Why buy a robot when you can build your own?
Meet YOR, our new open-source bimanual mobile manipulator robot ā built for researchers and hackers alike for only ~$10k. š§µš
Proud to announce DobbĀ·E: the next step in home robot system that I was working on for the past 3 years.
We have visited 10 homes, learned 100+ tasks, and we are just getting started!
And we fully open-sourced it all, hardware, models, and software: dobb-e.com š§µ
Robot Utility Models (RUMs) enable basic tasks ā door opening, drawer opening, object reorientation, etc. ā at ~90% accuracy without ANY finetuning (i.e. zero-shot) in unseen new environments.
Fully open source!!! models, data, code & hw.
We think this is super exciting, why?š
How can we train data-efficient robots that can respond to open-ended queries like āwarm up my lunchā or āfind a blue bookā?
Introducing CLIP-Field, a semantic neural field trained w/ NO human labels & only w/ web-data pretrained detectors, VLMs, and LLMs mahis.life/clip-fields
Happy to share that I'm a Dr. now! šš I'm indebted to @LerrelPinto for his š„ advice & mentorship, and an unforgettable five years.
Next up, I'm starting a postdoc with @JitendraMalikCV, spending time at @berkeley_ai & @AIatMeta. Would love to say hi if you're in the bay area!
Wouldnāt it be nice if you could bring a robot home, give it a video of your room, and immediately start asking it to move objects around?
Turns out, now you can!
Introducing OK-Robot, a zero-shot language-specified pick & drop system that we built with exactly ZERO training! š§µ
Delighted to share that I've been awarded the 2023 @Apple Scholars in AI/ML PhD fellowship for my work in Machine Learning for robots: machinelearning.apple.com/updates/apple-ā¦
Huge part of the credits go to @LerrelPinto for the invaluable advising and support. Thank you!
The "Supervised Policy Learning for Real Robots" tutorial at #RSS2024 is now public!
supervised-robot-learning.github.io
We're trying to democratize the "folk knowledge" of training real robot policies, and cover the fundamentals of imitation, recent algorithms, & practical considerations.
If you want robots that can just live with you & help 24/7, it needs to build & update its memory on the fly. Current semantic memory representations like VoxelMap from OK-Robot can't change with the world.
That's why we built DynaMem: dynamic memory for a changing, open world!
Morning, #ICRA2025@ieee_ras_icra!
Bring something small šš and have our Robot Utility Model pick it up at our EXPO demo today from 1-5 PM, between hall A2/A3! Talk and poster is right before, 11:15-12:15 in room 411.
Also, DM if you want to chat š¤ for the messy, real world!
"Imitation learning just works" should probably be one of the biggest takeaways from the last year in robotics. Congrats @tonyzzhao@zipengfu and @chelseabfinn on this amazing work! Let's make the setup more compact so I can bring it to my (grad student sized) home :D
Meet Mobile ALOHA! š¤
Whatās new:
- low-cost but widely-capable teleop platform š¦¾š
- imitation learning just works
Paper/Code/Videos: mobile-aloha.github.io
Led by @zipengfu and @tonyzzhao
Had a fun day of demoing Dobbā¢E with @HarithejaE at NeurIPS!
Tomorrow we will be at the robot learning workshop (hall B2), so stop by for some real robot fun if you missed us today :)
OK-Robot code is now open! Check out github.com/ok-robot/ok-roā¦
We want to make it even better by collaborating with the community, so join our discord if you have questions, need help, or want to help discord.gg/wzzZJxqKYC
Thereās nothing like seeing a robot working at home for yourself. It has to move a variety of unusual objects, like the green cactus plushie in this video, and place them intelligently in a very messy world.
So on that note, we're opening up OK Robot to the community! A thread:
Almost ā¾ unlabeled data is the āsecret sauceā for today's ML, but how do we use uncurated datasets in robot learning?
Conditional Behavior Transformer makes sense of "play" style robot demos w/ no labels and no RL to extract conditional policies!
Play-to-policy.github.io š§µ