Open X-Embodiment: Robotic Learning Datasets and RT-X Models

We assemble a dataset from 22 different robots collected through a collaboration between 21 institutions, demonstrating 527 skills (160266 tasks). We show that a high-capacity model trained on this data, which we call RT-X, exhibits positive transfer and improves the capabilities of multiple robots by leveraging experience from other platforms.

RT-2-X (55B): one of the biggest models to date performing unseen tasks in academic labs

The dataset was constructed by pooling 60 existing robot datasets from 34 robotic research labs around the world.