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Human emotional understanding for empathetic companion robots

Version 2 2024-06-05, 00:19
Version 1 2018-08-02, 13:35
conference contribution
posted on 2024-06-05, 00:19 authored by AD May, A Lotfi, C Langensiepen, Kevin LeeKevin Lee, G Acampora
Companion robots are becoming more common in home environments, as such a greater emphasis is required on analysis of human behaviour. An important aspect of human behaviour is emotion, both the ability to express and comprehend. While humans have developed excellent skills in inferring the emotional states of their counterparts via implicit cues such as facial expression and body language, this level of understanding is often neglected in Human Robot Interactions; furthermore, humans are able to empathetically respond to the emotions of others to create amore harmonious and person relationship. This paper is a preliminary proposal of a novel approach for facial emotional detection and appropriate empathetic responses, in conjunction with long term emotion mapping and prediction; the proposed system will be implemented on a social mobile robot, thus allowing a further level of behavioural comprehension to achieve a more human like encounter. The technique will be based on Fuzzy Cognitive Maps, using FACS Action Units as inputs, a high level facial descriptor layer and output of six emotions.

History

Volume

513

Pagination

277-285

Location

Lancaster, Eng.

Start date

2016-09-07

End date

2016-09-09

ISSN

2194-5357

ISBN-13

9783319465616

Language

eng

Publication classification

E Conference publication, E1.1 Full written paper - refereed

Copyright notice

2017, Springer International Publishing AG

Editor/Contributor(s)

Angelov P, Gegov A, Jayne C, Shen Q

Title of proceedings

Advances in Computational Intelligence Systems : Proceedings of the 16th UK Workshop on Computational Intelligence 2016

Event

Computational Intelligence Systems. Workshop (16th : 2016 : Lancaster, Eng.)

Publisher

Springer

Place of publication

Cham, Switzerland

Series

Computational Intelligence Systems Workshop