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CASIE– Computing affect and social intelligence for healthcare in an ethical and trustworthy manner

Caputo, Annalina ORCID: 0000-0002-7144-8545, Vasiliu, Laurentiu, Cortis, Keith ORCID: 0000-0002-9748-0340, McDermott, Ross, Kerr, Aphra ORCID: 0000-0001-5445-7805, Peters, Arne ORCID: 0000-0002-0620-3154, Hesse, Marc ORCID: 0000-0002-9500-3284, Hagemeyer, Jens, Belpaeme, Tony ORCID: 0000-0001-5207-7745, McDonald, John, Villing, Rudi, Mileo, Alessandra ORCID: 0000-0002-6614-6462, Scriney, Michael ORCID: 0000-0001-6813-2630, Griffiths, Sascha ORCID: 0000-0003-2696-4855, Koumpis, Adamantios ORCID: 0000-0003-2661-7749 and Davis, Brian ORCID: 0000-0002-5759-2655 (2021) CASIE– Computing affect and social intelligence for healthcare in an ethical and trustworthy manner. Journal of Behavioral Robotics, 12 . pp. 437-453. ISSN 2080-9778

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Abstract

This article explores the rapidly advancing innovation to endow robots with social intelligence capabilities in the form of multilingual and multimodal emotion recognition, and emotion-aware decision-making capabilities, for contextually appropriate robot behaviours and cooperative social human–robot interaction for the healthcare domain. The objective is to enable robots to become trustworthy and versatile social robots capable of having human-friendly and human assistive interactions, utilised to better assist human users’ needs by enabling the robot to sense, adapt, and respond appropriately to their requirements while taking into consideration their wider affective, motivational states, and behaviour. We propose an innovative approach to the difficult research challenge of endowing robots with social intelligence capabilities for human assistive interactions, going beyond the conventional robotic sense-think-act loop. We propose an architecture that addresses a wide range of social cooperation skills and features required for real human–robot social interaction, which includes language and vision analysis, dynamic emotional analysis (long-term affect and mood), semantic mapping to improve the robot’s knowledge of the local context, situational knowledge representation, and emotion-aware decision-making. Fundamental to this architecture is a normative ethical and social framework adapted to the specific challenges of robots engaging with caregivers and care-receivers.

Item Type:Article (Published)
Refereed:Yes
Uncontrolled Keywords:social human–robot interaction; sHRI; computing affect; emotion analysis; healthcare robots; robot assisted care; robot ethics
Subjects:UNSPECIFIED
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Initiatives and Centres > Lero: The Irish Software Engineering Research Centre
Research Initiatives and Centres > INSIGHT Centre for Data Analytics
Research Initiatives and Centres > ADAPT
Publisher:De Gruyter Open
Official URL:https://dx.doi.org/10.1515/pjbr-2021-0026
Copyright Information:© 2019 The Authors. Open Access (CC-BY 4.0)
Funders:Science Foundation Ireland Grant 13/RC/2094 and co-funded under the European Regional Development Fund through the Southern and Eastern Regional Operational Programme to Lero, Insight Centre for Data Analytics which is funded by Science Foundation Ireland (SFI/12/RC/2289 P2), ADAPT Centre for Digital Content Technology under the Science Foundation Ireland Research Centres Programme (Grant 13/RC/2106).
ID Code:27601
Deposited On:22 Aug 2022 12:26 by Thomas Murtagh . Last Modified 13 Oct 2022 12:13

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