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UAV route planning based on the genetic simulated annealing algorithm

机译:基于遗传模拟退火算法的无人机航路规划

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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.
机译:针对无人机航路规划中遗传算法的局部最小问题,将模拟退火算法的Metropolis验收准则纳入遗传算法。在该算法中,原始的DEM(数字高程图)被处理为最小的威胁面。为了获得更平滑的飞行表面,原始的数字高程图在四个方向上进行处理,然后将遗传模拟退火算法用于在此最小威胁表面中进行三维路线规划。另外,将轨迹段与威胁之间的距离转换为高程值,并将其添加到适应度函数中,同时提出了较小的代码空间。仿真结果表明,所提出的遗传模拟退火算法是好的。

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