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Can we collect robot data without any robots? Introducing Universal Manipulation Interface (UMI) An open-source $400 system from Stanford University designed to democratize robot data collection 0 teleop -> autonomously wash dishes (precise), toss (dynamic), and fold clothes (bimanual)

Check out Cheng Chi's step-by-step tutorial on building the UMI gripper. We really hope to see more UMIs running in the wild. 😊

a bit surprised TRIs new robot has gotten little love on X current humanoid approaches seem very hand centric but we use tactile sensing across our whole body to do tasks

And if you’re at all interested in humanoids you need to check out Punyo, from TRI, a soft-body humanoid capable of whole-body manipulation. A soft robot like this could be extremely helpful for in-home robots. Check out their medium post: medium.com/toyotaresearch…

Introducing Diffusion Forcing, which unifies next-token prediction (eg LLMs) and full-seq. diffusion (eg SORA)! It offers improved performance & new sampling strategies in vision and robotics, such as stable, infinite video generation, better diffusion planning, and more! (1/8)

This #RSS2024 on July 19, we are organizing a tutorial on supervised policy learning for real world robots! Talks by Mahi Shafiullah 🏠🤖 & Russ Tedrake will cover the fundamentals of imitation, recent algorithms, walk-through code, and practical considerations. supervised-robot-learning.github.io

I'm super excited to start a great new collaboration with the fantastic team at Boston Dynamics. Scott Kuindersma and I chatted with Evan Ackerman about it earlier today. spectrum.ieee.org/boston-dynamic…

Announcing Diffusion Forcing Transformer (DFoT), our new video diffusion algorithm that generates ultra-long videos of 800+ frames. DFoT enables History Guidance, a simple add-on to any existing video diffusion models for a quality boost. Website: boyuan.space/history-guidan… (1/7)

New Paper: "Scalable Real2Sim: Physics-Aware Asset Generation via Robotic Pick-and-Place Setups"! 🤖 We introduce a fully automated pipeline that generates simulation-ready assets for real-world objects—no manual intervention needed! 🌐 Website: scalable-real2sim.github.io (1/5)⬇️

Very proud of Nicholas, who recently shared scalable-real2sim.github.io (for physics-quality assets from a small amount of interaction with a robot) and is now following up with his work on scene-level generation.