Rhythmic Human-Robot Social Interaction

Abstract

Social scientists have identified and begun to describe rhythmic and synchronous properties of human social interaction. However, social interactions with robots are often stilted due to temporal mismatch between the behaviors, both verbal and nonverbal, of the interacting partners. This thesis brings the theory of interactional synchrony to bear on the design of social robots with a proposed architecture for rhythmic intelligence. We have developed technology that allows the robot Keepon to perceive social rhythms and to behave rhythmically. We have facilitated constrained social interactions, and designed experimental protocols, in which a robot variably synchronizes to human and/or environmental rhythms—first in a dance-oriented task, and second in a cooperative video game. We have analyzed these interactions to understand the effects of Keepon's rhythmic attention on human performance. This thesis demonstrates that variations in a robot's rhythmic behavior have measurable effects on human rhythmic behavior and on performance in rhythmic tasks. Furthermore, human participants were able to assume and transition between the roles of leader or follower in these tasks.