NVIDIA Isaac Lab

NVIDIA Isaac™ Lab is an open-source, unified framework for robot learning designed to help train robot policies. 

It’s built on NVIDIA Isaac Sim™, delivering high-fidelity physics simulation using NVIDIA PhysX® and physically based rendering with NVIDIA RTX™. This bridges the gap between high-fidelity simulation and perception-based robot training, helping developers and researchers build more robots, more efficiently.

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Documentation


How Isaac Lab Works

Isaac Lab’s modular architecture and NVIDIA GPU-based parallelization make it ideal for building robot policies that cover a wide range of embodiments, including humanoid robots, manipulators, and autonomous mobile robots (AMRs).

This gives you a comprehensive framework for robot learning, covering everything from environment setup to policy training. It supports both imitation and reinforcement learning methods. Plus, you can further customize and extend its capabilities with a variety of physics engines, such as PhysX, NVIDIA Warp, and MuJoCo.  

Isaac Lab is also the foundational robot learning framework of the NVIDIA Isaac GR00T platform.

Isaac Lab’s comprehensive platform for robot learning and robot policy building

Introductory Resources

A Simulation Framework for Multi-Modal Robot Learning

See how Isaac Lab’s combination of advanced simulation capabilities and data-center scale execution will help unlock breakthroughs in robotics research.

Next-Generation Open-Source Physics Simulation Engine

Built on Warp and OpenUSD, Newton is optimized for advancing robot learning and development and compatible with learning frameworks such as MuJoCo Playground or Isaac Lab.

Isaac Lab Courses

Explore the fundamentals of robot learning and Isaac Lab, a powerful tool for developing robotic applications.

Isaac Lab Office Hours

Stay informed with our recurring office hours that cover in-depth topics with experts answering questions about Isaac Lab.


Key Features

Two robotic hands rolling a ball showing flexible robot learning

Flexible Robot Learning

Customize workflows with robot training environments, tasks, learning techniques, and the ability to integrate custom libraries (e.g,. skrl, RLLib, rl_games, and more).

A robotic hand is programmed to pick up a teddy bear toy

Reduced Sim-to-Real Gap

The GPU-accelerated PhysX version provides accurate, high-fidelity physics simulations. These include support for deformables that allows for more realistic modeling of robot interactions with the environment.

Unified Representation

Discover easy customization and addition of new environments, robots, and sensors with OpenUSD through Isaac Lab’s modular design. 


Get Started With Isaac Lab

Download

Get started with the latest version of Isaac Lab by following the installation guides on GItHub .

Tutorials

Access the step-by-step guide to help understand and use various features of the framework.

Start Your Learning Path

Explore advanced concepts in robot learning, gain practical skills, and learn how you can streamline your development processes with Isaac Lab.


Newton, the Next-Generation Open-Source Physics Simulation Engine

Newton is an open-source, GPU-accelerated, and extensible physics engine, co-developed by Google DeepMind and Disney Research, and managed by the Linux Foundation. Built on Warp and OpenUSD, Newton is optimized for robotics and compatible with learning frameworks such as MuJoCo Playground or Isaac Lab. Newton Beta is now available to use.

Get Started on Newton
Newton Physics Engine logo

Starter Kits

View more tutorials and how-to guides in the documentation.

Accelerate Robot Learning

Choose from reinforcement learning and imitation learning to train AI robots. Easily bring your custom libraries, and use the direct agent-environment or hierarchical-manager development workflows.

Enable Perception in the Loop

Tiled rendering reduces rendering time by consolidating input from multiple cameras into a single large image. With a streamlined API for handling vision data, the rendered output directly serves as observational data for simulation learning.

Scale With Multi-GPU and Multi-Node Training

Scale up training of cross-embodied models for complex reinforcement learning environments across multiple GPUs and nodes. Deploy locally and on the cloud (AWS, GCP, Azure, and Alibaba Cloud) by integrating with NVIDIA OSMO.

Accurate High-Fidelity Physics Simulation and Rendering in Omniverse

Tap into the latest GPU-accelerated PhysX version through Isaac Lab, including support for deformables, ensuring quick and accurate physics simulations augmented by domain randomizations.


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RTX PRO Server—the Best Platform for Industrial and Physical AI

NVIDIA RTX PRO Server accelerates every industrial digitalization, robot simulation, and synthetic data generation workload.

Learn More

Isaac Lab Learning Library

Research

A GPU Accelerated Simulation Framework For Multi-Modal Robot Learning

NVIDIA Isaac Lab

We present Isaac Lab, the natural successor to Isaac Gym, which extends the paradigm of GPU-native robotics simulation into the era of large-scale multi-modal learning.

Tech Blog

Streamline Robot Learning with Whole-Body Control and Enhanced Teleoperation in NVIDIA Isaac Lab 2.3

NVIDIA Isaac Lab

The latest version of Isaac Lab 2.3, in early developer preview, improves humanoid robot capabilities with advanced whole-body control, enhanced imitation learning, and better locomotion.

Tech Blog

Quadruped Robot Locomotion and Multiphysics Simulation Using Newton in NVIDIA Isaac Lab

NVIDIA Isaac Lab

Walks through how to train a quadruped robot to move from one point to another and how to set up a multiphysics simulation with an industrial manipulator to fold clothes. This tutorial uses Newton within NVIDIA Isaac Lab.


Ecosystem

Our industry partners and collaborators are integrating NVIDIA Isaac Lab and accelerated computing into their platforms and solutions.

 NVIDIA industry partner - 1X
NVIDIA industry partner - AgiBot
NVIDIA industry partner - Agility
NVIDIA industry partner - Boston Dynamics
NVIDIA industry partner - Field AI
NVIDIA industry partner - Fourier
NVIDIA industry partner - Galbot
NVIDIA industry partner - General Robotics
 NVIDIA industry partner - RAI Institute
 NVIDIA industry partner - Skild AI
 NVIDIA industry partner - UCR
 NVIDIA industry partner - X-Humanoid

More Resources

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Explore the Community

Get Training and Certification

Join the Program for Startups


Latest Isaac Lab News

Get started with NVIDIA Isaac Lab today.

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FAQs

The Isaac Lab framework is open-sourced under the BSD-3-Clause license.

Isaac Sim is a comprehensive robotics simulation platform built on NVIDIA Omniverse™ that provides high-fidelity simulation with advanced physics and photorealistic rendering. It focuses on synthetic data generation (SDG) and testing and validation (SIL/HIL), and is a reference template for custom robotics simulators.

In contrast, Isaac Lab is a lightweight, open-source framework built on top of Isaac Sim, specifically optimized for robot learning workflows and designed to simplify common tasks in robotics research like reinforcement learning, imitation learning, and motion planning.

If you’re an existing NVIDIA Isaac Gym (predecessor of Isaac Lab) user, we recommend migrating to Isaac Lab to ensure you have access to the latest advancements in robot learning and a powerful development environment to accelerate your robot training efforts. Check out the migration guide from Isaac Gym environments to Isaac Lab.

Yes, Isaac Lab and MuJoCo are complementary. MuJoCo's ease of use and lightweight design allow for rapid prototyping and deployment of policies and Isaac Lab can complement it when you want to create more complex scenes, scaling massively parallel environments with GPUs and high-fidelity sensor simulations with RTX rendering. NVIDIA and MuJoCo are actively exploring advancing technical collaborations, stay tuned for future announcements.