Gilbert-Johnson-Keerthi algorithm. Control gains in the repulsive force control model are selected based on traditional control design and genetic algorithms. Results on shortest distance computation and collision detection are presented. Real-time manipulator collision avoidance control has achieved. A repulsive force gain is introduced through the approaches for definition of link coordinate frames and kinematics computations. The safety distance between objects is affected by the repulsive force gain. Safety zone can be adjustable by the repulsive force gain which is selected by a specified fitness function of the genetic algorithm.     

A review on communication protocols for autonomous unmanned aerial vehicles for inspection application

The communication system is a critical part of the system design for the autonomous Unmanned Aerial Vehicle (UAV). It has to address different considerations, including efficiency, reliability and mobility of the UAV. In addition, a multi-UAV system requires a communication system to assist information sharing, task allocation and collaboration in a team of UAVs. In this paper, we review communication solutions for supporting a team of UAVs while considering an application in the power line inspection industry. We provide a review of candidate wireless communication technologies for supporting communication in UAV applications. Performance measurements and UAV-related channel modeling of those candidate technologies are reviewed. A discussion of current technologies for building UAV mesh networks is presented. We then analyze the structure, interface and performance of robotic communication middleware, ROS and ROS2. Based on our review, the features and dependencies of candidate solutions in each layer of the communication system are presented.     

一站多机便携式无人机测控系统

针对目前多无人机协同作战应用需求,增强了无人机测控系统多机测控能力,实现了多机多系统互通互联互操作和资源共享等兼容与协同工作。分析了数字多波束相控阵天线,平台+插件的软件架构以及 XML技术的帧格式信息和参数信息描述等关键技术,研制了一款兼顾多型多目标通用化要求和后续无人机建设的扩展性需求的便携式无人机测控系统。该系统具备经扩展改造后进行新建无人机测控管理的能力,满足无人机多类型、多型号不断扩展的需求,减少无人机测控装备种类,提高综合测控保障能力,降低新型无人机系统装备建设成本。     

仿鹰鸽捕食逃逸行为的多无人机分组对抗博弈方法

针对多无人机对抗问题, 本文提出了一种三维空间中仿鹰鸽捕食逃逸行为的多无人机分组对抗博弈方法.在分析鹰鸽捕食逃逸行为的基础上, 文章构建了多无人机博弈对抗系统模型, 并定义了微分博弈中的连续可微值函数, 证明了值函数满足Hamilton-Jacobi-Isaacs(HJI)方程, 从而保证鞍点策略存在. 使用最优分配方法, 为仿鹰无人机一方设计了分组对抗分配策略, 以解决多无人机追逃场景中的任务分配问题. 本文对比仿真实验结果验证了所提出方法的有效性.     

Collision Avoidance Based on Line-of-Sight Angle

This paper focuses on the problem of collision avoidance for Unmanned Aerial Vehicles (UAVs). The dynamics of the UAV are modeled as a Dubins vehicle flying at constant altitude. The angular velocity is used as control input in order to avert a possible collision with a single obstacle, while the speed is left as an extra degree of freedom to achieve some temporal requirements. The proposed control algorithm uses only the line-of-sight angle as feedback: in this sense, the main contribution of this paper is providing a solution to the collision avoidance problem that can be used in situations where it is not possible to measure data such as position and velocity of the obstacle. A theoretical analysis of the result is provided, followed by simulation results that validate the efficacy of the control strategy.     

Smooth transition for collision avoidance of redundant robots: An on-line polynomial approach

The presence of cooperation between robots and machines in the industrial environment improved the solution for several manufacturing problems. With cooperation, new challenges emerged, and among these stands out the collision avoidance between such robots and machines. Collision avoidance can be dealt with in several ways, taking into account the computational effort to make a decision and the quality of the calculated trajectory for the robots, evaluated, for instance, by smooth profiles avoiding sudden variations in joints’ velocities or acceleration. In these circumstances, the involved robots need to be redundant since new movements are necessary for avoiding collisions. The strategies for collision avoidance are offline (i.e., based on pre-programming the task), or online (i.e., implemented while the robot performs the main task). In online collision avoidance strategies, numerical performance must ensure the time requirements of the main task performed by the robot; so, numerically efficient solutions are the most appropriate. This paper presents a proposal for the collision avoidance treatment from fixed obstacles for redundant robots, based on polynomial functions. The proposed solution allows achieving smooth trajectories according to criteria based on the continuity of derivatives in trajectory curve transitions. When the robot is out of the imminent collision, it is proposed to solve the inverse kinematics through the Adaptive Extended Jacobians. Throughout the text, the mathematical developments based on polynomials are presented, and in the end, a case study graphically shows comparative results.     

基于PSO的多无人机协同任务目标分配方法

针对多无人机协同任务分配的特点进行分析,在分析多种分配算法的基础上,提出离散粒子群算法求解多UAV任务分配问题。分析离散粒子群算法的原理,给出求解过程,利用计算机对一个简单的多UAV协同问题进行仿真,验证离散粒子群算法的有效性。      

Monte Carlo Simulation Analysis of Tagged Fish Radio Tracking Performance by Swarming Unmanned Aerial Vehicles in Fractional Order Potential Fields

Tracking fish using implanted radio transmitters is an important part of studying and preserving native fish species. However, conventional methods for locating the fish after they are tagged can be time consuming and costly. Unmanned Aerial Vehicles (UAV) have been used in general radio localization applications and can possibly be used to locate fish quickly and effectively. However, the methods developed for multi-UAV navigation and transmitter localization are complex and might not work well for practical and routine use. This work focuses on developing simple methods for multi-UAV navigation and transmitter localization. A real-world simulator is created to test these methods; it includes a signal propagation model based on actual data from a UAV. Swarm-like navigation methods (using potential fields) are used for multi-UAV navigation, and an Extended Kalman Filter is used, along with a simplified version of the propagation model, to estimate the location of the transmitter. Multiple navigation methods are introduced and compared using Monte Carlo Analysis. Despite a noisy signal and a simplified measurement model, the different navigation methods are able to estimate the location of the transmitter with one or more UAVs.