2 citations · 3 across the 2 of their papers we have counts for
2 papers
cs.RO2023★ 1 cited
Stabilize to Act: Learning to Coordinate for Bimanual Manipulation
Jennifer Grannen, Yilin Wu, Brandon Vu +1
Key to rich, dexterous manipulation in the real world is the ability to coordinate control across two hands. However, while the promise afforded by bimanual robotic systems is imme…
cs.RO2023★ 2 cited
Robot Fine-Tuning Made Easy: Pre-Training Rewards and Policies for Autonomous Real-World Reinforcement Learning
Jingyun Yang, Max Sobol Mark, Brandon Vu +3
The pre-train and fine-tune paradigm in machine learning has had dramatic success in a wide range of domains because the use of existing data or pre-trained models on the internet…