Path Planning of Mobile Robot in Dynamic Obstacle Avoidance Environment Based on Deep Reinforcement Learning

Path Planning of Mobile Robot in Dynamic Obstacle Avoidance Environment Based on Deep Reinforcement Learning

In this study, to address the issues faced by mobile robots in complex environments, such as sparse rewards caused by limited effective experience, slow learning efficiency in the early stages of training, as well as poor obstacle avoidance performance in environments with dynamic obstacles, the aut...

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Bibliographic Details
Main Authors: Qingfeng Zhang, Wenpeng Ma, Qingchun Zheng, Xiaofan Zhai, Wenqian Zhang, Tianchang Zhang, Shuo Wang
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Intrinsic curiosity module
LSTM network
mobile robot
path planning
reinforcement learning
Online Access:https://ieeexplore.ieee.org/document/10769446/
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