Xu, P, Wang, Z, Ding, L et al. (5 more authors) (2023) A Closed-Loop Shared Control Framework for Legged Robots. IEEE/ASME Transactions on Mechatronics. ISSN 1083-4435
Abstract
Shared control, as a combination of human and robot intelligence, has been deemed as a promising direction toward complementing the perception and learning capabilities of legged robots. However, previous works on human–robot control for legged robots are often limited to simple tasks, such as controlling movement direction, posture, or single-leg motion, yet extensive training of the operator is required. To facilitate the transfer of human intelligence to legged robots in unstructured environments, this article presents a user-friendly closed-loop shared control framework. The main novelty is that the operator only needs to make decisions based on the recommendations of the autonomous algorithm, without having to worry about operations or consider contact planning issues. Specifically, a rough navigation path from the operator is smoothed and optimized to generate a path with reduced traversing cost. The traversability of the generated path is assessed using fast Monte Carlo tree search, which is subsequently fed back through an intuitive image interface and force feedback to help the operator make decisions quickly, forming a closed-loop shared control. The simulation and hardware experiments on a hexapod robot show that the proposed framework gives full play to the advantages of human–machine collaboration and improves the performance in terms of learning time from the operator, mission completion time, and success rate than comparison methods.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Keywords: | Robots; Legged locomotion; Robot kinematics; Costs; Robot sensing systems; Planning; Collision avoidance |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 23 May 2023 14:42 |
Last Modified: | 24 May 2023 02:42 |
Published Version: | http://dx.doi.org/10.1109/tmech.2023.3270527 |
Status: | Published online |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Identification Number: | 10.1109/tmech.2023.3270527 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:199281 |