103 citations · 163 across the 17 of their papers we have counts for
5 papers · 1 filter
Zero-Shot Robotic Manipulation with Pretrained Image-Editing Diffusion Models
Kevin Black, Mitsuhiko Nakamoto, Pranav Atreya +4
If generalist robots are to operate in truly unstructured environments, they need to be able to recognize and reason about novel objects and scenarios. Such objects and scenarios m…
Open X-Embodiment: Robotic Learning Datasets and RT-X Models
Embodiment Collaboration, Abby O'Neill, Abdul Rehman +291
Large, high-capacity models trained on diverse datasets have shown remarkable successes on efficiently tackling downstream applications. In domains from NLP to Computer Vision, thi…
Goal Representations for Instruction Following: A Semi-Supervised Language Interface to Control
Vivek Myers, Andre He, Kuan Fang +7
Our goal is for robots to follow natural language instructions like "put the towel next to the microwave." But getting large amounts of labeled data, i.e. data that contains demons…
BridgeData V2: A Dataset for Robot Learning at Scale
Homer Walke, Kevin Black, Abraham Lee +11
We introduce BridgeData V2, a large and diverse dataset of robotic manipulation behaviors designed to facilitate research on scalable robot learning. BridgeData V2 contains 60,096…
Stabilizing Contrastive RL: Techniques for Robotic Goal Reaching from Offline Data
Chongyi Zheng, Benjamin Eysenbach, Homer Walke +4
Robotic systems that rely primarily on self-supervised learning have the potential to decrease the amount of human annotation and engineering effort required to learn control strat…