Robotap: Tracking arbitrary points for few-shot visual imitation
For robots to be useful outside labs and specialized factories we need a way to teach them
new useful behaviors quickly. Current approaches lack either the generality to onboard new …
new useful behaviors quickly. Current approaches lack either the generality to onboard new …
Meta-learning regrasping strategies for physical-agnostic objects
Grasping inhomogeneous objects in real-world applications remains a challenging task due
to the unknown physical properties such as mass distribution and coefficient of friction. In …
to the unknown physical properties such as mass distribution and coefficient of friction. In …
Cycle-Correspondence Loss: Learning Dense View-Invariant Visual Features from Unlabeled and Unordered RGB Images
Robot manipulation relying on learned object-centric descriptors became popular in recent
years. Visual descriptors can easily describe manipulation task objectives, they can be …
years. Visual descriptors can easily describe manipulation task objectives, they can be …