中文版 | English
Title

Research on Interaction Force for the Human-robot System based on Double People Walking Experiments

Author
Corresponding AuthorFu, Chenglong
DOI
Publication Years
2022
Conference Name
7th IEEE International Conference on Advanced Robotics and Mechatronics
ISBN
978-1-6654-8307-0
Source Title
Pages
1098-1103
Conference Date
JUL 09-11, 2022
Conference Place
null,Guilin,PEOPLES R CHINA
Publication Place
345 E 47TH ST, NEW YORK, NY 10017 USA
Publisher
Abstract
Walking requires metabolic energy, especially in load-carriage. Many wearable devices have been proposed to assist humans in walking with loads, such as elastic backpacks, exoskeletons, and supernumerary robotic legs (SRLs). Although remarkable progress has been obtained in this field, they still lack appropriate physical interaction control and response strategy, which may lead to crashing and dragging problems. Owing to the complexity of human walking, appropriate interaction force control is crucial to fulfilling the task of compliant human-robot cooperation. However, there is nearly no research on the human-robot interaction force during human walking presently. To address this issue, double people cooperative walking experiments have been designed to obtain the rules of timing and magnitude of the interaction force. Since human beings can adjust the step length and speed to different walking situations for energy saving, these two participants automatically enter into the cooperative walking pattern after a few steps at the beginning. The interaction force obtained from the cooperative walking pattern is likely to be energetically optimal for the overall system. The result shows that the double people can provide forward propulsion for the former in the double stance (DS) phase to reduce the metabolic cost by reducing the needed ground reaction force. It is also found that the data of the interaction force is positively correlated with the acceleration of the human center of mass (CoM). It also implies that in a human-robot system, the robot motion control system estimates the appropriate interaction forces by tracking the acceleration of the CoM, which may contribute to inspiring the design of the physical interaction control system of a human-robot system.
Keywords
SUSTech Authorship
First ; Corresponding
Language
English
URL[Source Record]
Indexed By
Funding Project
National Natural Science Foundation of China["U1913205","52175272"] ; Guangdong Basic and Applied Basic Research Foundation[2020B1515120098] ; Science, Technology, and Innovation Commission of Shenzhen Municipality["SGLH20180619172011638","ZDSYS20200811143601004"] ; Stable Support Plan Program of Shenzhen Natural Science Fund[20200925174640002] ; Joint Fund of Science & Technology Department of Liaoning Province[2020-KF-22-03] ; State Key Laboratory of Robotics, China[2020-KF-22-03]
WOS Research Area
Automation & Control Systems ; Engineering ; Robotics
WOS Subject
Automation & Control Systems ; Engineering, Electrical & Electronic ; Robotics
WOS Accession No
WOS:000926398000183
Data Source
Web of Science
PDF urlhttps://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9959182
Citation statistics
Cited Times [WOS]:0
Document TypeConference paper
Identifierhttp://kc.sustech.edu.cn/handle/2SGJ60CL/415840
DepartmentDepartment of Mechanical and Energy Engineering
工学院
Affiliation
1.Southern Univ Sci & Technol, Dept Mech & Energy Engn, Shenzhen Key Lab Biomimet Robot & Intelligent Sys, Shenzhen 518055, Peoples R China
2.Southern Univ Sci & Technol, Dept Mech & Energy Engn, Guangdong Prov Key Lab Human Augmentat & Rehabil, Shenzhen 518055, Peoples R China
First Author AffilicationDepartment of Mechanical and Energy Engineering
Corresponding Author AffilicationDepartment of Mechanical and Energy Engineering
First Author's First AffilicationDepartment of Mechanical and Energy Engineering
Recommended Citation
GB/T 7714
Yang, Ping,Leng, Yuquan,Fu, Chenglong. Research on Interaction Force for the Human-robot System based on Double People Walking Experiments[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE,2022:1098-1103.
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2022 ARM-Research_on(1325KB) Restricted Access--
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