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

机译:基于自组织图的多无人机协同任务分配方法

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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:多无人机的协作任务分配是无人机完成军事任务的重要保证。当前的任务分配方法具有诸如执行时间长和无法考虑无人机自身容量约束的缺点。因此,在本文中,我们综合考虑了舰队的总飞行距离和每架无人机的武器负荷,将多无人机的协同任务分配问题建模为能力车辆选路问题(CVRP)。一种基于竞争神经网络的方法称为自组织特征图(SOM),用于解决任务分配问题。将该方法的性能与蚁群算法进行了比较。实验结果表明了该方法的可行性和有效性。

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