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Task allocation of multiple UAVs and targets using improved genetic algorithm

机译:使用改进的遗传算法任务分配多个无人机和目标

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In this paper, task allocation of multi-Unmanned Aerial Vehicles (UAVs) is studied, that is, multi-UAVs from different bases should be allocated to attack multiple targets. Based on the existing task allocation model, which just take the values of targets, UAVs and weapons into account, the fuel consumption is added into consideration to make the model much more practical. An improved genetic algorithm is proposed for such a multi-UAVs multi-targets task allocation. Simulation results show that the algorithm is significantly effective and the allocation result is reasonable.
机译:在本文中,研究了多人空中车辆(无人机)的任务分配,即应该分配来自不同基地的多UVS以攻击多个目标。基于现有的任务分配模型,刚刚考虑到目标,无人机和武器的价值,加入了燃料消耗,以考虑到模型更实用。提出了一种改进的遗传算法,用于这种多无人机多目标任务分配。仿真结果表明,该算法显着有效,分配结果是合理的。

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