Knowledge Commons of Institute of Automation,CAS
From Rough to Precise: Human-Inspired Phased Target Learning Framework for Redundant Musculoskeletal Systems | |
Zhou, Junjie1,2,3; Chen, Jiahao2,3,4; Deng, Hu1,3; Qiao, Hong1,2,5 | |
发表期刊 | FRONTIERS IN NEUROROBOTICS |
ISSN | 1662-5218 |
2019-07-31 | |
卷号 | 13期号:61页码:14 |
摘要 | Redundant muscles in human-like musculoskeletal robots provide additional dimensions to the solution space. Consequently, the computation of muscle excitations remains an open question. Conventional methods like dynamic optimization and reinforcement learning usually have high computational costs or unstable learning processes when applied to a complex musculoskeletal system. Inspired by human learning, we propose a phased target learning framework that provides different targets to learners at varying levels, to guide their training process and to avoid local optima. By introducing an extra layer of neurons reflecting a preference, we improve the Q-network method to generate continuous excitations. In addition, based on information transmission in the human nervous system, two kinds of biological noise sources are introduced into our framework to enhance exploration over the solution space. Tracking experiments based on a simplified musculoskeletal arm model indicate that under guidance of phased targets, the proposed framework prevents divergence of excitations, thus stabilizing training. Moreover, the enhanced exploration of solutions results in smaller motion errors. The phased target learning framework can be expanded for general-purpose reinforcement learning, and it provides a preliminary interpretation for modeling the mechanisms of human motion learning. |
关键词 | musculoskeletal system human-inspired motion learning noise in nervous system reinforcement learning phased target learning |
DOI | 10.3389/fnbot.2019.00061 |
关键词[WOS] | PHYSICAL LIMITS ; MUSCLE ; MODEL ; MOVEMENT ; CONTRACTION ; PREDICTION ; CRITERION ; TENDON ; NOISE |
收录类别 | SCI |
语种 | 英语 |
资助项目 | Strategic Priority Research Program of Chinese Academy of Science[XDB32000000] ; National Key Research and Development Program of China[2017YFB1300203] ; National Key Research and Development Program of China[2017YFB1300200] ; Development of Science and Technology of Guangdong Province Special Fund Project[2016B090910001] ; National Natural Science Foundation of China[91648205] ; National Natural Science Foundation of China[61627808] ; National Natural Science Foundation of China[61627808] ; National Natural Science Foundation of China[91648205] ; Development of Science and Technology of Guangdong Province Special Fund Project[2016B090910001] ; National Key Research and Development Program of China[2017YFB1300200] ; National Key Research and Development Program of China[2017YFB1300203] ; Strategic Priority Research Program of Chinese Academy of Science[XDB32000000] |
WOS研究方向 | Computer Science ; Robotics ; Neurosciences & Neurology |
WOS类目 | Computer Science, Artificial Intelligence ; Robotics ; Neurosciences |
WOS记录号 | WOS:000478024100002 |
出版者 | FRONTIERS MEDIA SA |
七大方向——子方向分类 | 类脑模型与计算 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/27764 |
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 | Qiao, Hong |
作者单位 | 1.State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China 2.School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China 3.Beijing Key Laboratory of Research and Application for Robotic Intelligence of “Hand–Eye–Brain” Interaction, Beijing, China 4.Research Center for Brain-Inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing, China 5.CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai, China |
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 | Zhou, Junjie,Chen, Jiahao,Deng, Hu,et al. From Rough to Precise: Human-Inspired Phased Target Learning Framework for Redundant Musculoskeletal Systems[J]. FRONTIERS IN NEUROROBOTICS,2019,13(61):14. |
APA | Zhou, Junjie,Chen, Jiahao,Deng, Hu,&Qiao, Hong.(2019).From Rough to Precise: Human-Inspired Phased Target Learning Framework for Redundant Musculoskeletal Systems.FRONTIERS IN NEUROROBOTICS,13(61),14. |
MLA | Zhou, Junjie,et al."From Rough to Precise: Human-Inspired Phased Target Learning Framework for Redundant Musculoskeletal Systems".FRONTIERS IN NEUROROBOTICS 13.61(2019):14. |
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