Prediction of Human Voluntary Torques Based on Collaborative Neuromusculoskeletal Modeling and Adaptive Learning
文献类型:期刊论文
作者 | Wang, Weiqun1,2; Shi, Weiguo1,2; Hou, Zeng-Guang1,2,3; Chen, Badong4; Liang, Xu1,2; Ren, Shixin1,2; Wang, Jiaxing1,2; Peng, Liang1,2 |
刊名 | IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS |
出版日期 | 2021-06-01 |
卷号 | 68期号:6页码:5217-5226 |
ISSN号 | 0278-0046 |
关键词 | Muscles Adaptation models Adaptive learning Force Calibration Hip Electromyography Adaptive learning human– robot interaction neuromusculoskeletal modeling parameter calibration surface electromyography (sEMG) processing |
DOI | 10.1109/TIE.2020.2991999 |
英文摘要 | Surface Electromyography (sEMG) based human-robot interaction has been widely studied, where prediction of human voluntary torques is one of the key issues that have not been well addressed. In this article, a torque prediction method based on collaborative neuromusculoskeletal modeling and adaptive learning, is proposed to overcome the limitation of existing methods. First, an sEMG-torque model is designed in comprehensive consideration of the previous research results, the requirement for subject-specific adjustment and the coupling between the muscle or muscle-tendon length and the adjacent joint angles, where the latter two factors have rarely been considered in the literature. Then, by combining the advantages of the stochastic particle swarm optimization and conjugate gradient algorithms, a collaborative optimization method is designed to calibrate simultaneously the undetermined parameters. Moreover, an adaptive learning method based on Gaussian process regression is proposed to learn and predict the estimation errors in real time, by which it is supposed that the torque prediction accuracy can be improved efficiently. Finally, experiments were carried out to validate the performance of the proposed method. |
资助项目 | National Natural Science Foundation of China[91648208] ; National Natural Science Foundation of China[91848110] ; National Natural Science Foundation of China[U1913601] ; National Key R&D Program of China[2017YFB1302303] ; Strategic Priority Research Program of Chinese Academy of Science[XDB32000000] |
WOS研究方向 | Automation & Control Systems ; Engineering ; Instruments & Instrumentation |
语种 | 英语 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
WOS记录号 | WOS:000621470900060 |
资助机构 | National Natural Science Foundation of China ; National Key R&D Program of China ; Strategic Priority Research Program of Chinese Academy of Science |
源URL | [http://ir.ia.ac.cn/handle/173211/43317] |
专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_先进机器人控制团队 |
通讯作者 | Hou, Zeng-Guang |
作者单位 | 1.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 3.CAS Ctr Excellence Brain Sci & Intelligence Techn, Beijing 100190, Peoples R China 4.Jiaotong Univ, Inst Artificial Intelligence & Robot, Xian 710049, Peoples R China |
推荐引用方式 GB/T 7714 | Wang, Weiqun,Shi, Weiguo,Hou, Zeng-Guang,et al. Prediction of Human Voluntary Torques Based on Collaborative Neuromusculoskeletal Modeling and Adaptive Learning[J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS,2021,68(6):5217-5226. |
APA | Wang, Weiqun.,Shi, Weiguo.,Hou, Zeng-Guang.,Chen, Badong.,Liang, Xu.,...&Peng, Liang.(2021).Prediction of Human Voluntary Torques Based on Collaborative Neuromusculoskeletal Modeling and Adaptive Learning.IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS,68(6),5217-5226. |
MLA | Wang, Weiqun,et al."Prediction of Human Voluntary Torques Based on Collaborative Neuromusculoskeletal Modeling and Adaptive Learning".IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 68.6(2021):5217-5226. |
入库方式: OAI收割
来源:自动化研究所
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