1 citations · 1 across the 3 of their papers we have counts for
3 papers
Equivariant Goal Conditioned Contrastive Reinforcement Learning
Arsh Tangri, Nichols Crawford Taylor, Haojie Huang +1
Contrastive Reinforcement Learning (CRL) provides a promising framework for extracting useful structured representations from unlabeled interactions. By pulling together state-acti…
Towards Assistive Robotic Pick and Place in Open World Environments
Dian Wang, Colin Kohler, Andreas ten Pas +4
Assistive robot manipulators must be able to autonomously pick and place a wide range of novel objects to be truly useful. However, current assistive robots lack this capability. A…
Adapting control policies from simulation to reality using a pairwise loss
Ulrich Viereck, Xingchao Peng, Kate Saenko +1
This paper proposes an approach to domain transfer based on a pairwise loss function that helps transfer control policies learned in simulation onto a real robot. We explore the id…