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Updated: Jul 25, 2026

Long-term Behavioral Tracking of Freely Swimming Weakly Electric Fish
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基于学习的不连续路径,遵循生物仿真水下车辆的控制

Yu Wang1,2, Hongfei Chu1, Ruichen Ma1

  • 1State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China.

Research (Washington, D.C.)
|January 31, 2024
PubMed
概括

本研究引入了对仿生水下车辆 (BUV) 进行深度强化学习 (DRL) 控制,以导航复杂的,不连续的路径. 该方法可以实现自适应路径切换和翅膀控制,以实现更安全的水下勘探.

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