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Reducing Redundancy of Musculoskeletal Robot With Convex Hull Vertexes Selection | |
Zhong, Shanlin1,2![]() ![]() ![]() ![]() | |
发表期刊 | IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS
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ISSN | 2379-8920 |
2020-09-01 | |
卷号 | 12期号:3页码:601-617 |
通讯作者 | Zhong, Shanlin(zhongshanlin2016@ia.ac.cn) |
摘要 | It has been a long-term dream of roboticist to create a robot that has similar behavior and appearance to human. With highly redundant joints and actuators, the musculoskeletal system of human can fulfill movement and operation with high precision, flexibility, and reliability. However, the redundancy of the musculoskeletal system also brings great difficulties to the control and fabrication of a human-like robot. Therefore, we propose an algorithm based on the convex hull theory to effectively reduce the number of redundant muscles. Specifically, taking the strength limitation and state-dependent characteristics of muscles into consideration, by analyzing the torque contribution of muscles for the discrete motion of joints, each muscle can be represented by a feature vector, and the convex hulls are formed by these vectors in high-dimensional space. By applying the proposed algorithm, the muscles corresponding to the vertexes of the convex hull are reserved while the redundant muscles within the convex hull are deleted, and a simplified model can be obtained. Sets of motion experiments demonstrate that the simplified model can achieve high-precision movement as a complete model. Based on the simplified model, a hardware platform of a robotic arm is constructed, which consists of six degrees of freedom and 11 pneumatic muscles. |
关键词 | Muscles Robots Mathematical model Hardware Redundancy Numerical models Convex hull vertexes human-like robot motion experiment musculoskeletal system reduce redundancy |
DOI | 10.1109/TCDS.2019.2953642 |
关键词[WOS] | COMPUTED MUSCLE CONTROL ; DYNAMIC SIMULATIONS ; UPPER EXTREMITY ; MODEL ; OPTIMIZATION ; SYNERGIES |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Key Research and Development Program of China[2017YFB1300200] ; National Key Research and Development Program of China[2017YFB1300203] ; National Natural Science Foundation of China[91648205] ; National Natural Science Foundation of China[61627808] ; Strategic Priority Research Program of Chinese Academy of Science[XDB32000000] |
项目资助者 | National Key Research and Development Program of China ; National Natural Science Foundation of China ; Strategic Priority Research Program of Chinese Academy of Science |
WOS研究方向 | Computer Science ; Robotics ; Neurosciences & Neurology |
WOS类目 | Computer Science, Artificial Intelligence ; Robotics ; Neurosciences |
WOS记录号 | WOS:000568663000020 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
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/173211/41968 |
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 | Zhong, Shanlin |
作者单位 | 1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 3.Chinese Acad Sci, Inst Automat, Res Ctr Brain Inspired Intelligence, Beijing 100190, Peoples R China 4.Univ Sci & Technol Beijing, Key Labs Res & Applicat Robot Intelligence Hand E, Beijing 100190, Peoples R China 5.Chinese Acad Sci, Inst Neurosci, Ctr Excellence Brain Sci & Intelligence Technol, Shanghai 200031, Peoples R 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 | Zhong, Shanlin,Chen, Jiahao,Niu, Xingyu,et al. Reducing Redundancy of Musculoskeletal Robot With Convex Hull Vertexes Selection[J]. IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS,2020,12(3):601-617. |
APA | Zhong, Shanlin,Chen, Jiahao,Niu, Xingyu,Fu, Hang,&Qiao, Hong.(2020).Reducing Redundancy of Musculoskeletal Robot With Convex Hull Vertexes Selection.IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS,12(3),601-617. |
MLA | Zhong, Shanlin,et al."Reducing Redundancy of Musculoskeletal Robot With Convex Hull Vertexes Selection".IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS 12.3(2020):601-617. |
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