Kanoulas, D, Zhou, C orcid.org/0000-0002-6677-0855, Nguyen, A et al. (3 more authors) (2018) Vision-based foothold contact reasoning using curved surface patches. In: 2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids). 2017 IEEE-RAS, 15-17 Nov 2017, Birmingham, UK. IEEE , pp. 121-128. ISBN 978-1-5386-4678-6
Abstract
Reasoning about contacts between a legged robot's foot and the ground is a critical aspect of locomotion in natural terrains. This interaction becomes even more critical when the robot must move on rough surfaces. This paper presents a new visual contact analysis, based on curved patches that model local contact surfaces both on the sole of the robot's foot and in the terrain. The focus is on rigid, flat feet that represent the majority of the designs for current humanoids, but we also show how the introduced framework could be extended to other foot profiles, such as spherical feet. The footholds are localized visually in the environment's point cloud through a fast patch fitting process and a contact analysis between patches on the sole of the foot and in the surrounding environment. These patches aim to compose a spatial patch map for contact reasoning. We experimentally validate the introduced visionbased framework, using range data for rough terrain stepping demonstrations on the COMAN and WALK-MAN humanoids.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2017 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: | Foot; Cognition; Legged locomotion; Robot kinematics; Rough surfaces; Surface roughness |
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 13:51 |
Last Modified: | 04 Apr 2019 13:51 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/HUMANOIDS.2017.8239546 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:144460 |