An Electrical Impedance Tomography Based Interface for Human-Robot Collaboration
Zheng, Enhao6; Li, Yuhua5,6; Zhao, Zhiyu5,6; Wang, Qining2,3,4; Qiao, Hong1,6
刊名IEEE-ASME TRANSACTIONS ON MECHATRONICS
2021-10-01
卷号26期号:5页码:2373-2384
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
ISSN号1083-4435
DOI10.1109/TMECH.2020.3039017
通讯作者Zheng, Enhao(enhao.zheng@ia.ac.cn)
英文摘要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.
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]
WOS关键词GRASPING FORCE ; POSTURE ; SIGNALS
WOS研究方向Automation & Control Systems ; Engineering
语种英语
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号WOS:000707442500015
资助机构National Natural Science Foundation of China ; Fundamental Research Funds for the Central Universities
内容类型期刊论文
源URL[http://ir.ia.ac.cn/handle/173211/46233]  
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Zheng, Enhao
作者单位1.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
2.Peking Univ, Beijing Innovat Ctr Engn Sci & Adv Technol BIC ES, Beijing 100871, Peoples R China
3.Peking Univ, Inst Artificial Intelligence, Beijing 100871, Peoples R China
4.Peking Univ, Coll Engn, Dept Adv Mfg & Robot, Beijing 100871, Peoples R China
5.China Univ Geosci Beijing, Sch Informat Engn, Beijing 100083, Peoples R China
6.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
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.
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