Colloquium Details
Is Data All You Need? Large Robot Action Models and Good Old Fashioned Engineering
Speaker: Ken Goldberg
Location: 60 Fifth Avenue 150
Date: September 6, 2024, 11 a.m.
Host:
Synopsis:
2024 is off to an exciting start with enormous enthusiasm for humanoids and other robots based on recent advances in "end-to-end" large robot action models. Initial results are promising, and several collaborative efforts are underway to collect the needed demonstration data. But is data all you need?
I'll share my concerns about current trends in robot task definition, data collection, and experimental evaluation. I propose that to reach expected performance levels, we'll need "good old fashioned engineering" -- modularity, algorithms, and metrics. Like biological brains, which evolved to be modular rather than monolithic, we need systematic approaches to combine GOFE and learning. I'll present MANIP, a new framework that integrates engineering / modularity with learning, that we've applied to robot tasks such as cable untangling, surgical suturing, and bagging.
Speaker Bio:
Ken Goldberg is William S. Floyd Distinguished Chair of Engineering at UC Berkeley and Chief Scientist of Ambi Robotics and Jacobi Robotics. Ken leads research in robotics and automation: grasping, manipulation, and learning for applications in warehouses, industry, homes, agriculture, and robot-assisted surgery. He is Professor of IEOR with appointments in EECS and Art Practice. Ken is Chair of the Berkeley AI Research (BAIR) Steering Committee (60 faculty) and is co-founder and Editor-in-Chief emeritus of the IEEE Transactions on Automation Science and Engineering (T-ASE). He has published ten US patents, over 400 refereed papers, and presented over 600 invited lectures to academic and corporate audiences.
Notes:
In-person attendance only available to those with active NYU ID cards.