Knowledge Commons of Institute of Automation,CAS
Improving performance of robots using human-inspired approaches: a survey | |
Qiao, Hong1,2,3; Zhong, Shanlin1,2; Chen, Ziyu1,2; 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 |
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 |
七大方向——子方向分类 | 智能机器人 |
国重实验室规划方向分类 | 受人机理启发的类脑控制和类肌肉骨骼系统理论 |
是否有论文关联数据集需要存交 | 否 |
引用统计 | |
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. |
条目包含的文件 | 条目无相关文件。 |
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