Scaling up Self Supervised Robot Learning

Newell Simon Hall 1507

Abstract Robot learning holds promise in alleviating several real world problems, by performing complex behaviors in complex environments. But what is the right way to train these robots? Our methods on self supervision shows encouraging results on several tasks like grasping objects, pushing objects and even flying drones. One key challenge with these methods is [...]

Bayesian Eigenobjects: A Unified Framework for 3D Robot Perception

GHC 6501

  Abstract: Robot-object interaction requires several key perceptual building blocks including object pose estimation, object classification, and partial-object completion. These tasks form the perceptual foundation for many higher level operations including object manipulation and world-state estimation. Most existing approaches to these problems in the context of 3D robot perception assume an existing database of objects [...]