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Boston Dynamics collaborated with NVIDIA to demonstrate DextrAH-RGB, a workflow for dexterous grasping from stereo RGB input. The end-to-end policy for Atlas robot, trained entirely in NVIDIA Isaac Lab, transfers zero-shot from simulation to the real robot.

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The Humanoid Hub

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79,696 görüntüleme • 1 yıl önce •via X (Twitter)

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Trains a fabric-guided teacher policy with RL in simulation, then distills it into a stereo-RGB student policy via an imitation learning framework for zero-shot grasping on novel objects. Technical blog:

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Meta AI researchers are fretting over the threat of Chinese AI, whose quality caught American firms, including OpenAI, by surprise.

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Reborn1 yıl önce

NVIDIA’s Isaac platform has quietly become one of the most comprehensive robotics dev stack out there.

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i would love to see an uncut version of like 20 minutes to see where we rly are this video has a lot of cuts in it still amazing though

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Yo that's so sickkk

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So basically, we’re one step closer to having robots that can steal our snacks without us noticing? 🍕🤖

Benzer Videolar

Next step in dynamic dexterous grasping from NVIDIA: DextrAH-RGB! No more depth. We’re now consuming RGB stereo pairs, and the resulting perceptual system is much more robust. Trained entirely in sim (IsaacLab), leveraging fast tiled rendering, and deployed zero-shot to real.
0:47

Next step in dynamic dexterous grasping from NVIDIA: DextrAH-RGB! No more depth. We’re now consuming RGB stereo pairs, and the resulting perceptual system is much more robust. Trained entirely in sim (IsaacLab), leveraging fast tiled rendering, and deployed zero-shot to real.

Nathan Ratliff

47,247 görüntüleme • 1 yıl önce

We talked to Ritvik Singh about how you can train sim-to-real dexterous manipulation policies using NVIDIA Isaac. This robot is grasping objects using pure RGB stereo: take in images from a camera pair and predict what to do, all without training in the real world.
1:08

We talked to Ritvik Singh about how you can train sim-to-real dexterous manipulation policies using NVIDIA Isaac. This robot is grasping objects using pure RGB stereo: take in images from a camera pair and predict what to do, all without training in the real world.

Chris Paxton

20,042 görüntüleme • 10 ay önce

Boston Dynamics taught Atlas a Rabona kick. Learned from human mocap, retargeted to Atlas, trained in sim via RL, deployed zero-shot to the real robot. Soccer skills demand whole-body coordination, and similar recipe transfers to warehouse work.
0:58

Boston Dynamics taught Atlas a Rabona kick. Learned from human mocap, retargeted to Atlas, trained in sim via RL, deployed zero-shot to the real robot. Soccer skills demand whole-body coordination, and similar recipe transfers to warehouse work.

The Humanoid Hub

11,109 görüntüleme • 15 gün önce

A big part of scaling robot learning to solve real-world problems is that we somehow need to get enough diverse, high-quality data to train our robots to perform useful things. GPT and its fellow large language models were bootstrapped and proved out on a massive dataset of real-world language data. Unfortunately, despite our best efforts, similarly massive datasets don’t really exist for robotics — so, in our unending pursuit of high-quality, useful data, we turn to simulation. I compared a couple recent works on sim-to-real robot manipulation, which discuss how to train perception-driven manipulation policies in simulation, in such a way that they’re useful in the real world. - DextraH-RGB, from NVIDIA - Sim-and-Real Co-Training: A Simple Recipe for Vision-Based Robotic Manipulation, also from NVIDIA — specifically the GEAR lab - Sim-to-Real Reinforcement Learning for Vision-Based Dexterous Manipulation on Humanoids, another GEAR lab paper - Local Policies Enable Zero-shot Long-Horizon Manipulation, from CMU (video from DextrAH-RGB)
0:33

A big part of scaling robot learning to solve real-world problems is that we somehow need to get enough diverse, high-quality data to train our robots to perform useful things. GPT and its fellow large language models were bootstrapped and proved out on a massive dataset of real-world language data. Unfortunately, despite our best efforts, similarly massive datasets don’t really exist for robotics — so, in our unending pursuit of high-quality, useful data, we turn to simulation. I compared a couple recent works on sim-to-real robot manipulation, which discuss how to train perception-driven manipulation policies in simulation, in such a way that they’re useful in the real world. - DextraH-RGB, from NVIDIA - Sim-and-Real Co-Training: A Simple Recipe for Vision-Based Robotic Manipulation, also from NVIDIA — specifically the GEAR lab - Sim-to-Real Reinforcement Learning for Vision-Based Dexterous Manipulation on Humanoids, another GEAR lab paper - Local Policies Enable Zero-shot Long-Horizon Manipulation, from CMU (video from DextrAH-RGB)

