Learning complex manipulation tasks in realistic, obstructed environment...
In this work we propose Pathfinder Discovery Networks (PDNs), a method f...
Deep reinforcement learning (RL) agents are able to learn contact-rich
m...
Constrained robot motion planning is a widely used technique to solve co...
Motion planning with constraints is an important part of many real-world...
We address the problem of planning robot motions in constrained configur...
The transfer of a robot skill between different geometric environments i...
Successful human-robot cooperation hinges on each agent's ability to pro...
Learning policies that generalize across multiple tasks is an important ...