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Robust Motion Learning for Musculoskeletal Robots Based on a Recurrent Neural Network and Muscle Synergies | |
Jiahao Chen1![]() ![]() ![]() | |
发表期刊 | IEEE Transactions on Automation Science and Engineering
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ISSN | 1545-5955 |
2024 | |
页码 | 1-16 |
通讯作者 | Huang, Xiao(huangxiao@bit.edu.cn) |
文章类型 | 学术论文 |
摘要 | Musculoskeletal robots with human-like joints, muscles, and actuation mechanisms are characterized by exceptional dexterity, compliance, and versatility. However, existing reinforcement learning methods for such robots rely on precise and sufficient state observation, rendering them vulnerable to perturbations. To address this limitation, this paper proposes a robust motion learning method based on a recurrent neural network (RNN) and muscle synergy. First, the proposed method utilizes task-joint-muscle space states to create an RNN-based neuromuscular controller. Furthermore, a motion learning method with a synergistic constraint of muscles is developed. Additionally, theoretical analysis confirms that the RNN-based controller is more robust to perturbations of state observation than a Multilayer Perceptron (MLP) based controller. The proposed method is evaluated on a simulated musculoskeletal robot and demonstrates superior robustness to other MLP-based reinforcement learning methods. Furthermore, the proposed method is also validated on a musculoskeletal robot hardware system, indicating its potential for real-world applications. |
关键词 | Musculoskeletal system Robots Muscles Reinforcement learning Robustness Learning systems Recurrent neural networks Musculoskeletal robots recurrent neural network muscle synergy robustness |
DOI | 10.1109/TASE.2024.3379247 |
关键词[WOS] | MODEL |
收录类别 | SCIE |
语种 | 英语 |
资助项目 | National Natural Science Foundation of China |
项目资助者 | National Natural Science Foundation of China |
WOS研究方向 | Automation & Control Systems |
WOS类目 | Automation & Control Systems |
WOS记录号 | WOS:001193633600001 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
七大方向——子方向分类 | 智能机器人 |
国重实验室规划方向分类 | 受人机理启发的类脑控制和类肌肉骨骼系统理论 |
是否有论文关联数据集需要存交 | 否 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/57180 |
专题 | 多模态人工智能系统全国重点实验室_机器人理论与应用 |
通讯作者 | Huang X(黄销) |
作者单位 | 1.Institute of Automation, Chinese Academy of Sciences 2.中国科学院大学 3.北京科技大学 4.北京理工大学 |
第一作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Jiahao Chen,Wu YX,Yao CJ,et al. Robust Motion Learning for Musculoskeletal Robots Based on a Recurrent Neural Network and Muscle Synergies[J]. IEEE Transactions on Automation Science and Engineering,2024:1-16. |
APA | Jiahao Chen,Wu YX,Yao CJ,&Huang X.(2024).Robust Motion Learning for Musculoskeletal Robots Based on a Recurrent Neural Network and Muscle Synergies.IEEE Transactions on Automation Science and Engineering,1-16. |
MLA | Jiahao Chen,et al."Robust Motion Learning for Musculoskeletal Robots Based on a Recurrent Neural Network and Muscle Synergies".IEEE Transactions on Automation Science and Engineering (2024):1-16. |
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Robust_Motion_Learni(4084KB) | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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