Chris Paxton

20,486 görüntüleme • 1 yıl önce

NVIDIA announces the first open humanoid robot reference design built for robotics research. The NVIDIA Isaac GR00T Reference Humanoid Robot combines the Unitree H2 humanoid robot, Sharpa Wave five-fingered hands for dexterous manipulation, Jetson Thor onboard compute, and Isaac GR00T open software and models, giving researchers a full-stack platform from data capture to model deployment. Read the #NVIDIAGTC Taipei announcement:
0:20

NVIDIA announces the first open humanoid robot reference design built for robotics research. The NVIDIA Isaac GR00T Reference Humanoid Robot combines the Unitree H2 humanoid robot, Sharpa Wave five-fingered hands for dexterous manipulation, Jetson Thor onboard compute, and Isaac GR00T open software and models, giving researchers a full-stack platform from data capture to model deployment. Read the #NVIDIAGTC Taipei announcement:

NVIDIA Robotics

161,220 görüntüleme • 18 gün önce

What if we can simulate an *interactive 3D world*, from a single image, in the wild, in real time? Introducing PointWorld-1B: a large pre-trained 3D world model that predicts env dynamics given RGB-D capture and robot actions. 🌐 from Stanford University NVIDIA
2:08

What if we can simulate an *interactive 3D world*, from a single image, in the wild, in real time? Introducing PointWorld-1B: a large pre-trained 3D world model that predicts env dynamics given RGB-D capture and robot actions. 🌐 from Stanford University NVIDIA

Wenlong Huang

273,009 görüntüleme • 5 ay önce

Physics AI 🌊 Jensen just unveiled the NVIDIA Isaac GR00T Reference Humanoid Robot at GTC Taipei--the world’s first open-source humanoid robot reference design Built on Jetson Thor edge computing and the Isaac GR00T open platform, it features a Unitree H2 Plus body with Sharpa five-finger dexterous hands and 75 degrees of freedom. Even before Physical AI truly explodes, NVIDIA has built a complete end-to-end full-stack infrastructure: >chips (Jetson Thor + Blackwell), >synthetic data (GR00T-Dreams), >world models (Cosmos), >foundation models (GR00T N-series VLA), >high-fidelity simulation platforms (Isaac Sim + Isaac Lab + Omniverse). Dozens of humanoid robot companies ,including Agility Robotics, Aglie robotics,Boston Dynamics, Figure, 1X, NEURA Robotics, XPENG Robotics, and more are already running large-scale daily simulation training on this platform, rapidly iterating perception, reasoning, and actions in virtual environments, speeding up the jump from lab prototypes to real factory deployment. By providing an open reference design and full-stack tools, NVIDIA has dramatically lowered the barrier, letting every robotics team join the Physical AI wave with low cost and high efficiency.
4:31

Physics AI 🌊 Jensen just unveiled the NVIDIA Isaac GR00T Reference Humanoid Robot at GTC Taipei--the world’s first open-source humanoid robot reference design Built on Jetson Thor edge computing and the Isaac GR00T open platform, it features a Unitree H2 Plus body with Sharpa five-finger dexterous hands and 75 degrees of freedom. Even before Physical AI truly explodes, NVIDIA has built a complete end-to-end full-stack infrastructure: >chips (Jetson Thor + Blackwell), >synthetic data (GR00T-Dreams), >world models (Cosmos), >foundation models (GR00T N-series VLA), >high-fidelity simulation platforms (Isaac Sim + Isaac Lab + Omniverse). Dozens of humanoid robot companies ,including Agility Robotics, Aglie robotics,Boston Dynamics, Figure, 1X, NEURA Robotics, XPENG Robotics, and more are already running large-scale daily simulation training on this platform, rapidly iterating perception, reasoning, and actions in virtual environments, speeding up the jump from lab prototypes to real factory deployment. By providing an open reference design and full-stack tools, NVIDIA has dramatically lowered the barrier, letting every robotics team join the Physical AI wave with low cost and high efficiency.

