Zhenyu Jiang
@SteveTod1998
Ph.D. student in computer vision and robotics at @UTCompSci.
How to use simulation data for real-world robot manipulation? We present sim-and-real co-training, a simple recipe for manipulation. We demonstrate that sim data can significantly enhance real-world performance, even with notable differences between the sim and the real. (1/n)
Check out Casper, a robot sidekick that actively predicts user intent and assists human interactively!
Meet Casper👻, a friendly robot sidekick who shadows your day, decodes your intents on the fly, and lends a hand while you stay in control! Instead of passively receiving commands, what if a robot actively sense what you need in the background, and step in when confident? (1/n)
(1/n) Many large-scale robot datasets have been released, but their quality varies. How can we curate them to improve policy performance? We present SCIZOR, a self-supervised framework that filters low-quality data, boosting policy performance in both simulation and real world.
Ep#11 with @snasiriany @SteveTod1998 @abhirammaddukur @Lawrence_Y_Chen on Sim-and-Real Co-Training: A Simple Recipe for Vision-Based Robotic Manipulation co-training.github.io Co-hosted by @chris_j_paxton & @micoolcho
Excited to be at Atlanta for #ICRA2025 next week and present our work DexMimicGen on Thursday! Please come check our presentation at 5:00 pm @ 411 and stop by our poster at poster board!
How can we scale up humanoid data acquisition with minimal human effort? Introducing DexMimicGen, a large-scale automated data generation system that synthesizes trajectories from a few human demonstrations for humanoid robots with dexterous hands. (1/n)
Competitive Pokémon has all the makings of a great RL research problem: - Stochasticity? ✅ - Imperfect information? ✅ - Generalization? ✅ - More fun than half-cheetah? ✅✅✅ And today it gets better…
Awesome work from @adamwei_ diving deep into sim-and-real co-training. Our concurrent work (co-training.github.io) shares similar findings on a large range of tasks. We are seeing promising progress on leveraging simulation data on a larger scale!
Learning from both sim+real data could scale robot imitation learning. But what are the scaling laws & principles of sim+real cotraining? We study this in the first focused analysis of sim+real cotraining spanning 250+ policies & 40k+ evals arxiv.org/abs/2503.22634 (1/6)
Check out GR00T N1, our first open foundation model for humanoid robots!
Excited to announce GR00T N1, the world’s first open foundation model for humanoid robots! We are on a mission to democratize Physical AI. The power of general robot brain, in the palm of your hand - with only 2B parameters, N1 learns from the most diverse physical action dataset…