When: Wednesday, April 13th at 15:00
Talk Abstract The questions of dexterity, agility, and learning from a few demonstrations have intrigued robotics researchers. In this talk, I will explore answers and solutions to these questions via the following case studies: (i) a dexterous manipulation system capable of re-orienting novel objects. (ii) a quadruped robot that is substantially more agile than its counterparts (runs, spins) on challenging natural terrains. (iii) framework for learning task-sensitive perceptual representations for planning and out-of-distribution generalization. While a lot of recent progress in robotics is driven by perception, we show that learned controllers can help address problems that were previously thought to be hard. I will discuss our findings, the insights we gained, and the road ahead.