Prescott, T.J. orcid.org/0000-0003-4927-5390, Mitchinson, B., Conran, S. et al. (2 more authors)
(2018)
MiRo: Social Interaction and Cognition in an Animal-like Companion Robot.
In:
Proceeding HRI '18 Companion of the 2018 ACM/IEEE International Conference on Human-Robot Interaction.
The 13th Annual ACM/IEEE International Conference on Human Robot Interaction, 05-08 Mar 2018, Chicago, IL, USA.
ACM
, p. 41.
ISBN 9781450356152
Abstract
Future companion and assistive robots will interact directly with end-users in their own homes over extended periods of time. To be useful, and remain engaging over the long-term, these technologies need to pass a new threshold in social robotics-to be aware of people, their identities, emotions and intentions and to adapt their behavior to different individuals. Our immediate goal is to match the social cognition ability of companion animals who recognize people and their intentions without linguistic communication. The MiRo robot is a pet-sized mobile platform, with a brain-based control system and an emotionally-engaging appearance, which is being developed for research on companion robotics, and for applications in education, assistive living and robot-assisted therapy. This paper describes new MiRo capabilities for animal-like perception and social cognition that support the adaptation of behavior towards people and other robots.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2018 ACM. This is an author produced version of a paper subsequently published in Proceeding HRI '18 Companion of the 2018 ACM/IEEE International Conference on Human-Robot Interaction. Uploaded in accordance with the publisher's self-archiving policy. |
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: | 15 May 2018 13:47 |
Last Modified: | 19 Dec 2022 13:49 |
Published Version: | https://doi.org/10.1145/3173386.3177844 |
Status: | Published |
Publisher: | ACM |
Refereed: | Yes |
Identification Number: | 10.1145/3173386.3177844 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:130855 |