Motor-Cortex-Like Recurrent Neural Network and Multitask Learning for the Control of Musculoskeletal Systems
文献类型：期刊论文
| 作者 | Chen, Jiahao2,3,4 ; Qiao, Hong1,2,3,4
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| 刊名 | IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS
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| 出版日期 | 2022-06-01 |
| 卷号 | 14期号:2页码:424-436 |
| 关键词 | Muscles Musculoskeletal system Robots Statistics Sociology Recurrent neural networks Neurons Biologically inspired motor cortex muscle synergy musculoskeletal system neuromuscular control recurrent neural network (RNN) |
| ISSN号 | 2379-8920 |
| DOI | 10.1109/TCDS.2020.3045574 |
| 通讯作者 | Qiao, Hong(hong.qiao@ia.ac.cn) |
| 英文摘要 | The musculoskeletal robot is a promising direction of the next-generation robots. However, current control methods of musculoskeletal robots lack multitask learning ability, great generalization, and biological plausibility. In this article, a motor-cortex-like recurrent neural network (RNN) and a reward-modulated multitask learning method are proposed. First, inspired by the dynamic system hypothesis of motor cortex, the RNN is introduced to transform movement targets into muscle excitations. The condition that makes an RNN generate motor-cortex-like consistent population response is investigated. Second, a reward-modulated multitask learning method of such an RNN is proposed. In the experiments, the control of a musculoskeletal system is realized with multitask learning ability, great generalization, and robustness for noises. Furthermore, the RNN and muscle excitations demonstrate motor-cortex-like consistent population response and human-like muscle synergies, respectively. Therefore, the proposed method has better performance and biological plausibility, and verifies the neural mechanisms in the robotic research. |
| WOS关键词 | MUSCLE SYNERGIES ; CORTICAL REPRESENTATION ; DYNAMIC SIMULATIONS ; DIRECTION ; ARM |
| 资助项目 | National Key Research and Development Program of China[2017YFB1300203] ; National Natural Science Foundation of China[91648205] ; National Natural Science Foundation of China[61627808] ; National Natural Science Foundation of China[91948303] ; Strategic Priority Research Program of Chinese Academy of Science[XDB32050100] |
| WOS研究方向 | Computer Science ; Robotics ; Neurosciences & Neurology |
| 语种 | 英语 |
| WOS记录号 | WOS:000809402600019 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 资助机构 | National Key Research and Development Program of China ; National Natural Science Foundation of China ; Strategic Priority Research Program of Chinese Academy of Science |
| 源URL | [http://ir.ia.ac.cn/handle/173211/49216]  |
| 专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_机器人应用与理论组 |
| 通讯作者 | Qiao, Hong |
| 作者单位 | 1.CAS Ctr Excellence Brain Sci & Intelligence Techn, Shanghai 200031, Peoples R China 2.Beijing Key Lab Res & Applicat Robot Intelligence, Beijing 100190, Peoples R China 3.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 4.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Chen, Jiahao,Qiao, Hong. Motor-Cortex-Like Recurrent Neural Network and Multitask Learning for the Control of Musculoskeletal Systems[J]. IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS,2022,14(2):424-436. |
| APA | Chen, Jiahao,&Qiao, Hong.(2022).Motor-Cortex-Like Recurrent Neural Network and Multitask Learning for the Control of Musculoskeletal Systems.IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS,14(2),424-436. |
| MLA | Chen, Jiahao,et al."Motor-Cortex-Like Recurrent Neural Network and Multitask Learning for the Control of Musculoskeletal Systems".IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS 14.2(2022):424-436. |
入库方式： OAI收割
来源：自动化研究所
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