无人机多目标路径规划的GA/DP混合解决方案

Chin-E. Lin, Yu Ming Syu
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引用次数: 2

摘要

遗传算法在无人机路径规划中得到了成功的应用。然而,对于多目标问题,应增加附加功能以提高无人机的性能。本文介绍了求解无人机系统多目标路径规划的动态规划方法。该混合方案将遗传算法与规划算法相结合,保证了无人机路径规划的安全性和可行性。为实现路径规划算法,建立了虚拟飞行地图(VFM)。在两个目标之间,遗传算法寻找具有合适适应度函数的最优路径;利用多目标对之间的距离矩阵,将两个目标路径规划扩展为多个目标。该算法确定多个目标的访问顺序,一次访问所有目标,最终以最短路径返回起始点。提出了一种完整的测试算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
GA/DP Hybrid Solution for UAV Multi-Target Path Planning
Genetic Algorithm (GA) has made successful application in unmanned aerial vehicle (UAV) path planning. However, for multi-target problem, additional function should be included to enhance UAV performance. This paper introduces the Dynamic Programming (DP) for solving multiple target path planning into UAV system. The proposed hybrid solution integrates GA with DP for UAV to guarantee the safety requirement and feasibility for path planning. The Virtual Flight Map (VFM) is built for path planning algorithm. Between two targets, GA finds the optimal path with suitable fitness function; while with the distance matrices between all pairs of multiple targets, DP expands the two target path planning into multiple targets. The DP decides the visiting sequence of multiple targets and visits all targets just in once tour and finally returns to the starting point in the shortest route. The proposed algorithm is formulated and integrated for complete tests.
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