2 papers
cs.RO2024
Dynamic Non-Prehensile Object Transport via Model-Predictive Reinforcement Learning
Neel Jawale, Byron Boots, Balakumar Sundaralingam +1
We investigate the problem of teaching a robot manipulator to perform dynamic non-prehensile object transport, also known as the `robot waiter' task, from a limited set of real-wor…
cs.LG2024
Overcoming the Sim-to-Real Gap: Leveraging Simulation to Learn to Explore for Real-World RL
Andrew Wagenmaker, Kevin Huang, Liyiming Ke +3
In order to mitigate the sample complexity of real-world reinforcement learning, common practice is to first train a policy in a simulator where samples are cheap, and then deploy…