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Improving performance of robots using human-inspired approaches: a survey

文献类型：期刊论文

作者Qiao, Hong1,2,3; Zhong, Shanlin2,3; Chen, Ziyu2,3; Wang, Hongze2,3
刊名SCIENCE CHINA-INFORMATION SCIENCES
出版日期2022-12-01
卷号65期号:12页码:31
ISSN号1674-733X
关键词human-inspired intelligent robots brain-inspired intelligence decision making visual cognition musculoskeletal robots
DOI10.1007/s11432-022-3606-1
通讯作者Qiao, Hong(hong.qiao@ia.ac.cn)
英文摘要Realizing high performance of ordinary robots is one of the core problems in robotic research. Improving the performance of ordinary robots usually relies on the collaborative development of multiple research fields, resulting in high costs and difficulty to complete some high-precision tasks. As a comparison, humans can realize extraordinary overall performance under the condition of limited computational-energy consumption and low absolute precision in sensing and controlling each body unit. Therefore, developing human-inspired robotic systems and algorithms is a promising avenue to improve the performance of robotic systems. In this review, the cutting-edge research work on human-inspired intelligent robots in decision-making, cognition, motion control, and system design is summarized from behavior- and neural-inspired aspects. This review aims to provide a significant insight into human-inspired intelligent robots, which may be beneficial for promoting the integration of neuroscience, machinery, and control, so as to develop a new generation of robotic systems.
WOS关键词CAPTURABILITY-BASED ANALYSIS ; PEG-IN-HOLE ; OBJECT RECOGNITION ; ATTRACTIVE REGION ; NEURAL-NETWORK ; DIMENSIONALITY REDUCTION ; MUSCLE SYNERGIES ; DECISION-MAKING ; CORTICAL REPRESENTATION ; INSERTION STRATEGY
资助项目Major Project of Science and Technology Innovation 2030-Brain Science and Brain-Inspired Intelligence[2021ZD0200408] ; National Natural Science Foundation of China[91948303] ; National Natural Science Foundation of China[62203443] ; Strategic Priority Research Program of Chinese Academy of Sciences[XDB32050100] ; Science Foundation for Youth of the State Key Laboratory of Management and Control for Complex System[2022QN09]
WOS研究方向Computer Science ; Engineering
语种英语
出版者SCIENCE PRESS
WOS记录号WOS:000887904900002
资助机构Major Project of Science and Technology Innovation 2030-Brain Science and Brain-Inspired Intelligence ; National Natural Science Foundation of China ; Strategic Priority Research Program of Chinese Academy of Sciences ; Science Foundation for Youth of the State Key Laboratory of Management and Control for Complex System
源URL[http://ir.ia.ac.cn/handle/173211/51293]  
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.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
3.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		 Qiao, Hong,Zhong, Shanlin,Chen, Ziyu,et al. Improving performance of robots using human-inspired approaches: a survey[J]. SCIENCE CHINA-INFORMATION SCIENCES,2022,65(12):31.
APA Qiao, Hong,Zhong, Shanlin,Chen, Ziyu,&Wang, Hongze.(2022).Improving performance of robots using human-inspired approaches: a survey.SCIENCE CHINA-INFORMATION SCIENCES,65(12),31.
MLA Qiao, Hong,et al."Improving performance of robots using human-inspired approaches: a survey".SCIENCE CHINA-INFORMATION SCIENCES 65.12(2022):31.

入库方式： OAI收割

来源：自动化研究所

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