Plan What You Can, Learn What You Must: Interleaving Planning and Learning for Multi-Robot Manipulation
Abstract: Multi-robot manipulation is becoming an inevitability of modern robotics. As hardware costs fall, the barrier to deploying robot teams has shifted from economics to algorithmic capability. To fulfill their promise, multi-robot systems must jointly reason about geometric coordination, contact interactions, task assignments, and scene dynamics, while adapting to variable team sizes and diverse robot [...]
To Be Announced
Robot Learning, With Inspiration From Child Development
Abstract: For intelligent robots to become ubiquitous, we need to “solve" locomotion, navigation and manipulation at sufficient reliability in widely varying environments. In locomotion, we now have demonstrations of humanoid walking in a variety of challenging environments. In navigation, we pursued the task of “Go to Any Thing” – a robot, on entering a newly [...]
