Fall 2023 GRASP SFI: Xiaolong Wang, University of California San Diego, “Generalizable Geometric Robot Learning”

This is a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom.

ABSTRACT

Robot learning has witnessed significant progress in terms of generalization recently, with the help of data-driven learning and image/text foundation models. While these achievements are encouraging, most tasks conducted in this context are relatively simple (e.g., pick-and-place with a parallel gripper). In this talk, I will talk about our recent efforts to learn generalizable skills focusing on tasks with rich physical contacts and geometric reasoning. Specifically, I will discuss our research on: (i) the use of a large number of low-cost, binary force sensors to enable Sim2Real manipulation; (ii) unifying 3D and semantic representation learning to generalize policy learning across diverse objects and scenes. I will showcase the real-world applications of our research, including dexterous manipulation, and legged locomotion control, and language-driven mobile manipulation.