首页|Intuitive Human-Robot-Environment Interaction With EMG Signals:A Review
Intuitive Human-Robot-Environment Interaction With EMG Signals:A Review
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原文链接
国家科技期刊平台
NETL
NSTL
万方数据
维普
A long history has passed since electromyography(EMG)signals have been explored in human-centered robots for intuitive interaction.However,it still has a gap between scientific research and real-life applications.Previous studies mainly focused on EMG decoding algorithms,leaving a dynamic rela-tionship between the human,robot,and uncertain environment in real-life scenarios seldomly concerned.To fill this gap,this paper presents a comprehensive review of EMG-based techniques in human-robot-environment interaction(HREI)systems.The gen-eral processing framework is summarized,and three interaction paradigms,including direct control,sensory feedback,and par-tial autonomous control,are introduced.EMG-based intention decoding is treated as a module of the proposed paradigms.Five key issues involving precision,stability,user attention,compli-ance,and environmental awareness in this field are discussed.Several important directions,including EMG decomposition,robust algorithms,HREI dataset,proprioception feedback,rein-forcement learning,and embodied intelligence,are proposed to pave the way for future research.To the best of what we know,this is the first time that a review of EMG-based methods in the HREI system is summarized.It provides a novel and broader perspective to improve the practicability of current myoelectric interaction systems,in which factors in human-robot interaction,robot-environment interaction,and state perception by human sensations are considered,which has never been done by previ-ous studies.
State Key Laboratory of Robotics,Shenyang Institute of Automation,Chinese Academy of Sciences,Shenyang 110016
Institutes for Robotics and Intelligent Manufacturing,Chinese Academy of Sciences,Shenyang 110169
University of Chinese Academy of Sciences,Beijing 100049,China
Institutes for Robotics and Intelligent Manufacturing,Chinese Academy of Sciences,Shenyang 110169,China
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国家重点研发计划国家重点研发计划国家重点研发计划国家重点研发计划国家重点研发计划国家自然科学基金国家自然科学基金国家自然科学基金国家自然科学基金国家自然科学基金国家自然科学基金Self-Planned Project of the State Key Laboratory of Robotics中国博士后科学基金
国家科技期刊平台
NSTL
万方数据
维普
