Real-Time Changes To Social Dynamics In Human-Robot Turn-Taking

In order for robots to work alongside humans in a range of domains, they will need to operate with a variety of social dynamics that each context will require. This paper builds on previous work with a parameterized turn-taking model, CADENCE, in which different parameter settings resulted in different social dynamics. In contrast to the static parameter settings of previous work, we now investigate the problem of changing these turn-taking parameter sets dynamically within a single interaction session. This ability is necessary for successful peer-to-peer collaborations, in which balance of control between leading and following must be maintained. We present our dynamic switching approach and an experiment with 15 participants. Our results confirm that it is possible to achieve the same changes in social dynamics within a single interaction session that were previously seen only between independent sessions of different parameter settings. Moreover, we show that such a change in social dynamics is contingent upon changing parameters at socially appropriate turn boundaries.