Mismatched partners in human-robot interaction: biomimetic insights on aligning internal states with external expressions

Huang, G., Chen, C. and Moore, R.K. orcid.org/0000-0003-0065-3311 (2026) Mismatched partners in human-robot interaction: biomimetic insights on aligning internal states with external expressions. In: Rodríguez, A.J., Mestre, R., Chen, C., Mura, A., Barker, E., Verschure, P. and Prescott, T., (eds.) Biomimetic and Biohybrid Systems. Living Machines 2025, 14th International Conference on Biomimetic and Biohybrid Systems, 15-18 Jul 2025, Sheffield, United Kingdom. Lecture Notes in Computer Science, 15582. Springer Nature Switzerland, pp. 366-373. ISBN: 9783032074478. ISSN: 0302-9743. EISSN: 1611-3349.

Abstract

Metadata

Item Type: Proceedings Paper
Authors/Creators:
Editors:
  • Rodríguez, A.J.
  • Mestre, R.
  • Chen, C.
  • Mura, A.
  • Barker, E.
  • Verschure, P.
  • Prescott, T.
Copyright, Publisher and Additional Information:

© 2026 The Author(s). Except as otherwise noted, this author-accepted version of a proceedings paper published in Biomimetic and Biohybrid Systems is made available via the University of Sheffield Research Publications and Copyright Policy under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/

Keywords: human-robot interaction; social robotics; affordance design; interaction design; theoretical framework
Dates:
  • Published (online): 25 November 2025
  • Published: 2026
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield)
Date Deposited: 30 Jan 2026 09:23
Last Modified: 30 Jan 2026 09:27
Status: Published
Publisher: Springer Nature Switzerland
Series Name: Lecture Notes in Computer Science
Refereed: Yes
Identification Number: 10.1007/978-3-032-07448-5_31
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Open Archives Initiative ID (OAI ID):

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