舰船电子工程2025，Vol.45Issue(7)：36-40,5.DOI:10.3969/j.issn.1672-9730.2025.07.009
基于改进DQN的无人机三维路径规划研究
Research on UAV 3D Path Planning Based on Improved DQN
孔建国 1赵恬恬 1梁海军 1刘晨宇 1马珂昕1
作者信息
- 1. 中国民用航空飞行学院空中交通管理学院 广汉 618300
- 折叠
摘要
Abstract
In order to solve the problems of poor convergence and low success rate of DQN in UAV path planning under un-known environment,a NoisyNet-DuelingDQN based pathplanning method is proposed.Based on the traditional DQN algorithm,the competition network is introduced to evaluate the value of each action better.Secondly,by introducing noise into the weight of the neural network,the space can be better explored and the optimal strategy can be found.Finally,the simulation results show that the algorithm hasbetter convergence and higher reward value than the traditional DQN and NoisyNet-DQN algorithms in different envi-ronments.After 60 000 simultaneous training times,the success rate of the algorithm is increased by 12.16%compared with DQN and 3.6%comparedwith NoisyNet-DQN.关键词
深度强化学习/路径规划/DQN算法/NoisyNet-DuelingDQNKey words
deep reinforcement learning/path planning/DQN algorithm/NoisyNet-DuelingDQN分类
信息技术与安全科学引用本文复制引用
孔建国,赵恬恬,梁海军,刘晨宇,马珂昕..基于改进DQN的无人机三维路径规划研究[J].舰船电子工程,2025,45(7):36-40,5.