CyberRobo

17,092 görüntüleme • 18 gün önce

Boston Dynamics has demonstrated its new Atlas humanoid robot lifting and carrying a 50-pound fridge. The robot uses its whole body to balance and move the heavy object in a natural, human-like way. Before doing it in the real world, Atlas practiced the task for millions of hours in a virtual simulation.
0:26

Boston Dynamics has demonstrated its new Atlas humanoid robot lifting and carrying a 50-pound fridge. The robot uses its whole body to balance and move the heavy object in a natural, human-like way. Before doing it in the real world, Atlas practiced the task for millions of hours in a virtual simulation.

Space and Technology

178,642 görüntüleme • 12 gün önce

Real → Sim → Robot — fast. With Gaussian splats, GRID brings physical assets into simulation tools like AirGen and NVIDIA Isaac Sim, enabling AI skills to be tested in sim and deployed to real robots in minutes. #Robotics #PhysicalAI #Simulation
0:58

Real → Sim → Robot — fast. With Gaussian splats, GRID brings physical assets into simulation tools like AirGen and NVIDIA Isaac Sim, enabling AI skills to be tested in sim and deployed to real robots in minutes. #Robotics #PhysicalAI #Simulation

General Robotics

12,257 görüntüleme • 10 ay önce

Excited to introduce StereoPolicy, led by Evans Han. 📷📷🤖StereoPolicy is an effective way to add geometric cues to modern robot policy models while keeping the strengths of pretrained 2D encoders. ⁉️Why stereo for robot manipulation? Monocular RGB often lacks the depth cues needed for precise manipulation, while RGB-D and point clouds can be noisy or brittle, especially on reflective and transparent objects in real-world deployment. Instead of explicitly reconstructing disparity, depth, or point clouds, StereoPolicy directly fuses synchronized left/right RGB views to learn implicit stereo cues, avoiding extra reconstruction latency that can make real-time manipulation difficult. Project Page:
0:50

Excited to introduce StereoPolicy, led by Evans Han. 📷📷🤖StereoPolicy is an effective way to add geometric cues to modern robot policy models while keeping the strengths of pretrained 2D encoders. ⁉️Why stereo for robot manipulation? Monocular RGB often lacks the depth cues needed for precise manipulation, while RGB-D and point clouds can be noisy or brittle, especially on reflective and transparent objects in real-world deployment. Instead of explicitly reconstructing disparity, depth, or point clouds, StereoPolicy directly fuses synchronized left/right RGB views to learn implicit stereo cues, avoiding extra reconstruction latency that can make real-time manipulation difficult. Project Page:

Ruohan Zhang

848,366 görüntüleme • 16 gün önce

Big news! World Labs' Marble is officially compatible with NVIDIA Robotics' Isaac Sim. Instead of showcasing their highlight reel, our team at Lightwheel created a full environment from a 360 pano using Marble and showed you can train directly in sim. The only non-generated assets are the robot arms, coffee, and bowl. Everything else was generated with Marble. Not sure how to do this yourself? NVIDIA wrote a technical blog with full instructions. You will learn how to: 1. Export scenes from World Labs' Marble as Gaussian splats 2. Convert to USD using NVIDIA Omniverse NuRec 3. Import into NVIDIA Isaac Sim 4. Add a robot and run the simulation Read the guide ➡️ #WorldModels #Robotics
0:32

Big news! World Labs' Marble is officially compatible with NVIDIA Robotics' Isaac Sim. Instead of showcasing their highlight reel, our team at Lightwheel created a full environment from a 360 pano using Marble and showed you can train directly in sim. The only non-generated assets are the robot arms, coffee, and bowl. Everything else was generated with Marble. Not sure how to do this yourself? NVIDIA wrote a technical blog with full instructions. You will learn how to: 1. Export scenes from World Labs' Marble as Gaussian splats 2. Convert to USD using NVIDIA Omniverse NuRec 3. Import into NVIDIA Isaac Sim 4. Add a robot and run the simulation Read the guide ➡️ #WorldModels #Robotics

Jonathan Stephens

13,783 görüntüleme • 6 ay önce

Teach your robot how to screw bolts, 1080p 30 Hz RGB+ Stereo depth + IMU+ 3D hand annotation + text annotation reply for sample dataset :)
0:55

Teach your robot how to screw bolts, 1080p 30 Hz RGB+ Stereo depth + IMU+ 3D hand annotation + text annotation reply for sample dataset :)

Bercan

52,218 görüntüleme • 8 ay önce

🤖HUMANOIDS ARE READY FOR HEAVY LIFTING, LITERALLY Boston Dynamics’ Atlas picked up a FULL fridge and carried it across the lab. The robot figured out how to keep the load steady on its own.
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🤖HUMANOIDS ARE READY FOR HEAVY LIFTING, LITERALLY Boston Dynamics’ Atlas picked up a FULL fridge and carried it across the lab. The robot figured out how to keep the load steady on its own.

