Several of Rethink’s Sawyer robotics are crammed into a small corner of a lab at UC Berkeley’s Sutardja Dai Hall. The industrial robotic arms are separated by a makeshift scaffold. It’s a bit of a tight squeeze as we set up to watch the first of two demos, each taking a distinctly different approach to a similar goal: teaching robots to learn how to learn.
End the final.
The team walks us through a pair of demos to showcase how it’s thinking about robotics learning. The first, “Deep Visual Foresight for Planning Robot Motion,” is designed to help robots collect their own data without direct human supervision.
After all, these sorts of training exercises often require robots to execute tens of thousands of sequences or more, in order to have a sufficient database. That means running a robot overnight for days on end — precisely the sort of repetitive task these sorts of industrial robots are designed to replace.