Jevtić, A., Flores Valle, A., Alenyà, G. et al. (4 more authors) (2019) Personalized robot assistant for support in dressing. IEEE Transactions on Cognitive and Developmental Systems, 11 (3). pp. 363-374. ISSN 2379-8920
Abstract
Robot-assisted dressing is performed in close physical interaction with users who may have a wide range of physical characteristics and abilities. Design of user adaptive and personalized robots in this context is still indicating limited, or no consideration, of specific user-related issues. This paper describes the development of a multimodal robotic system for a specific dressing scenario-putting on a shoe, where users' personalized inputs contribute to a much improved task success rate. We have developed: 1) user tracking, gesture recognition, and posture recognition algorithms relying on images provided by a depth camera; 2) a shoe recognition algorithm from RGB and depth images; and 3) speech recognition and text-to-speech algorithms implemented to allow verbal interaction between the robot and user. The interaction is further enhanced by calibrated recognition of the users' pointing gestures and adjusted robot's shoe delivery position. A series of shoe fitting experiments have been performed on two groups of users, with and without previous robot personalization, to assess how it affects the interaction performance. Our results show that the shoe fitting task with the personalized robot is completed in shorter time, with a smaller number of user commands, and reduced workload.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2018 The Author(s). This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see http://creativecommons.org/licenses/by/4.0/ |
Keywords: | Assistive robots; multimodal human–robot interaction (HRI); robot personalization |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 24 Feb 2020 16:32 |
Last Modified: | 24 Feb 2020 16:38 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Refereed: | Yes |
Identification Number: | 10.1109/TCDS.2018.2817283 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:155658 |