Modeling of honest signals for human robot interaction

Abstract

Recent studies have shown that human beings unconsciously use signals that represent their thoughts and/or intentions when communicating with each other. These signals are known as “honest signals.” This study involves the use of a sociometer to capture multimodal data resulting from the interaction between humans. These data are then used to model the interaction using a multimodal hierarchical Dirichlet process hidden Markov model, which is then implemented in the robot. The model enables robots to generate “honest signals” and to interact in a natural manner.