无人机群变航迹多任务综合规划方法研究

Study on Changeable Path Planning and Multi-Task Assignment Optimization Design for Unmanned Aerial Vehicles Cluster

将无人机群作为一个整体,对任务和航线进行综合规划有利于提高效率,减少油耗。为了缩短机群的任务完成时间,减少飞行航程,提出了一种启发式的任务和轨迹综合规划方法。通过将各无人机的任务执行时间趋于均衡以减小机群任务的总完成时间,同时兼顾同一无人机执行的多个任务在路径上的相邻,使得机群的总飞行航程得到缩短,从而减少了油耗。仿真试验表明,任务轨迹综合规划算法与仅考虑航线或任务执行时间的算法相比较,机群的任务完成时间减少了18%左右,提高了无人机群的工作效率,减少了油耗。

In order to reduce tasks execution time and the route, a changeable path planning and multi-task assignment optimization design method is introduced in this paper. Tasks finishing time of unmanned aerial vehicles （UAVs） cluster is reduced by tasks balanced distribution to each UAV and flying route is shortened by adjacent tasks distribution to same UAV. The result proves that compared with route priority algorithm or task priority algorithms, The tasks finishing time of UAVs cluster of the proposed method is decreased 18% and fuel consumption is reduced obviously.