Facial Expression Generation Using Fuzzy Integral for Robotic Heads

This paper proposes a generation method of facial expressions using fuzzy measure and fuzzy integral for robotic heads. Human’s emotion state can be represented by a fuzzy measure which can effectively deal with ambiguity. Because facial expressions are usually ambiguous such that it is difficult to discern emotions and assign a sharp boundary to each emotion. In this method, users can adjust the personality of robot by assignign fuzzy measure to every set of emotions. The partial evaluation values of the current emotion state are obtained from a difference between the ideal basic emotion states and the current emotion state. The Choquet integral of the partial evaluation values with respect to the fuzzy measure is calculated to decide which emotion should occur. The effectiveness of the proposed method is demonstrated through computer simulations and experiments with a robotic head with 19 degrees of freedom, developed in RIT Lab., KAIST.