多无人机协同覆盖路径规划

Cooperative coverage path planning for multiple UAVs

多无人机协同覆盖路径规划(CPP)由于其并行性和容错能力,对于提高无人机完成侦察、监视、搜索等任务的效率具有重要意义。提出了一种基于无人机任务性能评价和任务区域划分的多无人机协同CPP算法。定量分析了无人机执行覆盖任务的能力,根据无人机及携带成像传感器的性能给出了计算无人机任务性能指数的数学公式;提出了一种基于任务性能和子区域宽度的任务区域划分算法,使无人机的总转弯次数达到最少。仿真结果表明,所提出的CPP算法能够规划出全局最优的多无人机协同覆盖路径。

Because of its parallelism and fault tolerant capability,the cooperative coverage path planning（CPP）for UAVs is very important in enhancing UAV＇s abilities for reconnaissance,surveillance,search and other missions.An algorithm for cooperative CPP for multiple UAVs is proposed based on mission performance evaluation and mission region decomposition.The UAV＇s capabilities for coverage mission implementation are analyzed quantitatively.The formulas for calculating the mission performance index are given based on the performances of the UAV and the onboard imaging sensor.A subregion decomposition algorithm based on the mission performance of the UAV and the width of the subregion is proposed to get the least total number of turns.The simulation results show that we can obtain the global optimal cooperative paths for multiple UAVs by using the proposed algorithm.