An Approach to the Synthesis of Humanoid Robot Dance Using Non-interactive Evolutionary Techniques

After bipedal locomotion, dance is one of the most commonly studied behaviours for researchers seeking to replicate human-like motion in humanoid robots. Many of the methods employed involve direct interaction with, or imitation of, human participant(s). For example, the generation of dance movements using interactive evolutionary computation (IEC) involves the replacement of an objective fitness function with the subjective evaluations of human observer(s). In this paper we present an alternative approach to the synthesis of humanoid robot dance using non-interactive evolutionary computation (non-IEC) methods. We propose a novel fitness function for the evolution of robotic dance, and we present initial results of the application of this evolutionary process to the generation of dance patterns for the 18-DOF Bioloid humanoid robot. We conclude that even without the presence of a human or humans in the evolutionary loop, it is possible to produce surprisingly lifelike and novel dances using this approach.