Real-Time Dance Generation to Music for a Legged Robot

The development of robots that can dance has received considerable attention. However, they are often either limited to a pre-defined set of movements and music or demonstrate little variance when reacting to external stimuli, such as microphone or camera input. In this paper, we contribute with a novel approach allowing a legged robot to listen to live music while dancing in synchronization with the music in a diverse fashion. This is achieved by extracting the beat from an onboard microphone in real-time, and subsequently creating a dance choreography by picking from a user-generated dance motion library at every new beat. Dance motions include various stepping and base motions. The process of picking from the library is defined by a probabilistic model, namely a Markov chain, that depends on the previously picked dance motion and the current music tempo. Finally, delays are determined online by time-shifting a measured signal and a reference signal, and minimizing the least squares error with the time-shift as parameter. Delays are then compensated for by using a combined feedforward and feedback delay controller which shifts the robot whole-body controller reference input in time. Results from experiments on a quadrupedal robot demonstrate the fast convergence and synchrony to the perceived music