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ViNT (Visual Nav Transformer) now has a diffusion decoder, which enables some cool new capabilities! We call it NoMaD, and it can explore new environments, control different robots, and seek out goals. If you want an off-the-shelf navigation foundation model, check it out! A 🧵👇

Visual Nav Transformer 🤝 Diffusion Policy Works really well and ready for deployment on your robot today! We will also be demoing this Conference on Robot Learning 🤖 Videos, code and checkpoints: general-navigation-models.github.io Work led by Ajay Sridhar in collaboration with Catherine Glossop Sergey Levine

Cross-embodied robot policies hold the promise of one policy to control all robots. But how far does transfer go? In new work, we study positive transfer between *manipulation* & *navigation* and show that nav data helps manipulation, and vice versa! extreme-cross-embodiment.github.io 🧵 👇

Cross embodiment for manipulation (RT-X) and cross embodiment for navigation (NoMAD) win best paper at #ICRA2024 Big congratulations in order for my colleagues and students, congratulations! Seems pretty clear where the field is headed...

Hearty congratulations to BAIR students, faculty and alumni for their many awards at #ICRA2024 this week in Japan BAIR alumni Pulkit Agrawal Lerrel Pinto Roberto Calandra won Early Career awards; students from Sergey Levine Ken Goldberg Jitendra MALIK labs won both Best Paper awards!

Excited to share our recent research, LeLaN for learning language-condtitioned navigation policy from in-the-wild video in UC Berkeley and Toyota Motor North America. We present the LeLaN on CoRL 2024. Catherine Glossop Ajay Sridhar Dhruv Shah Oier Mees and Sergey Levine

We trained a robotic foundation model that can drive mobile robots in six different countries, and navigate Sproul Plaza in midday on the UC Berkeley campus! Some cool new work w/ noriaki_hirose, Lydia Ignatova, Kyle Stachowicz, Catherine Glossop, Dhruv Shah model-base-reannotation.github.io