Martinez-Hernandez, U. orcid.org/0000-0002-9922-7912, Firouzy, S., Mehryar, P. et al. (4 more authors) (Cover date: March 2023) Human-in-the-loop layered architecture for control of a wearable ankle–foot robot. Robotics and Autonomous Systems, 161. 104353. ISSN 0921-8890
Abstract
Intelligent wearable robotics is a promising approach for the development of devices that can interact with people and assist them in daily activities. This work presents a novel human-in-the-loop layered architecture to control a wearable robot while interacting with the human body. The proposed control architecture is composed of high-, mid- and low-level computational and control layers, together with wearable sensors, for the control of a wearable ankle–foot robot. The high-level layer uses Bayesian formulation and a competing accumulator model to estimate the human posture during the gait cycle. The mid-level layer implements a Finite State Machine (FSM) to prepare the control parameters for the wearable robot based on the decisions from the high-level layer. The low-level layer is responsible for the precise control of the wearable robot over time using a cascade proportional–integral–derivative (PID) control approach. The human-in-the-loop layered architecture is systematically validated with the control of a 3D printed wearable ankle–foot robot to assist the human foot while walking. The assistance is applied lifting up the human foot when the toe-off event is detected in the walking cycle, and the assistance is removed allowing the human foot to move down and contact the ground when the heel-contact event is detected. Overall, the experiments in offline and real-time modes, undertaken for the validation process, show the potential of the human-in-the-loop layered architecture to develop intelligent wearable robots capable of making decisions and responding fast and accurately based on the interaction with the human body.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/) |
Keywords: | Layered architectures; Autonomous systems; Bayesian inference; Sensorimotor control |
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) |
Depositing User: | Symplectic Publications |
Date Deposited: | 25 Aug 2023 10:08 |
Last Modified: | 25 Aug 2023 10:08 |
Published Version: | https://www.sciencedirect.com/science/article/pii/... |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.robot.2022.104353 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:202444 |
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