Amy La Viers: Dancing with Robots: Expressivity in Natural and Artificial Systems

Movement seems to encode information. How does this work? We know that animals, including humans, use the motion of counterparts to produce coordinated, social behaviors. But how do we resolve the discrete measures of communication and information theory with the continuous laws of motion and mechanics? Answering these questions is critical to developing expressive robotic systems that integrate seamlessly with natural counterparts—a goal that has increasing urgency as robots move out of factories and into workplaces and homes.

This talk by Amy LaViers, an assistant professor of mechanical science and engineering at the University of Illinois at Urbana-Champaign and director of the Robotics, Automation, and Dance (RAD) Lab at UC Berkeley, presents this problem in an information-theoretic model and highlights how this model guides work in the RAD Lab. The talk will present work in generating bipedal gait that leverages qualitative observation, embodied movement practice, and artistic creation, highlighting how dancing with robots is critical to developing automation that functions correctly in human-built spaces.

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Presented by the Berkeley Center for New Media; cosponsored by UC Berkeley’s Department of Theater, Dance, and Performance Studies, and CITRIS People and Robots (CPAR).