Xin, S, Zhou, C orcid.org/0000-0002-6677-0855 and Tsagarakis, N (2019) New Cross-Step Enabled Configurations for Humanoid Robot. In: IEEE-RAS International Conference on Humanoid Robots. IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids), 06-09 Nov 2018, Beijing, China. IEEE , pp. 1067-1072. ISBN 9781538672839
Abstract
This paper explores two new configurations for humanoid robot balancing and locomotion. Centroidal momentum manipulability analysis has been performed to study the features of the newly proposed configurations. Numerical simulations show that they outperform the regular ones in terms of angular momentum manipulability. More than that, the new configurations allow the humanoid robot to perform cross-step motions which is usually risky or mechanically impossible for most existing robots. However, cross-step introduces non-convex feasible region which makes it difficult to be incorporated into our existing step planner. Therefore, a simple heuristic has been proposed to help choosing a sub-convex region for the step planner. To validate the cross-step movement, walking simulations have been performed.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2018 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. |
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 Jul 2019 12:52 |
Last Modified: | 05 Sep 2019 22:09 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/HUMANOIDS.2018.8624982 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:148950 |