首页> 外文会议>Foundations of Intelligent Systems; Lecture Notes in Artificial Intelligence; 4203 >Genetic Algorithm Based Approach for Multi-UAV Cooperative Reconnaissance Mission Planning Problem
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Genetic Algorithm Based Approach for Multi-UAV Cooperative Reconnaissance Mission Planning Problem

机译:基于遗传算法的多无人机协同侦察任务规划方法

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Multiple UAV cooperative reconnaissance is one of the most important aspects of UAV operations. This paper presents a genetic algorithm(GA) based approach for multiple UAVs cooperative reconnaissance mission planning problem. The objective is to conduct reconnaissance on a set of targets within predefined time windows at minimum cost, while satisfying the reconnaissance resolution demands of the targets, and without violating the maximum travel time for each UAV. A mathematical formulation is presented for the problem, taking the targets reconnaissance resolution demands and time windows constraints into account, which are always ignored in previous approaches. Then a GA based approach is put forward to resolve the problem. Our GA implementation uses integer string as the chromosome representation, and incorporates novel evolutionary operators, including a subsequence crossover operator and a forward insertion mutation operator. Finally the simulation results show the efficiency of our algorithm.
机译:多次无人机协同侦察是无人机作战最重要的方面之一。本文提出了一种基于遗传算法的多种无人机协同侦察任务计划方法。目的是在预定的时间范围内以最小的成本对一组目标进行侦察,同时满足目标的侦察分辨率要求,并且不违反每个无人机的最大行驶时间。针对该问题,提出了一种数学公式,其中考虑了目标侦察分辨率要求和时间窗口约束,而在先前的方法中始终将其忽略。然后提出了一种基于遗传算法的解决方案。我们的GA实现使用整数字符串作为染色体表示,并结合了新颖的进化算子,包括子序列交叉算子和正向插入突变算子。最后的仿真结果表明了该算法的有效性。

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