HMM-based Error Recovery of Dance Step Selection for Dance Partner Robot

Abstract

A dance partner robot has been developed as an example of platforms for realizing the effective human-robot coordination with physical interactions. This robot could dance together with a human by estimating the next step intended by the human. If the robot would mistake the step estimation, the human-robot coordination could not be continued. In this paper, an error recovery method for step selections, which changes robot's behavior according to human's behavior, is designed using hidden Markov models. Experimental results illustrate the validity of the proposed method.