3 citations · 7 across the 13 of their papers we have counts for
4 papers · 1 filter
STRAP: Robot Sub-Trajectory Retrieval for Augmented Policy Learning
Marius Memmel, Jacob Berg, Bingqing Chen +2
Robot learning is witnessing a significant increase in the size, diversity, and complexity of pre-collected datasets, mirroring trends in domains such as natural language processin…
URDFormer: A Pipeline for Constructing Articulated Simulation Environments from Real-World Images
Zoey Chen, Aaron Walsman, Marius Memmel +6
Constructing simulation scenes that are both visually and physically realistic is a problem of practical interest in domains ranging from robotics to computer vision. This problem…
ASID: Active Exploration for System Identification in Robotic Manipulation
Marius Memmel, Andrew Wagenmaker, Chuning Zhu +3
Model-free control strategies such as reinforcement learning have shown the ability to learn control strategies without requiring an accurate model or simulator of the world. While…
DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset
Alexander Khazatsky, Karl Pertsch, Suraj Nair +98
The creation of large, diverse, high-quality robot manipulation datasets is an important stepping stone on the path toward more capable and robust robotic manipulation policies. Ho…