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

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.