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...

詳細記述

書誌詳細
出版年:Gong-kuang zidonghua
主要な著者: ZHAO Kebao, LI Lingfeng, CHEN Zhuo, HAN Jun, YIN Rui
フォーマット: 論文
言語:中国語
出版事項: Editorial Department of Industry and Mine Automation 2025-06-01
主題:
オンライン・アクセス:http://www.gkzdh.cn/article/doi/10.13272/j.issn.1671-251x.2025040020