1673-159X

CN 51-1686/N

基于柱坐标系的可变密度栅格无人机终端区航路规划

Route Planning of UAV Terminal Area with Variable Density Grid in Column Coordinate System

  • 摘要: 由于城市低空风险分布不均匀,无人机起降场终端区附近障碍物密集,多无人机在起降场终端区汇聚运行,传统基于直角坐标系的均匀密度栅格法难以解决该特定场景下的航路规划。针对以上难题,本文基于柱坐标系构建空域模型,分别提出基于 \mathrmA^* 算法与遗传算法的可变密度栅格法用于无人机终端区的航路规划。仿真结果表明,基于 \mathrmA^* 算法的柱坐标系可变密度栅格法比基于 \mathrmA^\mathrm* 算法的直角坐标系传统栅格法的航路规划效率提高了82.60%,路径总长度缩短了4.25%;基于遗传算法的柱坐标系可变密度栅格法比基于遗传算法的直角坐标系传统栅格法的航路规划效率提高了71.72%,路径总长度缩短了1.29%。本文方法解决了传统栅格法无法兼顾规划效率与环境描述精度的研究难题。

     

    Abstract: The traditional uniform density grid method in rectangular coordinate system is difficult to solve the route planning in the particular scenario due to the uneven distribution of low-altitude risks in cities, or the dense obstacles near the terminal area of the UAV landing field, and the converging operation of multiple UAVs in the terminal area. To solve the problems, this paper constructed the spatial model in column coordinate system, and proposed the variable density grid method based on A* algorithm and genetic algorithm for the route planning of the terminal area of the UAV take-off and landing field respectively. The relate simulation work was carried out. The results show that the route planning efficiency of the variable density grid method based on A* algorithm is improved by 82.60% and the total route length is shortened by 4.25% compared with the traditional grid method based on A* algorithm. Compared with the traditional grid method in car rectangular coordinate system based on genetic algorithm, the route planning efficiency of variable density grid method based on genetic algorithm is increased by 71.72%, and the total path length is shortened by1.29%.The presented method can solve the difficult problem that the traditional grid method can not take into account the planning efficiency and the environmental description accuracy.

     

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