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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TabuSearch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 at the problem that the existing task allocation method is not easy to solve when the number of task points is large and the calculation is heavy, a task allocation method based on fuzzy C-means clustering algorithm is proposed. First of all, the assignment of the task points is carried out by using the membership matrix obtained by the fuzzy C-means clustering algorithm. Secondly, aiming at the problem that the UAV tasks may be unbalanced based on the spatial clustering, the local optimization and adjustment rules of the tasks are designed. Finally, Combining with single traveling salesman problem, TabuSearch algorithm is used to design the optimal mission route for each UAV. The simulation results show that this method can effectively solve the task assignment problem of multi-UAV system, and the algorithm has better timeliness.