An Electrical Impedance Tomography Based Interface for Human-Robot Collaboration

doi:10.1109/TMECH.2020.3039017

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

	An Electrical Impedance Tomography Based Interface for Human-Robot Collaboration
	Zheng, Enhao1 ; Li, Yuhua 1,2; Zhao, Zhiyu 1,2; Wang, Qining 3,4,5; Qiao, Hong1,6
发表期刊	IEEE-ASME TRANSACTIONS ON MECHATRONICS
ISSN	1083-4435
	2021-10-01
卷号	26 期号:5 页码:2373-2384
通讯作者	Zheng, Enhao(enhao.zheng@ia.ac.cn)
摘要	Adaptation to the operator's intents and the external physical uncertainties is critical to the performances of the human-robot collaboration. In this study, we proposed a control interface that combined the electrical impedance tomography (EIT) based sensing approach with the robotic controllers to produce proper assistance with external uncertainties in the collaborative task. The interface first estimates the continuous forearm muscle contractions (represented by the grasp forces) by the optimized EIT features with an easily worn fabric band. The recognition decisions then serve as the control inputs to adjust the state transitions and the desired interaction forces in real time. We evaluated the interface in the tasks of grasp force estimation and human-robot sawing by recruiting more than 20 subjects in total. For grasp force estimation, the interface produced an average of R-2 >= 0.9 in both offline and online validations with the feature optimization procedure and a sigmoid regression function. The interface was robust to external disturbances without retraining or manual calibrations. The average R-2 = 0.86 with the untrained dynamic postures, and the average R-2 values ranged from 0.85 to 0.88 in the tests with redonning the front-end in interday and intraday uses. For human-robot sawing, the interface accomplished the tasks with a high success rate in controlling the states (>96%) and intuitive adjusting of the sawing forces, being combined with the designed hybrid admittance/position controller. It was also adaptive to the sawing frequency changes and the sawing directions according to the operator's intents. The interface's performances are comparable, if not better, to the state of the art on both biological signal based grasp force estimation and human-robot sawing. Future efforts are worth being paid in this new direction to get more promising outcomes.
关键词	Robot sensing systems Sensors Robots Electrodes Collaboration Muscles Task analysis Electrical impedance tomography (EIT) grasp force estimation human-machine interface human-robot collaboration
DOI	10.1109/TMECH.2020.3039017
关键词[WOS]	GRASPING FORCE ; POSTURE ; SIGNALS
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[61703400] ; National Natural Science Foundation of China[91648207] ; National Natural Science Foundation of China[51922015] ; National Natural Science Foundation of China[91948302] ; Fundamental Research Funds for the Central Universities[22120200149]
项目资助者	National Natural Science Foundation of China ; Fundamental Research Funds for the Central Universities
WOS研究方向	Automation & Control Systems ; Engineering
WOS类目	Automation & Control Systems ; Engineering, Manufacturing ; Engineering, Electrical & Electronic ; Engineering, Mechanical
WOS记录号	WOS:000707442500015
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
七大方向——子方向分类	人机融合
引用统计	被引频次：15[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/173211/46234
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	Zheng, Enhao
作者单位	1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.China Univ Geosci Beijing, Sch Informat Engn, Beijing 100083, Peoples R China 3.Peking Univ, Coll Engn, Dept Adv Mfg & Robot, Beijing 100871, Peoples R China 4.Peking Univ, Inst Artificial Intelligence, Beijing 100871, Peoples R China 5.Peking Univ, Beijing Innovat Ctr Engn Sci & Adv Technol BIC ES, Beijing 100871, Peoples R China 6.Univ Chinese Acad Sci, Beijing 100049, 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	Zheng, Enhao,Li, Yuhua,Zhao, Zhiyu,et al. An Electrical Impedance Tomography Based Interface for Human-Robot Collaboration[J]. IEEE-ASME TRANSACTIONS ON MECHATRONICS,2021,26(5):2373-2384.
APA	Zheng, Enhao,Li, Yuhua,Zhao, Zhiyu,Wang, Qining,&Qiao, Hong.(2021).An Electrical Impedance Tomography Based Interface for Human-Robot Collaboration.IEEE-ASME TRANSACTIONS ON MECHATRONICS,26(5),2373-2384.
MLA	Zheng, Enhao,et al."An Electrical Impedance Tomography Based Interface for Human-Robot Collaboration".IEEE-ASME TRANSACTIONS ON MECHATRONICS 26.5(2021):2373-2384.