June 30, 2026
Ken Suzuki
Technology

Adding Isaac Lab to an Existing Isaac Sim (pip Install) Environment

A step-by-step record of installing Isaac Lab directly into a pip/conda-based Isaac Sim 5.1.0 environment — without Docker or the Omniverse Launcher that most official guides assume.

NVIDIAIsaac SimIsaac LabRoboticsUbuntu
Adding Isaac Lab to an Existing Isaac Sim (pip Install) Environment

Introduction

NVIDIA Isaac Lab is a robot learning framework built on top of Isaac Sim, offering a rich set of tutorials and sample environments for reinforcement learning and imitation learning — covering arm, quadruped, and humanoid robots.

I finally got around to installing Isaac Lab on top of an existing Isaac Sim setup.

Most of the official documentation assumes Docker or the Omniverse Launcher as the installation path, but this article documents the actual steps for adding Isaac Lab directly to an existing pip/conda-based Isaac Sim 5.1.0 environment — along with verification that everything works.

Environment

Item Details
Machine RTX 5090 32 GB / Ubuntu 24.04
Python 3.11 (conda environment)
Isaac Sim 5.1.0 (installed via pip)
Isaac Lab GitHub main branch (as of 2026-06-02)

Why I Skipped Docker

The official Isaac Lab guide does cover Docker-based usage. The main benefits of that approach are environment reproducibility and keeping the host OS clean.

In my case, however:

  • Isaac Sim was already installed on the host via pip inside a conda environment
  • Isaac Lab is essentially a set of libraries that depend on Isaac Sim's Python environment, so adding it to the same conda environment is the simplest integration path
  • There's no need for extra configuration to handle GPU passthrough or X11 GUI forwarding through Docker

For these reasons, I went with a direct installation instead.


Installation Steps

1. Clone the Isaac Lab Repository

conda activate env_isaacsim
mkdir isaac
cd isaac
git clone https://github.com/isaac-sim/IsaacLab.git
cd IsaacLab/

A note on reproducibility: The main branch changes with each release. If you want to reproduce these exact steps, specify a tag when cloning or record the commit hash after cloning.

# Clone a specific tag (example)
git clone --branch v2.1.0 https://github.com/isaac-sim/IsaacLab.git

# Or record the commit hash after cloning
git log --oneline -1

This article used the main branch as of 2026-06-02.

2. Let Isaac Lab Discover the Existing pip-installed Isaac Sim

Isaac Lab auto-detects the Isaac Sim path when using the Omniverse Launcher version. With a pip install, Isaac Sim lives inside the same Python environment, so isaaclab.sh will pick it up from env_isaacsim automatically — no additional configuration required.

./isaaclab.sh --install

Running the default install with no extra options was all it took to resolve the dependencies.

3. Verify the Installation (Headless)

./isaaclab.sh -p scripts/tutorials/00_sim/create_empty.py --headless

A successful run produces the following log output:

[INFO]: Setup complete...

Verifying with a GUI Demo

Beyond the headless check, I also confirmed that GUI demos work. Isaac Lab ships with several sample environments — arms, quadrupeds, humanoids, and more. I launched the robot arm demo:

./isaaclab.sh -p scripts/demos/arms.py

The 3D viewport opened and I could watch multiple robot arms being simulated simultaneously.

Isaac Lab arms demo: multiple robot arms simulated at the same time


Summary

  • If Isaac Sim is already installed in a pip/conda environment, the simplest way to add Isaac Lab is to install it directly into the same environment — no Docker needed
  • Cloning the repository and running ./isaaclab.sh --install with no extra options is enough to set up all dependencies
  • A good workflow is to verify with a --headless tutorial script first, then launch a GUI demo like scripts/demos/arms.py to confirm the visual output

If you have already set up a conda environment for Isaac Sim, it's worth trying this approach before reaching for Docker.


References

Adding Isaac Lab to an Existing Isaac Sim (pip Install) Environment | Shirokuma.online