New
A method for training our generalist policies with RL to improve success rate and throughput on real-world tasks.
Our latest generalist policy, π0.5, extends π0 and enables open-world generalization. Our new model can control a mobile manipulator to clean up an entirely new kitchen or bedroom.
We are releasing the weights and code for π0 as well as our new π0-FAST autoregressive model.
Our first generalist policy, π0, a prototype model that combines large-scale multi-task and multi-robot data collection with a new network architecture to enable the most capable and dexterous generalist robot policy to date.