Individual difference of artificial emotion applied to a service robot

Abstract

In order to enable personalized natural interaction in service robots, artificial emotion is needed which helps robots to appear as individuals. In the emotion modeling theory of emotional Markov chain model (eMCM) for spontaneous transfer and emotional hidden Markov model (eHMM) for stimulated transfer, there are three problems: 1) Emotion distinguishing problem: whether adjusting parameters of the model have any effects on individual emotions; 2) How much effect the change makes; 3) The problem of different initial emotional states leading to different resultant emotions from a given stimuli. To solve these problems, a research method of individual emotional difference is proposed based on metric multidimensional scaling theory. Using a dissimilarity matrix, a scalar product matrix is calculated. Subsequently, an individual attribute reconstructing matrix can be obtained by principal component factor analysis. This can display individual emotion difference with low dimension. In addition, some mathematical proofs are carried out to explain experimental results. Synthesizing the results and proofs, corresponding conclusions are obtained. This new method provides guidance for the adjustment of parameters of emotion models in artificial emotion theory.

Keywords

artificial emotion / home service robot (HSR) / human-robot interaction (HRI) / individual emotion difference / metric multidimensional scaling

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Acknowledgements

This work was supported by the National High Technology Research and Development Program of China (2007AA04Z218), the National Natural Science Foundation of China (Grant No. 60903067), and the Beijing Key Discipline Development Program (XK100080537).

RIGHTS & PERMISSIONS

2014 Higher Education Press and Springer-Verlag Berlin Heidelberg