面向协同区域反恐侦察的无人机集群规划与控制

Planning and Control of UAV Swarms for Cooperative Regional Anti-terrorist Reconnaissance

以无人机集群协同侦察多个区域内潜在的恐怖分子为背景,提出了一种基于贪婪算法的求解思路,设计了任务分配-路径规划-跟踪控制的算法流程,解决了面向协同区域反恐侦察的无人机集群规划与控制问题。首先,设计任务分配算法,为无人机分配任务区域,解决多无人机多目标的任务分配问题;然后,每一架无人机进行路径规划,生成从当前点到任务区域以及在任务区域侦察的组合路径;再使用追踪虚拟目标点的方法,使无人机沿着规划航线飞行。任务分配-路径规划-跟踪控制在线滚动执行,使无人机集群协同执行反恐侦察任务。对上述算法进行了数值仿真,并基于开源仿真平台搭建复合翼无人机协同仿真环境,进一步验证了算法流程。

This paper considers the problem of a swarm of UAVs cooperative reconnaissance of terrorists in multiple regions.The solution based on greedy algorithm is proposed,which consists of task allocation,path planning,and tracking control,and thus solves the planning and control problem of a swarm of UAVs cooperative regional anti-terrorism reconnaissance.First,the task allocation algorithm is designed to allocate the task area for UAVs to solve the task allocation problem involving multi-UAV and multi-target.Then each UAV carries out path planning,and generates a combined path from the current point to the mission area and reconnaissance in the mission area.Besides,the method of tracking virtual target points is used to make the UAVs fly along the planned route.Task allocation,path planning,tracking control are carried out online in a rolling way,to enable UAV swarms to perform anti-terrorism reconnaissance tasks cooperatively.In this paper,the above algorithm is numerically simulated,and the collaborative simulation environment of compound wing UAV is built based on the open-source simulation platform,which further verifies the algorithm process.