install-isaaclab

작성자: nvidia

Install Isaac Lab for Isaac Sim-backed workflows or Isaac Lab 3.0+ kit-less/Newton workflows, then verify the setup. Use when the user asks to install, set up,…

npx skills add https://github.com/nvidia/omniperf --skill install-isaaclab

Install Isaac Lab

Repo: https://github.com/isaac-sim/IsaacLab.git Modes: Isaac Sim-backed full install, or Isaac Lab 3.0+ kit-less/Newton install.

Choose Install Mode

  • Full Isaac Sim-backed install: use for PhysX, ROS, URDF/MJCF importers, Omniverse visualization, and most benchmarking/profiling work. This requires Isaac Sim first.
  • Kit-less/Newton install (Isaac Lab 3.0+): use only when the user explicitly wants core Isaac Lab/Newton workflows that do not require Isaac Sim features.

If the user does not specify, default to the full Isaac Sim-backed install for performance benchmarking.

Kit-less / Newton Quick Install (Isaac Lab 3.0+)

Use this path only when Isaac Sim features are not needed.

git clone https://github.com/isaac-sim/IsaacLab.git
cd IsaacLab
git checkout develop   # or a specific commit/tag

# Installs core Isaac Lab packages plus the Newton backend.
./isaaclab.sh -i

Do not use this mode for PhysX, ROS, URDF/MJCF importers, or Omniverse visualizers.

Full Isaac Sim-Backed Install

Step 1: Install Isaac Sim

See the install-isaacsim skill. You need a working Isaac Sim before proceeding.

Step 2: Install an Environment Manager (if not present)

Conda is the most common path; uv is also supported by recent Isaac Lab versions.

# Prefer an existing environment manager.
command -v conda >/dev/null && echo "CONDA OK" || echo "CONDA MISSING"
command -v uv >/dev/null && echo "UV OK" || echo "UV MISSING (needed for ./isaaclab.sh -u)"

If neither conda nor uv is available, ask before installing one. Do not run conda init from this skill; it mutates user shell startup files. If the user approves a local Miniconda install, use a non-mutating activation path:

wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O /tmp/miniconda.sh
bash /tmp/miniconda.sh -b -p "$HOME/miniconda3"
source "$HOME/miniconda3/etc/profile.d/conda.sh"
conda --version

Step 3: Clone Isaac Lab

git clone https://github.com/isaac-sim/IsaacLab.git
cd IsaacLab
git checkout develop   # or a specific commit/tag

Step 4: Link Isaac Sim

# If Isaac Sim was source-built:
ln -s /path/to/IsaacSim/_build/linux-x86_64/release _isaac_sim

# If Isaac Sim was pip-installed, the link may not be needed —
# isaaclab.sh should detect the pip installation automatically.
# Check: ./isaaclab.sh -p -c "import isaacsim; print('OK')"

Step 5: Create Environment

# Choose one. Default environment name is env_isaaclab if omitted.
# Conda:
./isaaclab.sh -c env_isaaclab

# uv on supported versions:
./isaaclab.sh -u env_isaaclab

This creates an environment with the correct Python version and base dependencies. The default name (if you omit the argument) is env_isaaclab.

Note: You may need to accept conda channel TOS first if this is a fresh install:

conda tos accept --override-channels --channel https://repo.anaconda.com/pkgs/main
conda tos accept --override-channels --channel https://repo.anaconda.com/pkgs/r

Step 6: Install Dependencies

# Conda
source "$(conda info --base)/etc/profile.d/conda.sh"
conda activate env_isaaclab

# Or uv
# source env_isaaclab/bin/activate

./isaaclab.sh -i

Important: Make sure to run these commands in bash (not sh). The source builtin and conda activate require bash.

Verify

source "$(conda info --base)/etc/profile.d/conda.sh"
conda activate env_isaaclab
cd IsaacLab

# Quick import check
./isaaclab.sh -p -c "import isaaclab; print('OK')"

# Run a minimal benchmark (few frames)
./isaaclab.sh -p scripts/benchmarks/benchmark_non_rl.py \
  --task=Isaac-Cartpole-Direct-v0 --viz none --num_frames 10 --num_envs=16

Note: --headless is deprecated in recent versions. Omit --viz for headless mode, or use --viz none to force headless when visualizers are configured.

Day-to-Day Activation

source "$(conda info --base)/etc/profile.d/conda.sh"
conda activate env_isaaclab
cd IsaacLab

Common Issues

./isaaclab.sh -i fails finding Isaac Sim

Make sure the _isaac_sim symlink points to a valid Isaac Sim build/install:

ls -la _isaac_sim/
# Should show Isaac Sim files (python.sh, kit/, exts/, etc.)

Conda env already exists

conda env remove -n env_isaaclab
./isaaclab.sh -c env_isaaclab

GPU not found / CUDA errors

Verify NVIDIA driver and CUDA:

nvidia-smi
python -c "import torch; print(torch.cuda.is_available())"

nvidia의 다른 스킬

compileiq-debug
nvidia
Use when something is wrong: Search() hangs, all evaluations return INVALID_SCORE, scores aren't improving, every config returns the same number, ptxas errors…
official
create-github-pr
nvidia
gh CLI를 사용하여 GitHub 풀 리퀘스트를 생성합니다. 사용자가 새 PR을 만들거나, 코드 리뷰를 제출하거나, 풀 리퀘스트를 열고자 할 때 사용합니다. 트리거 키워드 -…
official
diagnose-perf
nvidia
First-responder performance triage for Isaac Sim and Isaac Lab. Identifies bottleneck category (GPU-bound, CPU-bound, VRAM, loading) using nvidia-smi and…
official
eagle3-review-logs
nvidia
Review EAGLE3 pipeline experiment logs from the launcher's experiments/ directory. Summarizes pass/fail status for all 4 tasks, diagnoses failures with root…
official
nemoclaw-maintainer-cross-issue-sweep
nvidia
다른 열린 이슈들을 스캔하여 주어진 PR이 함께 수정하거나 실수로 망가뜨릴 수 있는 이슈를 찾습니다. 인접 수정 기회와 모순 위험을 file:line…과 함께 출력합니다.
official
karpathy-guidelines
nvidia
일반적인 LLM 코딩 실수를 줄이기 위한 행동 지침입니다. 코드 작성, 검토 또는 리팩토링 시 과도한 복잡성을 피하고 정밀한 변경을 위해 사용하세요.
official
fhir-basics
nvidia
에이전트에게 FHIR R4 API의 작동 방식, 사용 가능한 리소스, 검색 매개변수를 사용한 쿼리 방법, 모든 응답 형식을 올바르게 파싱하는 방법을 가르칩니다…
official
underdeclared-agent
nvidia
A helpful assistant agent
official