{"title":"A Control Strategy for Squat Assistance of Lower Limb Exoskeleton with Back Sensing","authors":"Jiaqi Wang, Dongmei Wu, W. Dong, Yongzhuo Gao","doi":"10.1109/ICMA54519.2022.9856343","DOIUrl":null,"url":null,"abstract":"While many challenges remain with respect to the mechanical design of the lower limb exoskeleton, it is equally challenging and important to develop effective control strategies. The exoskeleton is a highly human-robot coupled system with a complex dynamic model and working environment, so it is crucial that the controller works in concert with the user intention without relying on imprecise models. This paper proposes a motion controller for a lower limb exoskeleton, aiming to perform collaborative squatting assistance with efficiency and flexibility. This control strategy is designed for our exoskeleton which is equipped with a force sensor on the back. The high-level control is a force-velocity admittance model estimating the human intention by the interaction force, and the low-level control is based on PD closed-loop velocity control with gravity compensation. Through experimental studies conducted with our exoskeleton, the feasibility and effectiveness of the control strategy are demonstrated.","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMA54519.2022.9856343","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
While many challenges remain with respect to the mechanical design of the lower limb exoskeleton, it is equally challenging and important to develop effective control strategies. The exoskeleton is a highly human-robot coupled system with a complex dynamic model and working environment, so it is crucial that the controller works in concert with the user intention without relying on imprecise models. This paper proposes a motion controller for a lower limb exoskeleton, aiming to perform collaborative squatting assistance with efficiency and flexibility. This control strategy is designed for our exoskeleton which is equipped with a force sensor on the back. The high-level control is a force-velocity admittance model estimating the human intention by the interaction force, and the low-level control is based on PD closed-loop velocity control with gravity compensation. Through experimental studies conducted with our exoskeleton, the feasibility and effectiveness of the control strategy are demonstrated.