Autonomous obstacle avoidance of underground coal mine transport robots based on intrinsic motivation reinforcement learning algorithm

Existing robot obstacle avoidance methods mostly rely on preset rules or external reward signals, making it difficult to adapt to the complex and variable underground environment in coal mines. To achieve autonomous and efficient obstacle avoidance for underground coal mine transport robots, an auto...

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Bibliographic Details
Published in:Gong-kuang zidonghua
Main Authors: ZHAO Kebao, LI Lingfeng, CHEN Zhuo, HAN Jun, YIN Rui
Format: Article
Language:Chinese
Published: Editorial Department of Industry and Mine Automation 2025-06-01
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Online Access:http://www.gkzdh.cn/article/doi/10.13272/j.issn.1671-251x.2025040020

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