Emotive response to a hybrid-face robot and translation to consumer social robots
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Accepted version
Accepted version
Author(s)
Type
Journal Article
Abstract
We present the conceptual formulation, design, fabrication, control and commercial translation of an IoT enabled social robot as mapped through validation of human emotional response to its affective interactions. The robot design centres on a humanoid hybrid-face that integrates a rigid faceplate with a digital display to simplify conveyance of complex facial movements while providing the impression of three-dimensional depth. We map the emotions of the robot to specific facial feature parameters, characterise recognisability of archetypical facial expressions, and introduce pupil dilation as an additional degree of freedom for emotion conveyance. Human interaction experiments demonstrate the ability to effectively convey emotion from the hybrid-robot face to humans. Conveyance is quantified by studying neurophysiological electroencephalography (EEG) response to perceived emotional information as well as through qualitative interviews. Results demonstrate core hybrid-face robotic expressions can be discriminated by humans (80%+ recognition) and invoke face-sensitive neurophysiological event-related potentials such as N170 and Vertex Positive Potentials in EEG. The hybrid-face robot concept has been modified, implemented, and released by Emotix Inc in the commercial IoT robotic platform Miko (‘My Companion’), an affective robot currently in use for human-robot interaction with children. We demonstrate that human EEG responses to Miko emotions are comparative to that of the hybrid-face robot validating design modifications implemented for large scale distribution. Finally, interviews show above 90% expression recognition rates in our commercial robot. We conclude that simplified hybrid-face abstraction conveys emotions effectively and enhances human-robot interaction.
Date Issued
2022-03-01
Date Acceptance
2021-06-30
Citation
IEEE Internet of Things Journal, 2022, 9 (5), pp.3174-3188
ISSN
2327-4662
Publisher
Institute of Electrical and Electronics Engineers
Start Page
3174
End Page
3188
Journal / Book Title
IEEE Internet of Things Journal
Volume
9
Issue
5
Copyright Statement
© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, 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 component of this work in other works.
Sponsor
Medical Research Council
Medical Research Council
Identifier
http://arxiv.org/abs/2012.04511v1
Grant Number
UKDRI-7002
UKDRI-7003
Subjects
cs.RO
cs.RO
Notes
This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible
Publication Status
Published
Date Publish Online
2021-07-15