针对无人机有效、安全巡检输电线路的路径问题,提出了一种基于遗传算法的输电线路无人机巡检路径规划方法,采用极坐标编码方式对无人机巡检路径构造染色体;结合实际情况中的无人机巡检各种约束问题,设计了适合于无人机巡检路径规划的遗传算子;实验结果证明算法能综合考虑各种因素,提高了全局寻优能力,是解决实际输电线路无人机巡检路径规划问题的较好办法.
This paper, concerned with the problem of multi--objective multi--constraint path planning for power transmission lines inspection, presents a path planning for power transmission lines inspection with unmanned aerial vehicle based on genetic--pattern searching algorithm. The polar coding is used to construct chromosomes for flight direction. Combined with every constraint of inspection with UAV (Unmanned Aerial Vehicle) with the practical situation, genetic operators that fit to the path of inspection are designed. Experiments results demonstrate that the proposed algorithm is effective and efficient to plan optimal paths for a UAV with changing or fluctuating performances, thus improves its solvability for global optimization, which verifies that this algorithm is an ideal solution to the problem of power transmission lines inspection with UAV with the practical situation.