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SUMMARY:Fall 2022 GRASP SFI: Zhongyu Li\, University of California Berkeley\, “Can We Bridge Model-based Control and Model-free RL on Legged Robots?”
DESCRIPTION:*This will be a HYBRID Event with in-person attendance in Levine 307 and Virtual attendance via Zoom. \nIn this talk\, I will provide a brief introduction about our recent progress in applying optimal control and deep reinforcement learning (RL) on legged robots in the real world. I will then dive into our recent work to bridge model-based safety-critical control and model-free RL on a highly nonlinear and complex system\, such as a bipedal robot Cassie. Bridging model-based safety and model-free RL for dynamic robots is appealing since model-based methods are able to provide formal safety guarantees\, while RL-based methods are able to exploit the robot agility by learning from the full-order system dynamics. I will discuss a new method to combine them by explicitly finding a low-dimensional model of the system controlled by a RL policy and applying stability and safety guarantees on that simple model. \n 
URL:https://seasevents.nmsdev7.com/event/fall-2022-grasp-sfi-zhongyu-li-university-of-california-berkeley-can-we-bridge-model-based-control-and-model-free-rl-on-legged-robots/
LOCATION:Room 307\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ORGANIZER;CN="General Robotics%2C Automation%2C Sensing and Perception (GRASP) Lab":MAILTO:grasplab@seas.upenn.edu
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