2 research outputs found
A Reactive Competitive Emotion Selection System
We present a reactive emotion selection system designed to be used in a robot that needs to respond autonomously to relevant events. A variety of emotion selection models based on “cognitive appraisal” theories exist, but the complexity of the concepts used by most of these models limits their use in robotics. Robots have physical constrains that condition their understanding of the world and limit their capacity to built the complex concepts needed for such models. The system presented in this paper was conceived to respond to “disturbances” detected in the environment through a stream of images, and use this low-level information to update emotion intensities. They are increased when specific patterns, based on Tomkins’ affect theory, are detected or reduced when it is not. This system could also be used as part of (or as first step in the incremental design of) a more cognitively complex emotional system for autonomous robots
Affective Communication for Socially Assistive Robots (SARs) for Children with Autism Spectrum Disorder: A Systematic Review
Research on affective communication for socially assistive robots has been conducted to
enable physical robots to perceive, express, and respond emotionally. However, the use of affective
computing in social robots has been limited, especially when social robots are designed for children,
and especially those with autism spectrum disorder (ASD). Social robots are based on cognitiveaffective models, which allow them to communicate with people following social behaviors and
rules. However, interactions between a child and a robot may change or be different compared to
those with an adult or when the child has an emotional deficit. In this study, we systematically
reviewed studies related to computational models of emotions for children with ASD. We used the
Scopus, WoS, Springer, and IEEE-Xplore databases to answer different research questions related to
the definition, interaction, and design of computational models supported by theoretical psychology
approaches from 1997 to 2021. Our review found 46 articles; not all the studies considered children
or those with ASD.This research was funded by VRIEA-PUCV, grant number 039.358/202