空天预警研究学报2024，Vol.38Issue(2)：122-127,137,7.DOI:10.3969/j.issn.2097-180X.2024.02.010
一种无人机路径规划强化学习算法
A reinforcement learning algorithm for combat UAV path planning
陈孝如 1潘正党 2陈立军1
作者信息
- 1. 广州软件学院软件工程系,广州 510990
- 2. 正阳县职业中等专业学校,河南驻马店 463699
- 折叠
摘要
Abstract
In order to make it uneasy for unmanned aerial vehicles(UAVs)to be attacked by the ground am-bush of individual anti-aircraft weapons,this paper proposes a new reinforcement learning algorithm used for com-bat UAVs to perform the mission of missile avoidance,shortest path flight and formation flight.The algorithm combines self-imitation learning and stochastic network refining algorithm to enhance exploration through amplifi-cation of imitation effect(AIE).Experimental results show that the proposed algorithm is very effective in finding the shortest flight path for the combat UAV while avoiding enemy missiles,and is also superior to the existing al-gorithm in terms of convergence speed and learning stability.This provides a certain reference for the UAVs to avoid being hit by missiles.关键词
无人机/强化学习/自主飞行管理/路径规划Key words
UAV/reinforcement learning/autonomous flight management/path planning分类
交通工程引用本文复制引用
陈孝如,潘正党,陈立军..一种无人机路径规划强化学习算法[J].空天预警研究学报,2024,38(2):122-127,137,7.
