| 引用本文: | 马睿宸,白雪剑,王宇,王睿,王硕.基于强化学习的波动鳍推进水下作业机器人悬停控制[J].控制理论与应用,2022,39(11):2092~2099.[点击复制] |
| MA Rui-chen,BAI Xue-jian,WANG Yu,WANG Rui,WANG Shuo.Hovering control of an underwater vehicle-manipulator system propelled by undulatory fins via reinforcement learning[J].Control Theory and Technology,2022,39(11):2092~2099.[点击复制] |
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| 基于强化学习的波动鳍推进水下作业机器人悬停控制 |
| Hovering control of an underwater vehicle-manipulator system propelled by undulatory fins via reinforcement learning |
| 摘要点击 1051 全文点击 272 投稿时间：2021-11-01 修订日期：2022-09-13 |
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| DOI编号 10.7641/CTA.2022.11054 |
| 2022,39(11):2092-2099 |
| 中文关键词 水下作业机器人 悬停控制 波动鳍 神经网络 强化学习 |
| 英文关键词 underwater vehicle-manipulator system hovering control undulatory fin neural network reinforcement learning |
| 基金项目 国家自然科学基金项目(62122087, 62073316, U1806204, 62033013, U1713222), 中国科学院对外合作重点项目(173211KYSB20200020)资助. |
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| 中文摘要 |
| 本文针对波动鳍推进水下作业机器人的悬停控制问题开展研究. 首先, 给出了波动鳍推进水下作业机器人
的运动学模型、动力学模型和波动鳍的参数–力映射模型, 建立了基于马尔可夫决策过程的悬停控制训练框架. 其
次, 基于模型结构和训练策略, 使用强化学习的方法进行网络训练, 得到最佳的悬停控制器. 最终, 在室内水池中完
成了波动鳍推进水下作业机器人的悬停控制实验, 实验结果验证了所提方法的有效性. |
| 英文摘要 |
| This paper addresses the hovering control of an underwater vehicle-manipulator system (UVMS) propelled
by undulatory fins. First, the kinematic and dynamical models of the UVMS and a mapping model between the control
parameters of undulatory fins and the driving force of the UVMS are introduced, and a hovering control training framework
based on Markov decision process (MDP) is designed. Then, based on the framework and training strategies, the hovering
controller is fully trained via reinforcement learning method. Finally, the well-trained controller is applied in the real
environment, and the experimental results demonstrate that the proposed method can accomplish the UVMS’s hovering
control effectively. |
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