Mood-transition-based emotion generation model for the robot´s personality

Recently, as the relationship between robot and human has become closer, humans demand that robots pose familiar human-like characteristics. For a robot to live and communicate with people, it requires its own personality or individuality. Changing the mood transition of robots can change the perceptions people have of their characteristics. We propose an emotion generation model that represents a robot´s internal state. This model can assess the robot´s individuality through mood transitions. We report experiments of emotional conversation with a robot that had this model installed. The experimental results showed that personality could be effectively expressed by changing robot´s mood transitions. We also report significant results of evaluations of psychological impact.