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Labour division algorithm for a group of unmanned aerial vehicles in a clustered target field

机译:集群目标字段中一组无人空中车辆的劳动司算法

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In this paper we propose an algorithm for tasks distribution (division of labour) for a group of unmanned aerial vehicles (UAVs) when monitoring an emergency zone. The input data of the algorithm are information on the homogeneous group of UAVs, the coordinates of the home point, and a set of elementary subtasks coming from the command center. The presented algorithm is analytical and allows obtaining the correct distribution result for any consistent input data. The algorithm is based on the principle of preliminary combining elementary tasks into clusters on a territorial basis. The results of simulation showed that the proposed labour distribution algorithm allows to achieve an average of 4.7% – 12.8% less time to complete a global task in comparison with the greedy algorithm. We experimentally established that the best result is achieved when choosing a cluster size so that about 75% of tasks are included in clusters, and 25% of tasks remain free.
机译:在本文中,我们提出了一种针对监测急诊区域的一组无人航空车辆(无人机)的任务分布(劳动分工)算法。 算法的输入数据是关于均匀的无人机组,主点的坐标的信息,以及来自命令中心的一组基本子组织。 呈现的算法是分析的,允许获得任何一致输入数据的正确分布结果。 该算法基于初步组合基本任务的原则在领土基础上进入群集。 仿真结果表明,与贪婪算法相比,建议的劳动力分布算法允许平均达到4.7% - 12.8%的时间少4.7% - 12.8%。 我们通过实验确定,在选择群集大小时,最佳结果是在群集中包含约75%的任务,25%的任务仍然是免费的。

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