Towards A Framework For Dancing Beyond Demonstration

Abstract

This paper presents a prototype framework for developing real-time human-robot performances and its application within a recent choreographic work for the stage. The framework allows dancers to teach new motions to robots, while also giving choreographers the ability to compose performances from pre-built and learned behaviors. To achieve this capability, we combine behavior-based robotics and learning from demonstration approaches to construct behaviors and compose them into a performance. Our learning algorithm, dancing-from-demonstration (DfD), allows dancers and choreographers to teach new phrases to the robot and specify choreographic motifs for the performance. This collaborative work culminated in a human-robot duet, where the robot incorporates a new, learned motion into its choreography within live performance. These capabilities create a baseline for choreographers and dancers to eventually compose and perform in more dynamic, reactive choreo-robotic performances.