Ghaffar, A. orcid.org/0000-0001-9184-1865, Dehghani-Sanij, A.A., Xie, S.Q. orcid.org/0000-0002-8082-9112 et al. (2 more authors) (2023) Design optimization and redundant actuation selection for an efficient assistive robotic exoskeleton. Journal of the Chinese Institute of Engineers, 46 (5). pp. 490-503. ISSN 0253-3839
Abstract
Selection of an actuation system for assistive robotic exoskeletons requires careful consideration of various design factors. It is generally the requirement of the system to produce lightweight and power-efficient systems. In some cases, the torque and power requirements could be relaxed by using redundant systems. This paper involves the study of one such case in which the actuation redundancy of the system will be exploited, and the design optimization will be explored for a rigid and an elastic system. A multi-factor optimization technique will be developed for a redundant elastic actuation system. An actuator design framework will be used to evaluate the different actuator choices to determine the best motor and transmission system combination in a redundant actuation system arrangement. This will be evaluated for a rigid, parallel, and series elastic actuation system. The optimal redundant actuation system significantly reduced the power requirements of the system. The case study was virtually implemented. It was established that variable parallel elastic actuators (V-PEA) performed better as compared to variable series elastic actuators (V-SEA).
Metadata
Item Type: | Article |
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Authors/Creators: |
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Keywords: | Wearable robots; exoskeletons; actuation redundancy; elastic actuators |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mechanical Engineering (Leeds) > Institute of Engineering Systems and Design (iESD) (Leeds) The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Robotics, Autonomous Systems & Sensing (Leeds) |
Funding Information: | Funder Grant number EPSRC (Engineering and Physical Sciences Research Council) EP/S019219/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 25 Oct 2023 09:18 |
Last Modified: | 08 Nov 2023 11:30 |
Published Version: | https://www.tandfonline.com/doi/full/10.1080/02533... |
Status: | Published |
Publisher: | Taylor & Francis |
Identification Number: | 10.1080/02533839.2023.2204894 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:202446 |