基于聚类算法的多无人机系统任务分配

摘要

针对现有任务分配方法在任务点较多时不易解算,且计算量大的问题,提出了基于模糊C-均值聚类算法的多无人机系统任务分配方法.首先,利用模糊C-均值聚类算法得到的隶属度矩阵对任务点进行初始分配；其次,针对基于空间划分聚类可能造成各UAV任务不均衡的问题,设计任务的局部优化调整规则；最后,结合单旅行商问题,利用Tabu Search算法为各UAV设计最优任务航线.仿真结果表明,该方法能有效解决多无人机系统的任务分配问题,算法具有较好的时效性.%Aiming to reduce the computational complexity of the present task allocation strategy,a method of task allocation for Multi-UAV system is proposed based on the fuzzy C-means clustering algorithm.First of all,initial task allocation is achieved based on the membership degree matrix of task points; secondly,the initial task allocation plan is partially adjusted to achieve the relative balance of each UAV's task; finally,with the model of the single traveling salesman problem,the optimal task route of each UAV is calculated by Tabu Search Algorithm.The simulation results show that this method can effectively solve the multi-UAV task allocation problem,and the algorithm has a better timeliness.