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A Cooperative Task Assignment Method of Multi-UAV Based on Self Organizing Map

机译:基于自组织地图的多UV的合作任务任务分配方法

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Cooperative task assignment of multi unmanned aerial vehicles (UAV) is an important assurance for UAV to complete military missions. The current task assignment methods have drawbacks such as long execution time and failure to consider UAV's own capacity constraints. Therefore in this paper, we comprehensively considers the total flight distance of the fleet and the weapon load of each UAV, models the cooperative task assignment problem of multi-UAV as a capacitated vehicle routing problem (CVRP). A method based on a competitive neural network called self-organizing feature map (SOM) is used to solve the task assignment problem. The performance of proposed method is compared to that of ant colony algorithm. Experimental results show the feasibility and efficiency of the method.
机译:多人无人机(UAV)的合作任务分配是无人机完成军事代表团的重要保证。当前任务分配方法具有缺点,例如长的执行时间,并且无法考虑UAV的自己的容量约束。因此,在本文中,我们全面考虑了舰队的总飞行距离和每个无人机的武器负荷,为多UAV的协作任务分配问题模拟了电容车辆路由问题(CVRP)。一种基于竞争神经网络的方法,称为自组织特征映射(SOM)来解决任务分配问题。将所提出的方法的性能与蚁群算法进行比较。实验结果表明了该方法的可行性和效率。

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