基于行为方法和路径规划的群无人机分布式避障方法

Haixiang Wang, Pencheng Wen, L. Bai
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引用次数: 0

摘要

本文研究了群无人机的避障方法。该方法可避免蜂群通过障碍物区域时长时间的队形分裂。基于行为方法,在地层边界约束下设计了一种致密地层控制方法。这种分布式方法只需要每架无人机与邻近的蜂群进行通信。提出了一种基于粒子群优化(PSO)算法的航路规划新方法,为群无人机在障碍物区域规划一条与编队宽度相匹配的安全可飞航路。规划的路线作为蜂群的共识信息,相当于一个虚拟的无人机。在避障过程中,蜂群无人机被视为一个整体,按照规划的路线形成密集编队。仿真结果验证了该方法的有效性和合理性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Distributed Obstacle Avoidance Method for Swarm UAVs based on Behavioral Approach and Route Planning
In this paper, we study the obstacle avoidance method of swarm UAVs. This method is used to avoid the longtime split of the formation when the swarm passes through the obstacle area. A control method of the dense formation is designed based on the behavioral approach with the constraints of formation boundary. This distributed method just needs each UAV to communicate with neighboring individuals of the swarm. A new route planning method based on Particle Swarm Optimization (PSO) algorithm is proposed to plan a safe and flyable route matching the formation width for swarm UAVs in the area with obstacles. The planned route serves as the consensus information of the swarm, which is equivalent to a virtual UAV. During avoiding obstacles, swarm UAVs are treated as a whole, and the swarm forms a dense formation by following the planned route. Simulation results are presented to demonstrate the effectiveness and rationality of the proposed method.
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