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

doi:10.1007/s11432-022-3606-1

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 机器人理论与应用

	Improving performance of robots using human-inspired approaches: a survey
	Qiao, Hong1,2,3 ; Zhong, Shanlin1,2 ; Chen, Ziyu 1,2; Wang, Hongze1,2
发表期刊	SCIENCE CHINA-INFORMATION SCIENCES
ISSN	1674-733X
	2022-12-01
卷号	65 期号:12 页码:31
通讯作者	Qiao, Hong(hong.qiao@ia.ac.cn)
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.
关键词	human-inspired intelligent robots brain-inspired intelligence decision making visual cognition musculoskeletal robots
DOI	10.1007/s11432-022-3606-1
关键词[WOS]	CAPTURABILITY-BASED ANALYSIS ; PEG-IN-HOLE ; OBJECT RECOGNITION ; ATTRACTIVE REGION ; NEURAL-NETWORK ; DIMENSIONALITY REDUCTION ; MUSCLE SYNERGIES ; DECISION-MAKING ; CORTICAL REPRESENTATION ; INSERTION STRATEGY
收录类别	SCI
语种	英语
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]
项目资助者	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
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Information Systems ; Engineering, Electrical & Electronic
WOS记录号	WOS:000887904900002
出版者	SCIENCE PRESS
引用统计	被引频次：38[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/51294
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.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.CAS Ctr Excellence Brain Sci & Intelligence Techn, 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	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.