Zhou, C orcid.org/0000-0002-6677-0855, Wang, X, Li, Z et al. (1 more author) (2017) Overview of Gait Synthesis for the Humanoid COMAN. Journal of Bionic Engineering, 14 (1). pp. 15-25. ISSN 1672-6529
Abstract
This paper focuses on the developments of a generic gait synthesis for the humanoid robot COMAN. Relying on the essential Gait Pattern Generator (GPG), the proposed synthesis offers enhanced versatilities for the locomotion under different purposes, and also provides the data storage and communication mechanisms among different modules. As an outcome, we are able to augment new abilities for COMAN by integrating new control modules and software tools at a cost of very few modifications. Moreover, foot placement optimization is introduced to the GPG to optimize the gait parameter references in order to meet the robot’s natural dynamics and kinematics, which enhances the synthesis’s robustness while it’s being implemented on real robots. We have also presented a practical approach to generate pelvis motion from CoM references using a simplified three-point-mass model, as well as a straightforward but effective idea for the state estimation using the sensory feedback. Three physical experiments were studied in an increasing complexity to demonstrate the effectiveness and successful implementation of the proposed gait synthesis on a real humanoid system.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © Jilin University 2017. This is a post-peer-review, pre-copyedit version of an article published in Journal of Bionic Engineering. The final authenticated version is available online at: https://doi.org/10.1016/S1672-6529(16)60373-6 |
Keywords: | humanoid robots; bipedal locomotion; gait synthesis; dynamic walking |
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: | 04 Apr 2019 12:15 |
Last Modified: | 01 May 2020 03:03 |
Status: | Published |
Publisher: | Springer Singapore |
Identification Number: | 10.1016/S1672-6529(16)60373-6 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:144455 |