无人机任务分配与航迹规划协同控制方法

Cooperative control algorithm of task assignment and path planning for multiple UAVs

针对无人机协同控制问题,提出一种多无人机任务分配与航迹规划的整体控制架构。将威胁和障碍区域考虑为合理的多边形模型,使用改进的A*算法规划出两个航迹点之间的最短路径。并利用该路径航程作为任务分配过程全局目标函数的输入,采用与协同系统相匹配的粒子结构进行改进粒子群优化(particle swarm optimization,PSO)任务分配迭代寻优。根据分配结果并考虑无人机性能约束,基于B-spline法平滑路径组合,生成飞行航迹。仿真结果表明,算法在保证计算速度和收敛性能的同时,能够产生合理的任务分配结果和无人机的可飞行航迹。

An integrating framework of task assignment and path planning for multiple unmanned aerial ve- hicles （UAVs） is presented. To avoid the obstacles area which is represented as polygon, the shortest path seg- ment between UAVs and task can be found by the improved A^＊ algorithm. According to this segment distance, the global objective function of task allocation is modeled. The assignment process is determined by improved particle swarm optimization （PSO）, which particle structure matches the cooperative system. The B-spline method is adopted to smooth the flight path, which consists of path segments of the assignment. Numerical re- suits demonstrate that the proposed method can achieve the optimal task assignment solution and best flight routes.