基于分合粒子群算法的多无人机任务重分配

多UAV在执行任务过程中,战场环境以及UAV编队状态的改变将导致原有的分配计划失效或效率降低,因此有必要重新分配任务。针对多无人机任务重分配问题,首先建立了相应的数学模型。其次运用分组基础上的任务重分配策略进行任务分配,提出了改进的K均值聚类算法进行初步分组,再在分组的基础下,提出了分合粒子群优化算法进行组内任务分配。最后进行实验仿真。实验结果与分析表明基于分合粒子群算法的任务重分配方法能有效地满足多变的战场环境要求。

Multi-UAV Dynamic Task Assignment by Particle Swarm Optimization Algorithm Based on Division and Union Strategy

With the mission implemented by multi-UAV,the change of the battle field and formation state of UAV may cause failure of the original distribution plan or reduce efficiency,so it is necessary to execute multi-UAV dynamic task assignment again.Firstly,a formulation was proposed for it.Then task reassignment based on grouping was used.,task grouping was implemented according to improved k-means algorithm,and particle swarm optimization algorithm based on division and union strategy was used to make task reassignment inside a group.In the end,a simulation proceeds.The simulation results indicate that the approach satisfies the requirements of the battle field.