17 citations · 18 across the 4 of their papers we have counts for
5 papers
Learning Fabric Manipulation in the Real World with Human Videos
Robert Lee, Jad Abou-Chakra, Fangyi Zhang +1
Fabric manipulation is a long-standing challenge in robotics due to the enormous state space and complex dynamics. Learning approaches stand out as promising for this domain as the…
Learning Arbitrary-Goal Fabric Folding with One Hour of Real Robot Experience
Robert Lee, Daniel Ward, Akansel Cosgun +3
Manipulating deformable objects, such as fabric, is a long standing problem in robotics, with state estimation and control posing a significant challenge for traditional methods. I…
Model-free vision-based shaping of deformable plastic materials
Andrea Cherubini, Valerio Ortenzi, Akansel Cosgun +2
We address the problem of shaping deformable plastic materials using non-prehensile actions. Shaping plastic objects is challenging, since they are difficult to model and to track…
Evaluating task-agnostic exploration for fixed-batch learning of arbitrary future tasks
Vibhavari Dasagi, Robert Lee, Jake Bruce +1
Deep reinforcement learning has been shown to solve challenging tasks where large amounts of training experience is available, usually obtained online while learning the task. Robo…
Sim-to-Real Transfer of Robot Learning with Variable Length Inputs
Vibhavari Dasagi, Robert Lee, Serena Mou +3
Current end-to-end deep Reinforcement Learning (RL) approaches require jointly learning perception, decision-making and low-level control from very sparse reward signals and high-d…