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

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

Abstract To address the challenges of sample utilization efficiency and managing temporal dependencies, this paper proposes an efficient path planning method for mobile robot in dynamic environments based on an improved twin delayed deep deterministic policy gradient (TD3) algorithm. The proposed me...

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Bibliographic Details
Main Authors: Yunhan Lin, Zhijie Zhang, Yijian Tan, Hao Fu, Huasong Min
Format: Article
Language:English
Published: Nature Portfolio 2025-05-01
Series:Scientific Reports
Subjects:
Path planning in dynamic environment
Twin delayed deep deterministic policy gradient (TD3) algorithm
Reinforcement learning
Prioritized experience replay (PER)
Long short-term memory (LSTM )
Online Access:https://doi.org/10.1038/s41598-025-02244-z
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https://doi.org/10.1038/s41598-025-02244-z

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