Events Calendar

CS Colloquium: Sergey Levine (UC Berkeley) - Learning to Move: Machine Learning for Robotics and Animation

Speaker: Sergey Levine , UC Berkeley

Talk Title: Learning to Move: Machine Learning for Robotics and Animation

Series: CS Colloquium

Abstract: Being able to acquire new motion skills autonomously could help robots build rich motion repertoires suitable for tackling complex, varied environments. I will discuss my work on motion skill learning for robotics, including methods for learning from demonstration and reinforcement learning. In particular, I will describe a class of "guided" policy search algorithms, which combine reinforcement learning and learning from demonstration to acquire multiple simple, trajectory-centric policies, with a supervised learning phase to obtain a single complex, high-dimensional policy that can then generalize to new situations. I will show applications of this method to simulated bipedal locomotion, as well as a range of robotic manipulation tasks, including putting together two parts of a plastic toy and screwing bottle caps onto bottles. I will also discuss how such techniques can be applied to character animation in computer graphics, and how this field can inform research in robotics.

Biography: Sergey Levine is a postdoctoral researcher working with Professor Pieter Abbeel at the University of California at Berkeley. He previously completed his PhD with Professor Vladlen Koltun at Stanford University. His research areas include robotics, reinforcement learning and optimal control, machine learning, and computer graphics. His work includes the development of new algorithms for learning motor skills, methods for learning behaviors from human demonstration, and applications in robotics and computer graphics, ranging from robotic manipulation to animation of martial arts and conversational hand gestures.

Host: Fei Sha

Location: Henry Salvatori Computer Science Center (SAL) - 101

Audiences: Everyone Is Invited

Contact: Assistant to CS chair