Sun, L. orcid.org/0000-0002-0393-8665, Aragon-Camarasa, G., Rogers, S. et al. (1 more author) (2018) Autonomous clothes manipulation using a hierarchical vision architecture. IEEE Access, 6. pp. 76646-76662. ISSN 2169-3536
Abstract
This paper presents a novel robot vision architecture for perceiving generic 3-D clothes configurations. Our architecture is hierarchically structured, starting from low-level curvature features to mid-level geometric shapes and topology descriptions, and finally, high-level semantic surface descriptions. We demonstrate our robot vision architecture in a customized dual-arm industrial robot with our inhouse developed stereo vision system, carrying out autonomous grasping and dual-arm flattening. The experimental results show the effectiveness of the proposed dual-arm flattening using the stereo vision system compared with the single-arm flattening using the widely cited Kinect-like sensor as the baseline. In addition, the proposed grasping approach achieves satisfactory performance when grasping various kind of garments, verifying the capability of the proposed visual perception architecture to be adapted to more than one clothing manipulation tasks.
Metadata
Item Type: | Article |
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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 users, 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 components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy. |
Keywords: | Robot clothes manipulation; visual perception; garment flattening; garment grasping; dual-arm manipulation |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 16 Dec 2019 13:38 |
Last Modified: | 16 Dec 2019 13:41 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Refereed: | Yes |
Identification Number: | 10.1109/access.2018.2883072 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:154465 |