Categories: FAANG

Shaping the future of advanced robotics

AutoRT, SARA-RT, and RT-Trajectory build on our historic Robotics Transformers work to help robots make decisions faster, and better understand and navigate their environments.

Scaling up learning across many different robot types

We are launching a new set of resources for general-purpose robotics learning across different robot types, or embodiments. Together with partners from 34 academic labs we have pooled data from 22 different robot types to create the Open X-Embodiment dataset. We also release RT-1-X, a robotics transformer (RT) model derived…

October 4, 2023

In "FAANG"

RT-2: New model translates vision and language into action

Introducing Robotic Transformer 2 (RT-2), a novel vision-language-action (VLA) model that learns from both web and robotics data, and translates this knowledge into generalised instructions for robotic control, while retaining web-scale capabilities. This work builds upon Robotic Transformer 1 (RT-1), a model trained on multi-task demonstrations which can learn combinations…

July 29, 2023

In "FAANG"

RT-1: Robotics Transformer for Real-World Control at Scale

December 14, 2022

In "FAANG"

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