Robot's Emotion Generation Model with Personality and Loyalty based on Generalized Context Input Variables

摘要

For a friendly interaction between human and a robot,rnmany researchers have investigated the emotion generationrnmodel to naturalize the robot's emotion and to improve thernusability of the model for the designer of the robot. So inrnthis paper we used the hybrid emotion generationrnarchitecture, and defined the generalized context input ofrnemotion generation model for the designer to easilyrnimplement it to the robot. And we developed the personalityrnand loyalty model based on the psychology for variousrngeneration of emotion. Robot's personality is implementedrnwith the emotional stability from Big-Five, and loyalty isrnmade of familiarity generation, expression, and learningrnprocedure which are based on the human-human socialrnrelationship such as balance theory and social exchangerntheory. We verify this emotion generation model byrnimplementing it in the situation that the human and the robotrninteract for human's schedule management and a robotrncalling scenario.