Enhancing interaction through exaggerated motion synthesis

Other than eye gaze and referential gestures (e.g. pointing), the relationship between robot motion and observer attention is not well understood. We explore this relationship to achieve social goals, such as influencing human partner behavior or directing attention. We present an algorithm that creates exaggerated variants of a motion in real-time. Through two experiments we confirm that exaggerated motion is perceptibly different than the input motion, provided that the motion is sufficiently exaggerated. We found that different levels of exaggeration correlate to human expectations of robot-like, human-like, and cartoon-like motion. We present empirical evidence that use of exaggerated motion in experiments enhances the interaction through the benefits of increased engagement and perceived entertainment value. Finally, we provide statistical evidence that exaggerated motion causes predictable human partner gaze direction and better retention of interaction details.