基于自组织地图的多无人机协同任务分配方法

Shurong Zhu, Yingzhou Zhang, Yang Gao, Fan Wu
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引用次数: 5

摘要

多架无人机协同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存在执行时间长、不能考虑无人机自身能力约束等缺点。因此,综合考虑机群的总飞行距离和每架无人机的武器载荷,将多架无人机的协同任务分配问题建模为一个有能力的车辆路径问题(CVRP)。采用一种基于竞争神经网络的自组织特征映射(SOM)方法来解决任务分配问题。将该方法与蚁群算法的性能进行了比较。实验结果表明了该方法的可行性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Cooperative Task Assignment Method of Multi-UAV Based on Self Organizing Map
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.
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