This National Robotics Week, NVIDIA highlighted the pioneering technologies that are shaping the future of intelligent machines and driving progress across manufacturing, healthcare, logistics and more.Advancements in robotics simulation and robot learning are driving this fundamental shift in the industry. Plus, the emergence of world foundation models is accelerating the evolution of AI-enabled robots capable of adapting to dynamic and complex scenarios.
For example, by providing robot foundation models like NVIDIA GR00T N1, frameworks such as NVIDIA Isaac Sim and Isaac Lab for robot simulation and training, and synthetic data generation pipelines to help train robots for diverse tasks, the NVIDIA Isaac and GR00T platforms are empowering researchers and developers to push the boundaries of robotics.
Read on to learn the latest on physical AI, which enables machines to perceive, plan and act with greater autonomy and intelligence in real-world environments.
The Latest on Physical AI and Robotics, as Revealed at NVIDIA GTC Watch on-demand sessions from the NVIDIA GTC global AI conference to catch up on recent breakthroughs in robotics, showcased by leading experts in the field.
In his keynote, NVIDIA founder and CEO Jensen Huang announced NVIDIA Isaac GR00T N1, the world's first open, fully customizable foundation model for generalized humanoid robot reasoning and skills. He also introduced Newton, an open-source, extensible physics engine being developed by NVIDIA, Google DeepMind and Disney Research to advance robot learning and development.
Developers, researchers and enthusiasts can explore the following to learn more:
An Introduction to Building Humanoid Robots: Learn about NVIDIA Isaac GR00T, a platform for developing AI-powered humanoids.
Humanoid Developer Day: Dive into the latest breakthroughs in robotics, foundation models and simulation.
Physical AI and Robotics Playlist: Discover how accelerated computing and generative AI are transforming embodied AI.
Edge Computing Playlist: Learn how to take advantage of the NVIDIA edge computing platform to achieve low-latency and high-performance AI for robotics.
Get Started in Robotics With Free Courses and Open-Source Data Those looking to dive into robotics development can get started with NVIDIA's free Robotics Fundamentals Learning Path. This series of self-paced NVIDIA Deep Learning Institute (DLI) courses covers foundational robotics concepts and essential workflows in simulation and robot learning. Each course provides hands-on training across the NVIDIA Isaac platform, including Isaac ROS, Isaac Sim and Isaac Lab.
DLI training labs at NVIDIA GTC 2025. This year at GTC, NVIDIA hosted in-person training labs for robotics developers, which are now available online. They include:
Develop, Simulate and Deploy Robot Intelligence With Scaled Foundations
Generating High-Quality Motion Data for Robotics With MobilityGen
Software-in-the-Loop Testing for Robots With OpenUSD, Isaac Sim and ROS
These courses will be available soon:
An Introduction to NVIDIA Cosmos for Physical AI
Imitation Learning Techniques Using NVIDIA Isaac Lab and Apple Vision Pro
Accelerating ROS 2 With NVIDIA GPU-Powered Libraries and AI Models
NVIDIA also released a free, open-source physical AI dataset comprising commercial-grade, pre-validated data to help researchers and developers kickstart their projects. The initial dataset offers 15 terabytes of data representing more than 320,000 trajectories for robotics training and 1,000 Universal Scene Description (OpenUSD) assets, including those that are SimReady.
Access the NVIDIA Physical AI Dataset on Hugging Face.
Scaled Foundations Streamlines the Transition From Simulation to Real-World Application Robots have the potential to automate and scale difficult and repetitive tasks. However, programming robots to perform these tasks safely has traditionally been challenging, costly and specialized. Scaled Foundations, a member of the NVIDIA Inception program for cutting-edge startups, is lowering the barrier to entry with its GRID platform.
By integrating NVIDIA Isaac Sim into GRID, Scaled Foundations provides users with an opportunity to fast-track the development and deployment of advanced robotic AI solutions across new robot types. Developers and students can access state-of-the-art tools to develop, simulate and deploy robot AI systems - entirely inside a browser.
Access, build and manage seamless robot intelligence right from your browser.
Learn more about how to deploy solutions using Scaled Foundations' GRID platform by watching the NVIDIA GTC session, Introduction to Robot Simulation: Learn How to Develop, Simulate and Deploy Scalable Robot Intelligence.
Spotlight on Wheeled Lab: Advancing Simulation-to-Reality Robotics With NVIDIA Isaac Lab Wheeled Lab, a research project from the University of Washington, is bringing simulation-to-reality robotics to low-cost, open-source platforms.
Wheeled Lab, integrated with NVIDIA Isaac Lab - a unified framework for robot learning - enables reinforcement learning models to train wheeled robots for complex tasks like controlled drifting, obstacle avoidance, elevation traversal and visual navigation. This pipeline uses domain randomization, sensor simulation and end-to-end learning to bridge the gap between simulated training and real-world deployment, all while ensuring zero-shot simulation-to-reality transfer.
Left: Drift policy. Right: Training in Isaac Lab simulation.
The entire stack - spanning simulation, training and deployment - is fully open source, giving developers the freedom to iterate, modify policies and experiment with reinforcement learning techniques in a reproducible environment.
Left: Drift policy. Right: Training in Isaac Lab simulation.
Get started with the code on GitHub.
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