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Generalist robots need multimodal learning—fusing vision, touch, and body motion to handle unstructured worlds. 🦾 NVIDIA Isaac Lab is a GPU-accelerated, open-source simulation framework for robot learning that unifies physics, rendering, sensing, and parallel computing to train robot policies at scale. Learn more 🔗 #NVIDIAResearch

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NVIDIA Robotics

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18,568 views • 8 months ago •via X (Twitter)

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Generalist robot policies need a benchmark that works across any robot and any policy. 🦾 Introducing RoboLab, a high‑fidelity simulation benchmark built on NVIDIA Isaac and Omniverse to evaluate generalist robot policies in diverse, photoreal, physics‑based environments. Coming soon to the NVIDIA Isaac Lab‑Arena roadmap for large‑scale, robotic policy evaluation. 📖 #NationalRoboticsWeek
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Generalist robot policies need a benchmark that works across any robot and any policy. 🦾 Introducing RoboLab, a high‑fidelity simulation benchmark built on NVIDIA Isaac and Omniverse to evaluate generalist robot policies in diverse, photoreal, physics‑based environments. Coming soon to the NVIDIA Isaac Lab‑Arena roadmap for large‑scale, robotic policy evaluation. 📖 #NationalRoboticsWeek

NVIDIA Robotics

24,097 views • 7 months ago

Newton 1.0 is now generally available. 🙌 Take robot learning to the next level with: 🤖 Stable Articulated & Complex Mechanism Simulation – accurate, reliable machine modeling. 🖐️ High-Fidelity Hydroelastic Contact Modeling – realistic soft contact and touch-based interactions. 🧵 Deformable Body Simulation – simulate cables, cloth, rubber, and other elastic materials with VBD. ⚡ Accelerated Robot Learning at Scale – seamless integration with open simulation and learning frameworks, NVIDIA Isaac Sim and Isaac Lab for scalable workflows. Learn how to integrate this open-source physics engine into your workflow: #NVIDIAGTC
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Newton 1.0 is now generally available. 🙌 Take robot learning to the next level with: 🤖 Stable Articulated & Complex Mechanism Simulation – accurate, reliable machine modeling. 🖐️ High-Fidelity Hydroelastic Contact Modeling – realistic soft contact and touch-based interactions. 🧵 Deformable Body Simulation – simulate cables, cloth, rubber, and other elastic materials with VBD. ⚡ Accelerated Robot Learning at Scale – seamless integration with open simulation and learning frameworks, NVIDIA Isaac Sim and Isaac Lab for scalable workflows. Learn how to integrate this open-source physics engine into your workflow: #NVIDIAGTC

NVIDIA Robotics

82,939 views • 7 months ago

Multi-robot learning is getting a serious boost! 📚 Researchers have extended Isaac Lab to train heterogeneous multi-agent robotic policies at scale. The new framework supports high-resolution physics, GPU-accelerated simulation, and both homogeneous and heterogeneous agents working together on coordination tasks. They benchmarked different approaches (MAPPO: Multi-Agent Proximal Policy Optimization and HAPPO: Heterogeneous Agent PPO) across six challenging scenarios and showed that large-scale multi-robot training is not only feasible, but efficient. It’s an important step for real-world robotic collaboration, where teams of robots need to coordinate, split tasks, adapt roles, and interact dynamically, not just operate as identical clones. The code is open-source, and it pushes Isaac Lab closer to what robotics actually needs: scalable, physics-driven environments where many different robots can learn to work together. Here's the project page: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →
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Multi-robot learning is getting a serious boost! 📚 Researchers have extended Isaac Lab to train heterogeneous multi-agent robotic policies at scale. The new framework supports high-resolution physics, GPU-accelerated simulation, and both homogeneous and heterogeneous agents working together on coordination tasks. They benchmarked different approaches (MAPPO: Multi-Agent Proximal Policy Optimization and HAPPO: Heterogeneous Agent PPO) across six challenging scenarios and showed that large-scale multi-robot training is not only feasible, but efficient. It’s an important step for real-world robotic collaboration, where teams of robots need to coordinate, split tasks, adapt roles, and interact dynamically, not just operate as identical clones. The code is open-source, and it pushes Isaac Lab closer to what robotics actually needs: scalable, physics-driven environments where many different robots can learn to work together. Here's the project page: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

