How to generate billion-scale manipulation demonstrations easily? Let us leverage generative models! 🤖✨ We introduce Dex1B, a framework that generates 1 BILLION diverse dexterous hand demonstrations for both grasping 🖐️and articulation 💻 tasks using a simple C-VAE model.

How can we leverage diverse human videos to improve robot manipulation? Excited to introduce EgoVLA — a Vision-Language-Action model trained on egocentric human videos by explicitly modeling wrist & hand motion. We build a shared action space between humans and robots, enabling

The "Real Steel" moment comes to reality!! 🤯

Let your robot peek around corners, size up the gap between chairs, and know exactly where everything sits. 🤖 Our new work SR-3D masters this kind of spatial reasoning. It learns from multiple views to understand distances, layouts, and how objects relate in 3D space.

Ever want to enjoy all the privileged information in sim while seamlessly transferring to the real world? How can we correct policy mistakes after deployment? 👉Introducing GSWorld, a real2sim2real photo-realistic simulator with interaction physics with fully open-sourced code.

As an AI researcher, are you interested in tracking trends from CV/NLP/ML to robotics—even Nature/Science. Our paper “Real Deep Research for AI, Robotics & Beyond” automates survey generation and trend/topic discovery across fields 🔥Explore RDR at realdeepresearch.github.io

How do we make dexterous hands handle both power and precision tasks with ease? 🫳👌🫰 We introduce Power to Precision (💪➡️🎯), our new paper that optimizes both control and fingertip geometry to unlock robust manipulation from power grasp to fine-grained manipulations. With

Really inspiring! Check out this amazing project that optimizes with both software and hardware to produce such dexterous behavior!

What if a humanoid robot could choose how to interact with the environment 🤖 — soft when it needs compliance, stiff when it needs precision, and force-aware when it must push/pull? That’s exactly what our Heterogeneous Meta-Control (HMC) framework enables. Our new framework

How far can we push the limit of in-hand manipulation dexterity? Introducing our work on motion capture: DexterCap & DexterHand ! DexterCap: A high-fidelity motion capture system for intricate in-hand manipulation motion. DexterHand: A dataset featuring true in-hand

Can we bridge the Sim-to-Real gap in complex manipulation without explicit system ID? 🤖 Presenting Contact-Aware Neural Dynamics — a diffusion-based framework that grounds simulation with real-world touch. Implicit Alignment: No tedious parameter tuning. Tactile-Driven:

You dont need brute force randomization for cross embodiment whole body control

Generalist policies need to be cross-embodiment!🦾🦿

To what extent can the humanoid cross-embodiment do? Please check out the latest work! 💪 If you've done humanoid, then you must know how hard it is to get those different robots work at the same time!