Isaac Lab is a unified and modular framework for robot learning that aims to simplify common workflows in robotics research (such as RL, learning from demonstrations, and motion planning). It is built upon NVIDIA Isaac Sim to leverage the latest simulation capabilities for photo-realistic scenes and fast and accurate simulation.

Please refer to our documentation page to learn more about the installation steps, features, tutorials, and how to set up your project with Isaac Lab.

What's New in Isaac Lab 2.1

New Features:

• Introducing high-quality human demonstrations using the Apple Vision Pro for teleoperation
• Support for bi-manual manipulation
• Randomization of USD features, including scale, color, and texture
• Sim-to-real tutorial for Whole Body Control (WBC) to accelerate robot learning
• Command-line tool (template generator) for creating Isaac Lab-based projects and tasks, simplifying project visibility and updates
• Predefined render settings for easy toggle between rendering modes

Improvements & Bug fixes:

• Added Quickstart Guide in documentation
• Fixed distributed training setup with conflicting devices
• Various bug fixes for tutorial scripts, recording functionality, RL wrappers and train/play scripts
• Documentation improvements and code refactoring

License

By pulling and using the container, you accept the terms and conditions of the NVIDIA Software License Agreement.

Sources for OSS packages used in this container can be found here.

Suggested readings:

• GitHub Repo
• Documentation
• Support