38,997 views • 11 months ago

Building robots that can effectively operate alongside human workers is difficult. 🛠️ Advances in open-source physics, open foundation models, and frameworks are helping accelerate physical #AI deployment. ✔️ Newton Physics Engine, an open-source GPU-powered simulation built on OpenUSD, speeds up robot learning for advanced manipulation and mobility. ✔️ NVIDIA Cosmos Reason, an open reasoning vision language model, gives robots the ability to think like humans using prior knowledge, common sense and physics ✔️NVIDIA Isaac GR00T N1.6, an open robot foundation model, enables humanoids to understand ambiguous instructions Leading robotics developers including Agility Robotics, Lightwheel, Mentee Robotics, UniversalRobots, and Wandelbots are adopting simulation technologies and libraries to accelerate physical AI development and deployment. Omniverse Ambassador Dylan Tobin built an AI chatbot trained on Isaac Sim workflows, helping devs navigate Omniverse faster. Read the full blog 👉
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Building robots that can effectively operate alongside human workers is difficult. 🛠️ Advances in open-source physics, open foundation models, and frameworks are helping accelerate physical #AI deployment. ✔️ Newton Physics Engine, an open-source GPU-powered simulation built on OpenUSD, speeds up robot learning for advanced manipulation and mobility. ✔️ NVIDIA Cosmos Reason, an open reasoning vision language model, gives robots the ability to think like humans using prior knowledge, common sense and physics ✔️NVIDIA Isaac GR00T N1.6, an open robot foundation model, enables humanoids to understand ambiguous instructions Leading robotics developers including Agility Robotics, Lightwheel, Mentee Robotics, UniversalRobots, and Wandelbots are adopting simulation technologies and libraries to accelerate physical AI development and deployment. Omniverse Ambassador Dylan Tobin built an AI chatbot trained on Isaac Sim workflows, helping devs navigate Omniverse faster. Read the full blog 👉

NVIDIA

48,500 views • 1 year ago

NVIDIA announces new Isaac tools for agents as Agile Robots unveils Agile ONE SN, a reference humanoid for robotics research. 🦾 Built on NVIDIA Isaac GR00T and powered by Jetson Thor, Agile ONE SN gives researchers and developers an integrated platform to develop, train and validate humanoid skills. The Isaac expansion also introduces new datasets, a runtime, and robot learning framework updates to accelerate development from data to deployment. Read the #NVIDIAGTC announcement:
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NVIDIA announces new Isaac tools for agents as Agile Robots unveils Agile ONE SN, a reference humanoid for robotics research. 🦾 Built on NVIDIA Isaac GR00T and powered by Jetson Thor, Agile ONE SN gives researchers and developers an integrated platform to develop, train and validate humanoid skills. The Isaac expansion also introduces new datasets, a runtime, and robot learning framework updates to accelerate development from data to deployment. Read the #NVIDIAGTC announcement:

NVIDIA Robotics

65,538 views • 16 days ago

#NVIDIAIsaac Sim 5.0 and Isaac Lab 2.2 are now available in early developer preview on Github. 🎉 These releases give #Robotics developers early access to cutting-edge tools to simulate, train, and validate robots in a physics-based simulation environment. What’s new? ✅Open-source ✅Extensions for synthetic data generation ✅Robot models Read the tech blog to learn more ➡️ #GTCParis #VivaTech
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#NVIDIAIsaac Sim 5.0 and Isaac Lab 2.2 are now available in early developer preview on Github. 🎉 These releases give #Robotics developers early access to cutting-edge tools to simulate, train, and validate robots in a physics-based simulation environment. What’s new? ✅Open-source ✅Extensions for synthetic data generation ✅Robot models Read the tech blog to learn more ➡️ #GTCParis #VivaTech

NVIDIA Robotics

13,662 views • 1 year ago

Robot policies can succeed in a demo and still fail as tasks, environments, and conditions change. With open-source Isaac Lab-Arena 0.3, developers can use an experimental agentic workflow to generate environments, evaluate policies at scale, and identify where and why failures occur.
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Robot policies can succeed in a demo and still fail as tasks, environments, and conditions change. With open-source Isaac Lab-Arena 0.3, developers can use an experimental agentic workflow to generate environments, evaluate policies at scale, and identify where and why failures occur.

