火力与指挥控制2024，Vol.49Issue(2)：119-124,6.DOI:10.3969/j.issn.1002-0640.2024.02.018
融合Q学习算法和人工势场算法的无人机航迹规划方法
UAV Route Planning Method Based on Fusion of Q-learning Algorithm and Artificial Potential Field Algorithm
刘冬 1余文泉 1霍文健 1李瑞 1姜伟月1
作者信息
- 1. 北方自动控制技术研究所,太原 030006
- 折叠
摘要
Abstract
Aiming at the problem of collision with static obstacles when using a flight route planned by Q-learning algorithm,a UAV route planning method based on fusion of Q-learning algorithm and artificial potential field algorithm is proposed.The method first uses the Q-learning algorithm to plan a route,then counts the obstacles contained in each flight leg of the route according to the map,and finally applies the improved artificial potential field method to re-plan the flight leg containing obstacles.The experimental results show that the proposed fusion method can plan the shortest route to avoid collision with static obstacles at the cost of a small amount of time and trajectory length.关键词
航迹规划/Q学习算法/人工势场/无人机Key words
route planning/Q-learning algorithm/artificial potential field/UAV分类
信息技术与安全科学引用本文复制引用
刘冬,余文泉,霍文健,李瑞,姜伟月..融合Q学习算法和人工势场算法的无人机航迹规划方法[J].火力与指挥控制,2024,49(2):119-124,6.
