基于遗传模拟退火算法的无人机航路规划

Hao Meng, Guizhou Xin
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引用次数: 23

摘要

针对遗传算法在无人机航路规划中的局部最小问题,本文将模拟退火算法的Metropolis可接受准则引入到遗传算法中。该算法将原始DEM(数字高程图)处理成最小的威胁面。为了获得更光滑的飞行表面,对原始数字高程图进行4个方向的处理,然后利用遗传模拟退火算法在该最小威胁表面进行三维航路规划。此外,将轨迹段与威胁之间的距离转换为高程值,并将其加入适应度函数中,同时提出了更小的编码空间。仿真结果表明,所提出的遗传模拟退火算法是良好的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
UAV route planning based on the genetic simulated annealing algorithm
For the local minimum problem of genetic algorithm in unmanned aerial vehicle route planning, the Metropolis acceptance criteria of simulated annealing algorithm is incorporated into the genetic algorithm in this paper. In the algorithm, the original DEM (Digital Elevation Map) is processed into the smallest threat surface. In order to obtain a more smooth surface of flight, the original digital elevation map are processed in four directions, and then the genetic simulated annealing algorithm is used for three-dimensional route planning in this minimal threat surface. In addition, the distance between the track segment and threats are converted into elevation values and the value is added to the fitness function, a smaller code space was proposed at the same time. The simulation results show that the Genetic Simulated Annealing Algorithm proposed is good.
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