Coin Bureau

31,826 görüntüleme • 1 gün önce

NVIDIA's Jim Fan has verified from reliable sources that the video by EngineAI is a real robot demo and not CGI. The controller is a neural net trained in the NVIDIA Isaac simulator using reinforcement learning. There’s also another video from a different angle.
0:06

NVIDIA's Jim Fan has verified from reliable sources that the video by EngineAI is a real robot demo and not CGI. The controller is a neural net trained in the NVIDIA Isaac simulator using reinforcement learning. There’s also another video from a different angle.

The Humanoid Hub

148,535 görüntüleme • 1 yıl önce

Thirty years of development at Boston Dynamics led to their Robot, Atlas.
0:44

Thirty years of development at Boston Dynamics led to their Robot, Atlas.

Fascinating

1,802,014 görüntüleme • 2 yıl önce

Robot dogs dancing to K-pop and the first public appearance of Boston Dynamics’ Atlas humanoid robot highlight Hyundai’s CES tech showcase.
0:23

Robot dogs dancing to K-pop and the first public appearance of Boston Dynamics’ Atlas humanoid robot highlight Hyundai’s CES tech showcase.

The Associated Press

84,060 görüntüleme • 5 ay önce

Reality of robotics: humanoid kung fu is solved before they can open doors with RGB. Here we are. Introducing the frontier of sim2real at NVIDIA GEAR. 100% sim data. RGB input only. Code name: 𝗗𝗼𝗼𝗿𝗠𝗮𝗻. We are opening the sim-to-real door. 🧵
1:01

Reality of robotics: humanoid kung fu is solved before they can open doors with RGB. Here we are. Introducing the frontier of sim2real at NVIDIA GEAR. 100% sim data. RGB input only. Code name: 𝗗𝗼𝗼𝗿𝗠𝗮𝗻. We are opening the sim-to-real door. 🧵

Haoru Xue

370,906 görüntüleme • 6 ay önce

Dex is ready for the factory floor. 🏭 Learn how Richtech Robotics built this mobile humanoid robot, powered by NVIDIA Jetson AGX Thor and trained in Isaac Sim, to handle light to medium industrial tasks. Read the blog ➡️
0:36

Dex is ready for the factory floor. 🏭 Learn how Richtech Robotics built this mobile humanoid robot, powered by NVIDIA Jetson AGX Thor and trained in Isaac Sim, to handle light to medium industrial tasks. Read the blog ➡️

NVIDIA Robotics

25,381 görüntüleme • 6 ay önce

Boston Dynamics has released a new video of their next-generation humanoid robot, Atlas. "We are excited to share some of our progress on developing Large Behavior Models for Atlas. This work is part of a collaboration between AI research teams at Toyota Research Institute (TRI) and Boston Dynamics. We have been building end-to-end language-conditioned policies that enable Atlas to accomplish long-horizon manipulation tasks."
2:02

Boston Dynamics has released a new video of their next-generation humanoid robot, Atlas. "We are excited to share some of our progress on developing Large Behavior Models for Atlas. This work is part of a collaboration between AI research teams at Toyota Research Institute (TRI) and Boston Dynamics. We have been building end-to-end language-conditioned policies that enable Atlas to accomplish long-horizon manipulation tasks."

Sawyer Merritt

200,744 görüntüleme • 9 ay önce

Netflix funded $100 million to make Atlas, a film where JLO is forced to team up with an AI robot in order to prevent an apocalypse In the end JLO and the AI Robot expressed their feelings for each after winning the final battle, yes this is real.
2:19

Netflix funded $100 million to make Atlas, a film where JLO is forced to team up with an AI robot in order to prevent an apocalypse In the end JLO and the AI Robot expressed their feelings for each after winning the final battle, yes this is real.

Ahmed/The Ears/IG: BigBizTheGod 🇸🇴

829,508 görüntüleme • 2 yıl önce