Autonomous robot dancing driven by beats and emotions of music

Abstract

Many robot dances are preprogrammed by choreographers for a particular piece of music so that the motions can be smoothly executed and synchronized to the music. We are interested in automating the task of robot dance choreography to allow robots to dance without detailed human planning. Robot dance movements are synchronized to the beats and reflect the emotion of any music. Our work is made up of two parts: (1) The first algorithm plans a sequence of dance movements that is driven by the beats and the emotions detected through the preprocessing of selected dance music. (2) We also contribute a real-time synchronizing algorithm to minimize the error between the execution of the motions and the plan. Our work builds on previous research to extract beats and emotions from music audio. We created a library of parameterized motion primitives, whereby each motion primitive is composed of a set of keyframes and durations and generate the sequence of dance movements from this library. We demonstrate the feasibility of our algorithms on the NAO humanoid robot to show that the robot is capable of using the mappings defined to autonomously dance to any music. Although we present our work using a humanoid robot, our algorithm is applicable to other robots.