Multi-Point Mapping of Dancer Aesthetic Movements Onto a Robotic Arm

Dance and robotics share the investigation field of motion of articulated kinematic chains for aesthetic and practical proposes, respectively. The first researches the gracefulness of movements of the performer’s body to express emotion and captivate audiences, while the latter focuses on planning and controlling the motion of mechanical systems to complete pragmatic tasks. However, in recent years, even more and more robots have stepped on stages together with artists and dancers with the aim of enchanting the spectators with original and groundbreaking choreographies. In this study, we propose an approach to combine the graceful motion of a dancer with autonomous trajectory planning for an articulated arm in unique human-robot choreographies (HRCs). The expressiveness of dance and the posture of dancers are rendered in a robotic manipulator, mapping i) the most involved dancer limb and ii) the human center of gravity. The simultaneous mapping of these two points is achieved by exploiting the kinematic kernel of the redundant robot, by which it is possible to mime the dancer’s posture while the end-effector follows the limb movements. In this way, we developed an autonomous human-to-robot mapping method for aesthetic purposes that balances dance expressiveness and dancer posture. To validate the proposed method, we compared robot control performance and movement coherence with human-originating dances against robot movements obtained by tracking single points. Additionally, the effects of the multi-point projection on the audience experience were evaluated in an experimental campaign involving 30 participants. Their feedback confirmed the paramount of using the human centroid and end limb to represent human posture and dance nuances, respectively, and the positive impact of simultaneous mapping of these points on the audience’s experience.