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Cadence-Insensitive Soft Exoskeleton Design With Adaptive Gait State Detection and Iterative Force Control
Tan XW(谈晓伟)1,2,3; Zhang B(张弼)1,2; Liu GJ(刘光军)4; Zhao XG(赵新刚)1,2; Zhao YW(赵忆文)1,2
Department机器人学研究室
Source PublicationIEEE Transactions on Automation Science and Engineering
ISSN1545-5955
2021
Pages1-14
Indexed ByEI
EI Accession number20211310156920
Contribution Rank1
Funding OrganizationNational Natural Science Foundation of China under Grant U1813214, Grant 61821005, and Grant 61773369 ; China Postdoctoral Science Foundation under Grant 2019M661157
KeywordAssistive robotics exoskeletons, exosuit force control gait state human–robot interaction (HRI)
Abstract

Soft exoskeletons have demonstrated the potential to save energy, but their efficiency is sensitive to variations in human gait cadence. This work aims to develop adaptive gait state detection and iterative force control methods for a soft exoskeleton to reduce human walking metabolic cost consistently, while the user may change walking cadence. The proposed approach is motivated by the rhythmicity of gait and applies an iterative learning concept to enhance the exoskeleton's adaptability to varying walking conditions. The gait state detection method proposed for the designed exoskeleton combines two feature extraction algorithms, which can learn from the present and past body kinematic data, to provide accurate user gait state detection. Based on the state, the proposed force control method iteratively adjusts the commands to keep track of the desired profile. Experiments have been conducted on healthy subjects walking with varying cadence using the soft exoskeleton. Promising results were presented in separate validation tests. Moreover, metabolic costs of subjects walking under one unpowered and two powered conditions, where the assistance profiles were produced by classical methods and the proposed methods, showed that the proposed methods can effectively improve the exoskeleton's ability to save human energy of walking with varying cadence.

Language英语
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/28706
Collection机器人学研究室
Corresponding AuthorZhang B(张弼); Zhao YW(赵忆文)
Affiliation1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
2.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China
3.University of Chinese Academy of Sciences, Beijing 100049, China
4.Department of Aerospace Engineering, Ryerson University, Toronto, ON M5B 2K3, Canada
Recommended Citation
GB/T 7714
Tan XW,Zhang B,Liu GJ,et al. Cadence-Insensitive Soft Exoskeleton Design With Adaptive Gait State Detection and Iterative Force Control[J]. IEEE Transactions on Automation Science and Engineering,2021:1-14.
APA Tan XW,Zhang B,Liu GJ,Zhao XG,&Zhao YW.(2021).Cadence-Insensitive Soft Exoskeleton Design With Adaptive Gait State Detection and Iterative Force Control.IEEE Transactions on Automation Science and Engineering,1-14.
MLA Tan XW,et al."Cadence-Insensitive Soft Exoskeleton Design With Adaptive Gait State Detection and Iterative Force Control".IEEE Transactions on Automation Science and Engineering (2021):1-14.
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