NVIDIA Robotics

15,633 views • 1 month ago

Newton 1.5 is now available, making robot training at scale faster and more reliable. This release delivers: 🔁 More parallel simulation, lower memory, selective resets 🤝 Consistent contact physics 🤖 Experimental batched GPU control 📦 Cleaner USD/MJCF imports Get started:
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Newton 1.5 is now available, making robot training at scale faster and more reliable. This release delivers: 🔁 More parallel simulation, lower memory, selective resets 🤝 Consistent contact physics 🤖 Experimental batched GPU control 📦 Cleaner USD/MJCF imports Get started:

NVIDIA Robotics

86,912 views • 2 months ago

Robora Sim: A PyBullet-Powered Environment for Learning Robotic Physical Intelligence We are currently building our Robora simulation environment setup for our sim based learning, leveraging PyBullet, an industry-standard physics engine widely used in AI-driven robotics research and development. The environment is optimized with GPU-accelerated learning algorithms, enabling high-speed imitation learning and reinforcement learning within a safe and controlled virtual setup before shipping out to real world. This simulation platform allows our models to learn, adapt, and generalize across different robot morphologies, terrain types and task objectives - all before deployment to the real world. At it's core, the system combines a VLA-powered high-level planner with low-level motion control algorithms, working cohesively to produce emergent, physically intelligent behaviors. This synergy between simulation, learning, and real-world transfer marks a major step forward in our pursuit of adaptive and intelligent robotic systems. Through advanced domain randomization and synthetic data generation, the Robora Simulation Environment ensures that policies trained in simulation transfer effectively to real-world robots, minimizing the sim-to-real gap. Moreover, users will be able to test and integrate their own hardware kits within selected simulation environments in the Robora Dapp, ensuring seamless compatibility and safer real-world implementation.
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Robora Sim: A PyBullet-Powered Environment for Learning Robotic Physical Intelligence We are currently building our Robora simulation environment setup for our sim based learning, leveraging PyBullet, an industry-standard physics engine widely used in AI-driven robotics research and development. The environment is optimized with GPU-accelerated learning algorithms, enabling high-speed imitation learning and reinforcement learning within a safe and controlled virtual setup before shipping out to real world. This simulation platform allows our models to learn, adapt, and generalize across different robot morphologies, terrain types and task objectives - all before deployment to the real world. At it's core, the system combines a VLA-powered high-level planner with low-level motion control algorithms, working cohesively to produce emergent, physically intelligent behaviors. This synergy between simulation, learning, and real-world transfer marks a major step forward in our pursuit of adaptive and intelligent robotic systems. Through advanced domain randomization and synthetic data generation, the Robora Simulation Environment ensures that policies trained in simulation transfer effectively to real-world robots, minimizing the sim-to-real gap. Moreover, users will be able to test and integrate their own hardware kits within selected simulation environments in the Robora Dapp, ensuring seamless compatibility and safer real-world implementation.

Robora

23,540 views • 1 year ago

All robots need intelligence 🧠 Announcing #NVIDIA Isaac sim GRID integration. Develop, simulate, and deploy robot AI without complex infrastructure, across consumer and commercial robots—humanoids, quadrupeds arms. Blog: #CES #Robot #AI #CES2025 NVIDIA NVIDIA Robotics
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All robots need intelligence 🧠 Announcing #NVIDIA Isaac sim GRID integration. Develop, simulate, and deploy robot AI without complex infrastructure, across consumer and commercial robots—humanoids, quadrupeds arms. Blog: #CES #Robot #AI #CES2025 NVIDIA NVIDIA Robotics

General Robotics

30,203 views • 1 year ago

We've open-sourced torobo_isaac_lab, an extension for NVIDIA Isaac Lab. By providing rewards that consider gait, we have achieved smoother walking compared to standard Isaac Lab learning methods. Please give it a try!
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We've open-sourced torobo_isaac_lab, an extension for NVIDIA Isaac Lab. By providing rewards that consider gait, we have achieved smoother walking compared to standard Isaac Lab learning methods. Please give it a try!

