Adaptive Tracking Control of a Virtual Player in the Mirror Game

The coordination of interpersonal rhythmic movements is of great significance due to its potential relevance to human motor rehabilitation. In this paper we consider the problem of designing a controller able to drive a virtual player (VP) capable of imitating and following a human player in the mirror game [1]. The classic nonlinear Haken-Kelso-Bunz (HKB) model is adopted to describe the social motor coordination between two players. An adaptive control algorithm is developed and implemented on the HKB model to drive the VP. It is proven that the position error between the VP driven by our control algorithm and the human player is upper bounded during the game. Finally, experiments are conducted on a prototype set-up in order to evaluate the performance of the proposed control algorithm and compare it with other existing algorithms.