Emotion Expression of Robot with Personality

Abstract

A robot emotional expression model based on Hidden Markov Model (HMM) is built to enable robots which have different personalities to response in a more satisfactory emotional level. Gross emotion regulation theory and Five Factors Model (FFM) which are the theoretical basis are firstly described. And then the importance of the personality effect on the emotion expression process is proposed, and how to make the effect quantization is discussed. After that, the algorithm of HMM is used to describe the process of emotional state transition and expression, and the performance transferring probability affected by personality is calculated. At last, the algorithm model is simulated and applied in a robot platform. The results prove that the emotional expression model can acquire humanlike expressions and improve the human-computer interaction.