Yu Lei @_OutofMemory_
Looking for 25Fall Ph.D.!; Undergraduate @SJTU1896 | @CMU_Robotics; @UCSD. Learn to learn representations and learn to search within and beyond. 🤖🧠👁️ theknight-z.github.io Pittsburgh, PA Joined July 2023-
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90% success rate in unseen environments. No new data, no fine-tuning. Autonomously. Most robots need retraining to work in new places. What if they didn’t? Robot Utility Models (RUMs) learn once and work anywhere... zero-shot. A team from NYU and Hello Robot built a set of…
🏓🤖 Our humanoid robot can now rally over 100 consecutive shots against a human in real table tennis — fully autonomous, sub-second reaction, human-like strikes.
The new humanoid whole-body teleop & policy learning demo from @BostonDynamics & @ToyotaResearch is so impressive. The telelop system includes BD's MPC system as controllers, VR headset, base stations, and trackers on chest & feet. The policy learning architecture is similar to…
🎉 Very happy to have our paper on predictive red teaming accepted to @corl_conf! Writing a first-author paper again was a good reminder of all the hard work students put in on details that I've forgotten about over the years. Project page: rb.gy/buih3o
This is a neural network named Helix learning how to do laundry
A large part of Robot Learning is systems research, but it doesn't quite fit the existing paradigms: think of CoRL, RSS, SOSP, and MLSys. It draws from all but is inherently full-stack --- hardware, control, compute, ml algos. There are nice works here and there but we likely…
Another one. Already a powerful painting, but moving around it yourself gives a totally different feeling. Jacques Louis David's "The Death of Socrates" => #Genie3
World modeling for robotics is incredibly hard because (1) control of humanoid robots & 5-finger hands is wayyy harder than ⬆️⬅️⬇️➡️ in games (Genie 3); and (2) object interaction is much more diverse than FSD, which needs to *avoid* coming into contact. Our GR00T Dreams work was…
World modeling for robotics is incredibly hard because (1) control of humanoid robots & 5-finger hands is wayyy harder than ⬆️⬅️⬇️➡️ in games (Genie 3); and (2) object interaction is much more diverse than FSD, which needs to *avoid* coming into contact. Our GR00T Dreams work was…
What if you could not only watch a generated video, but explore it too? 🌐 Genie 3 is our groundbreaking world model that creates interactive, playable environments from a single text prompt. From photorealistic landscapes to fantasy realms, the possibilities are endless. 🧵
Excited to open-source GMR: General Motion Retargeting. Real-time human-to-humanoid retargeting on your laptop. Supports diverse motion formats & robots. Unlock whole-body humanoid teleoperation (e.g., TWIST). video with 🔊
Excited to see that particle-based dynamics model learning + MPC gets applied in cloth manipulation with multifingered hands! The idea of predicting object motions by representing them as dense particles shares the same insight as our recent paper, PGND…
Excited to see that particle-based dynamics model learning + MPC gets applied in cloth manipulation with multifingered hands! The idea of predicting object motions by representing them as dense particles shares the same insight as our recent paper, PGND…
Love this.
July has been a big month for Viser! - Released v1.0.0😊 - We did some writing Some demos👇
We’ve been building quietly — starting tomorrow, we go live. Here’s a teaser of what we did before Skild AI. It has shaped what’s coming next. 07/29. Stay tuned.
My Takeaways from GR3: Insights on Vision-Language-Action (VLA) Models Although I wasn’t directly involved in the GR3 project, I gained valuable insights into Vision-Language-Action (VLA) models through discussions and observing their performance, particularly their failure…
My Takeaways from GR3: Insights on Vision-Language-Action (VLA) Models Although I wasn’t directly involved in the GR3 project, I gained valuable insights into Vision-Language-Action (VLA) models through discussions and observing their performance, particularly their failure…
🚀 New Open-Source Release! PyTorchTNN 🚀 A PyTorch package for building biologically-plausible temporal neural networks (TNNs)—unrolling neural network computation layer-by-layer through time, inspired by cortical processing. PyTorchTNN naturally integrates into the…
Large robot datasets are crucial for training 🤖foundation models. Yet, we lack systematic understanding of what data matters. Introducing MimicLabs ✅System to generate large synthetic robot 🦾 datasets ✅Data-composition study 🗄️ on how to collect and use large datasets 🧵1/
When facing a new physical manipulation problem, robots should think creatively and solve them in only a few attempts. We make first steps towards this MacGyver robot in our work Causal-PIK. It enables smart exploration of the massive action space - sometimes faster than humans.
When facing a new physical manipulation problem, robots should think creatively and solve them in only a few attempts. We make first steps towards this MacGyver robot in our work Causal-PIK. It enables smart exploration of the massive action space - sometimes faster than humans.
🚀Thrilled to share what we’ve been building at TRI over the past several months: our first Large Behavior Models (LBMs) are here! I’m proud to have been a core contributor to the multi-task policy learning and post-training efforts. At TRI, we’ve been researching how LBMs can…
🚀Thrilled to share what we’ve been building at TRI over the past several months: our first Large Behavior Models (LBMs) are here! I’m proud to have been a core contributor to the multi-task policy learning and post-training efforts. At TRI, we’ve been researching how LBMs can… https://t.co/IjzvkhmBwP
Many roboticists focus on designing human-like hands, but we took a closer look at the fingers. Human fingers are soft, responsive, and packed with sensitive sensory points—perfect for handling even fragile objects. What if robots had such fingers? Check out our work on FORTE!
Many roboticists focus on designing human-like hands, but we took a closer look at the fingers. Human fingers are soft, responsive, and packed with sensitive sensory points—perfect for handling even fragile objects. What if robots had such fingers? Check out our work on FORTE!
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Yifan Zhu @YifanZhu_
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Annabella Macaluso @anna_macalus
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Aaron Tan @aaronistan
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Minghuan Liu @ericliuof97
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Hongsuk Benjamin Choi @redstone_hong
498 Followers 387 Following robotics & computer vision. PhD @Berkeley_AI | prev @ Seoul National University
VITA Group @VITAGroupUT
1K Followers 3K Following VITA Group @UTAustin w/ Prof Atlas Wang | https://t.co/Wi3tJXf1mg Run by VITA students (PI is busy changing diapers😄). Tweets only reflect personal views
Zhikai Zhang @Zhikai273
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Ada Fang @AdaFang_
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Computational Neurosc... @Comp_NeuroLab
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CBMM @MIT_CBMM
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Zhi Su @ZhiSu22
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Cornell Tech @cornell_tech
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1K Followers 605 Following Robotics Research Scientist @ Robotics and AI Institute (RAI) | Making robots smarter for everyone | CS PhD from @BrownUniversity 🤖
Kaizhe Hu @hkz222
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