Ep#114: Oopsie Data

Robotics has a data problem, but not the one you’re thinking of: almost all robotics data is of successful instances of robot behaviors. But many of the most exciting research areas for robotics today, including world models and reward model learning, require failures: interesting examples of manipulation trajectories that did not succeed. Claas Voelcker, Arpit Bahety, and Paul Zhou join us to talk about their data collection effort and their upcoming workshop on “oopsie data”: all these valuable failures that are currently being thrown out. Their goal is to collect the first large community-driven open-source dataset of failure examples. Watch Episode 114 of RoboPapers, with Chris Paxton and Jiafei Duan, to learn more! Learn More Project site: https://oopsie-data.com/ This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit robopapers.substack.com