A Hybrid Controller for Musculoskeletal Robots Targeting Lifting Tasks in Industrial Metaverse
文献类型：期刊论文
| 作者 | Qin, Shijie1,2; Li, Houcheng1,2 ; Cheng, Long1,2
|
| 刊名 | IEEE TRANSACTIONS ON CYBERNETICS
 |
| 出版日期 | 2024-02-14 |
| 页码 | 12 |
| 关键词 | Adaptive dynamic programming (ADP) brain-inspired method muscle synergy musculoskeletal system reinforcement learning (RL) tracking control |
| ISSN号 | 2168-2267 |
| DOI | 10.1109/TCYB.2024.3358739 |
| 通讯作者 | Cheng, Long(long.cheng@ia.ac.cn) |
| 英文摘要 | In manufacturing, musculoskeletal robots have gained more attention with the potential advantages of flexibility, robustness, and adaptability over conventional serial-link rigid robots. Focusing on the fundamental lifting tasks, a hybrid controller is proposed to overcome control challenges of such robots for widely applications in industry. The metaverse technology offers an available simulated-reality-based platform to verify the proposed method. The hybrid controller contains two main parts. A muscle-synergy-based radial basis function (RBF) network is proposed as the feedforward controller, which is able to characterize the phasic and the tonic muscle synergies simultaneously. The adaptive dynamic programming (ADP) is applied as the feedback controller to address the optimal control problem. The actor-critic structure is applied in the ADP-based controller, where the critic network is trained to approximate the optimal performance index and the actor network is trained to compute the optimal muscle excitations. Furthermore, the convergence and stability of the ADP algorithm are also analyzed. Finally, experiments have been designed to verify the effectiveness of this hybrid controller on an upper limb musculoskeletal system, and the comparisons with other controllers are also illustrated. The results show that the proposed controller can obtain a satisfactory performance for lifting tasks. |
| WOS关键词 | MUSCLE SYNERGIES ; LEARNING CONTROL ; TIME ; ARM ; COMBINATIONS ; SYSTEM |
| 资助项目 | National Key Research and Development Program of China |
| WOS研究方向 | Automation & Control Systems ; Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:001164066000001 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 资助机构 | National Key Research and Development Program of China |
| 源URL | [http://ir.ia.ac.cn/handle/173211/55661]  |
| 专题 | 多模态人工智能系统全国重点实验室 |
| 通讯作者 | Cheng, Long |
| 作者单位 | 1.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Inst Automat, State Key Lab Multimodal Artificial Intelligence S, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Qin, Shijie,Li, Houcheng,Cheng, Long. A Hybrid Controller for Musculoskeletal Robots Targeting Lifting Tasks in Industrial Metaverse[J]. IEEE TRANSACTIONS ON CYBERNETICS,2024:12. |
| APA | Qin, Shijie,Li, Houcheng,&Cheng, Long.(2024).A Hybrid Controller for Musculoskeletal Robots Targeting Lifting Tasks in Industrial Metaverse.IEEE TRANSACTIONS ON CYBERNETICS,12. |
| MLA | Qin, Shijie,et al."A Hybrid Controller for Musculoskeletal Robots Targeting Lifting Tasks in Industrial Metaverse".IEEE TRANSACTIONS ON CYBERNETICS (2024):12. |
入库方式： OAI收割
来源：自动化研究所
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