東京ロボティクス株式会社

11,361 views • 1 year ago

The wait is over. 🥁 NVIDIA Isaac Sim 5.0 and Isaac Lab 2.2 are now generally available. Dive in and start to simulate, train, and validate your AI-powered robots with these new key features: ⚡ Instant GPU access via NVIDIA Brev 🤖 3D #GaussianSplatting with NVIDIA Omniverse NuRec libraries 📈 Policy evaluation in Isaac Lab and more. Get started 👉 #NVIDIARobotics #SIGGRAPH2025
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The wait is over. 🥁 NVIDIA Isaac Sim 5.0 and Isaac Lab 2.2 are now generally available. Dive in and start to simulate, train, and validate your AI-powered robots with these new key features: ⚡ Instant GPU access via NVIDIA Brev 🤖 3D #GaussianSplatting with NVIDIA Omniverse NuRec libraries 📈 Policy evaluation in Isaac Lab and more. Get started 👉 #NVIDIARobotics #SIGGRAPH2025

NVIDIA Robotics

35,787 views • 1 year ago

Skild AI's new S1 robot foundation model helps robots learn previously unseen tasks from a single video demonstration. 🤖 See how NVIDIA technology supports S1 from training and simulation to real-world deployment. Learn more ➡️
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Skild AI's new S1 robot foundation model helps robots learn previously unseen tasks from a single video demonstration. 🤖 See how NVIDIA technology supports S1 from training and simulation to real-world deployment. Learn more ➡️

NVIDIA Robotics

36,398 views • 1 month ago

Can we make Transformers better and more efficient for robot learning? Excited to introduce Body Transformer (BoT), an architecture that leverages robot embodiment in the attention mechanism, by treating it as a graph of sensors and actuators.
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Can we make Transformers better and more efficient for robot learning? Excited to introduce Body Transformer (BoT), an architecture that leverages robot embodiment in the attention mechanism, by treating it as a graph of sensors and actuators.

Carlo Sferrazza

60,714 views • 2 years ago

just made it possible to evaluate generalist robotics models like Octo at 60-100x real world evaluation speeds via gpu simulation and rendering (~10x faster than original cpu sim code). All videos below are from our open source ManiSkill GPU sim!
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just made it possible to evaluate generalist robotics models like Octo at 60-100x real world evaluation speeds via gpu simulation and rendering (~10x faster than original cpu sim code). All videos below are from our open source ManiSkill GPU sim!

Stone Tao

13,456 views • 2 years ago

Robots won’t scale if every failure brings them to a halt. We train a generalist Transformer policy across a wide range of hardware impairments, enabling it to adapt to the robot’s changing capabilities at runtime through whole-body in-context learning. Meet Light REACT.
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Robots won’t scale if every failure brings them to a halt. We train a generalist Transformer policy across a wide range of hardware impairments, enabling it to adapt to the robot’s changing capabilities at runtime through whole-body in-context learning. Meet Light REACT.

LightOrigins

12,558 views • 1 month ago

A preview Into the future of #quantum-GPU computing: At GTC Washington, D.C., we announced NVIDIA NVQLink, an open system architecture for tightly coupling the extreme performance of GPU computing with quantum processors to build accelerated quantum supercomputers. In the expo hall, accelerated quantum computing was a centerpiece of the NVIDIA booth. See our live blog:
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A preview Into the future of #quantum-GPU computing: At GTC Washington, D.C., we announced NVIDIA NVQLink, an open system architecture for tightly coupling the extreme performance of GPU computing with quantum processors to build accelerated quantum supercomputers. In the expo hall, accelerated quantum computing was a centerpiece of the NVIDIA booth. See our live blog:

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55,458 views • 1 year ago

Using large-scale GPU parallelized reinforcement learning in Isaac Sim, we are able to obtain a robust whole-body controller for Taku optimized for precise loco-manipulation.
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Using large-scale GPU parallelized reinforcement learning in Isaac Sim, we are able to obtain a robust whole-body controller for Taku optimized for precise loco-manipulation.

Dyna Robotics

85,952 views • 1 month ago

Our New Open-Source Quadruped Robot "MEVIUS2" has been accepted to IEEE Robotics and Automation Practice (RA-P)! "MEVIUS2: Practical Open-Source Quadruped Robot with Sheet Metal Welding and Multimodal Perception" Threads👇
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Our New Open-Source Quadruped Robot "MEVIUS2" has been accepted to IEEE Robotics and Automation Practice (RA-P)! "MEVIUS2: Practical Open-Source Quadruped Robot with Sheet Metal Welding and Multimodal Perception" Threads👇

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26,472 views • 7 months ago