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Motion Learning for Musculoskeletal Robots Based on Cortex-Inspired Motor Primitives and Modulation | |
Xiaona Wang1,2![]() ![]() ![]() | |
发表期刊 | IEEE Transactions on Cognitive and Developmental Systems
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ISSN | 2379-8920 |
2024 | |
卷号 | 16期号:2页码:744-756 |
通讯作者 | Chen, Jiahao(jiahao.chen@ia.ac.cn) |
文章类型 | 学术论文 |
摘要 | Musculoskeletal robots have structural advantages of flexibility, robustness, and compliance. However, the control of such musculoskeletal robots is challenging. In particular, the efficiency and generalization of motion learning for such robots are still limited. Inspired by motor preparation theories of the motor cortex and motor primitives in neuroscience, a novel neuromuscular control method with high learning efficiency and great generalization is proposed. First, a recurrent neural network (RNN)-based neuromuscular controller is proposed, which autonomously evolves from the initial state of neurons to generate muscle excitations. Second, the motor primitive of initial states in an RNN is proposed and constructed as common knowledge for muscle control. Third, a motion learning method for the modulation of motor primitives is proposed. In the experiments, the proposed method is validated by a redundant musculoskeletal robot and compared with related methods. It demonstrates better performance in terms of learning efficiency, accuracy, and generalization. In addition, the fault tolerance of initial states is analyzed and the robustness to noise is demonstrated. |
关键词 | Biologically inspired control motor preparation motor primitive musculoskeletal robot recurrent neural network (RNN) |
DOI | 10.1109/TCDS.2023.3293097 |
关键词[WOS] | MODEL ; MOVEMENT ; SYSTEMS |
收录类别 | SCIE |
语种 | 英语 |
资助项目 | Major Project of Science and Technology Innovation 2030 C Brain Science and Brain-Inspired Intelligence |
项目资助者 | Major Project of Science and Technology Innovation 2030 C Brain Science and Brain-Inspired Intelligence |
WOS研究方向 | Computer Science ; Robotics ; Neurosciences & Neurology |
WOS类目 | Computer Science, Artificial Intelligence ; Robotics ; Neurosciences |
WOS记录号 | WOS:001197861000013 |
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/173211/57182 |
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 | Jiahao Chen |
作者单位 | 1.中国科学院自动化研究所 2.中国科学院大学 |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Xiaona Wang,Jiahao Chen,Wei Wu. Motion Learning for Musculoskeletal Robots Based on Cortex-Inspired Motor Primitives and Modulation[J]. IEEE Transactions on Cognitive and Developmental Systems,2024,16(2):744-756. |
APA | Xiaona Wang,Jiahao Chen,&Wei Wu.(2024).Motion Learning for Musculoskeletal Robots Based on Cortex-Inspired Motor Primitives and Modulation.IEEE Transactions on Cognitive and Developmental Systems,16(2),744-756. |
MLA | Xiaona Wang,et al."Motion Learning for Musculoskeletal Robots Based on Cortex-Inspired Motor Primitives and Modulation".IEEE Transactions on Cognitive and Developmental Systems 16.2(2024):744-756. |
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