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Efficient TD3 based path planning of mobile robot in dynamic environments using prioritized experience replay and LSTM.

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第一作者： Yunhan,Lin

第一单位： School of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, 430081, China.;Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System, Wuhan University of Science and Technology, Wuhan, 430081, China.;Institute of Robotics and Intelligent Systems, Wuhan University of Science and Technology, Wuhan, 430081, China.

作者： Yunhan,Lin ^[1] ; Zhijie,Zhang ^[1] ; Yijian,Tan ^[1] ; Hao,Fu ^[2] ; Huasong,Min ^[3]

作者单位： School of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, 430081, China.;Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System, Wuhan University of Science and Technology, Wuhan, 430081, China.;Institute of Robotics and Intelligent Systems, Wuhan University of Science and Technology, Wuhan, 430081, China. ^[1] School of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, 430081, China.;Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System, Wuhan University of Science and Technology, Wuhan, 430081, China. ^[2] Institute of Robotics and Intelligent Systems, Wuhan University of Science and Technology, Wuhan, 430081, China. mhuasong@wust.edu.cn. ^[3]

关键词 Long short-term memory (LSTM )Path planning in dynamic environment Prioritized experience replay (PER)Reinforcement learning Twin delayed deep deterministic policy gradient (TD3) algorithm

DOI 10.1038/s41598-025-02244-z

PMID 40419617

发布时间 2025-05-30

基金项目

2022YFB4700400/National Key Research and Development Program of China 62073249/National Natural Science Foundation of China 2023BBB011/Key R&D Program of Hubei Province

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