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SUMMARY:Fall 2024 GRASP SFI: Dian Wang\, Northeastern University\, “Equivariant Learning for Robotic Manipulation”
DESCRIPTION:This will be a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom. \nABSTRACT\nDespite recent advances in machine learning for robotics\, current approaches often lack sample efficiency\, posing a significant challenge due to the enormous time consumption to collect real-robot data. In this talk\, I will present our innovative methods that tackle this challenge by leveraging the inherent symmetries in the physical environment. Specifically\, I will outline a comprehensive framework of equivariant policy learning and its application across various problem settings\, including reinforcement learning\, behavior cloning\, and grasping. Our methods not only significantly outperform state-of-the-art baselines but also achieve these results with far less data\, both in simulation and in real-world scenarios. Furthermore\, our approach demonstrates robustness in the presence of symmetry distortions\, such as variations in camera angles.
URL:https://seasevents.nmsdev7.com/event/fall-2024-grasp-sfi-dian-wang/
LOCATION:Levine 307\, 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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