吉林大学学报(理学版) ›› 2025, Vol. 63 ›› Issue (2): 585-0594.

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复杂山区环境下的应急无人机路径规划

彭艺1, 唐剑1,2, 杨青青1   

  1. 1. 昆明理工大学 信息工程与自动化学院,  昆明 650500; 2. 邵阳工业职业技术学院 人工智能学院, 湖南 邵阳 422000
  • 收稿日期:2023-08-04 出版日期:2025-03-26 发布日期:2025-03-26
  • 通讯作者: 杨青青 E-mail:1061568608@qq.com

Emergency UAV Path Planning in Complex Mountainous Environment

PENG Yi1, TANG Jian1,2, YANG Qingqing1   

  1. 1. Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China;
    2. College of Artificial Intelligence, Shaoyang Industry Polytechnic College, Shaoyang 422000, Hunan Province, China
  • Received:2023-08-04 Online:2025-03-26 Published:2025-03-26

摘要: 针对复杂山区环境下应急通信无人机的飞行路径规划问题, 通过综合考虑障碍物、 无人机载重量、 无人机电池容量等约束条件, 为降低无人机的飞行时间并延长飞行距离, 基于Harris鹰算法框架设计一种改进Harris鹰算法的无人机三维路径规划方法. 首先, 对Harris鹰的种群初始位置、 位置更新方程和猎物的逃逸能量进行改进; 其次, 采用三次样条曲线插值法对路径进行平滑, 以确保无人机飞行过程中安全可靠且平滑; 最后, 将应急无人机在具有不同障碍物的山区进行测试, 并将所得结果与标准Harris鹰、 蚁群算法和人工蜂群算法进行对比分析. 分析结果表明, 该算法所规划的三维路径规划方法生成的路径更短, 并能更快地寻找到最优路径.

关键词: 路径规划, Harris鹰算法, 无人机, 最优路径

Abstract: Aiming at the flight path planning problem of emergency communication unmanned aerial vehicle (UAV) in complex mountainous environment, by  comprehensively considering the constraints such as obstacles, UAV load and UAV battery capacity, in order to reduce the flight time and extend the flight distance of UAV, based on the framework of Harris hawk algorithm, we designed a three-dimensional path planning method of UAV based on improved Harris hawk algorithm. Firstly, we  improved the initial position of Harris hawk population, position update equation and escape energy of prey. Secondly, the path was smoothed by using cubic spline curve interpolation method to ensure safe, reliable and smooth operation of the UAV during flight. Finally, the emergency UAV was tested in mountainous areas with different obstacles, and the results were compared with the standard Harris hawk, ant colony algorithm and artificial bee colony algorithm. The analysis results show that the path generated by the three-dimensional path planning method planned by this algorithm is shorter and can find the optimal path faster.

Key words: path planning, Harris hawk algorithm, unmanned aerial vehicle, optimal path

中图分类号: 

  • TP391