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Isaac Lab
NVIDIA robot learning framework on Isaac Sim for large-scale parallel training and sim-to-real.
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MuJoCo
Classic physics engine widely used in robot RL and control research — lightweight and accurate.
Why: Default simulator in robot research with a mature ecosystem
Overview
MuJoCo (Multi-Joint dynamics with Contact) is the default physics engine for much of robot learning research. It is fast, accurate for contact-rich manipulation, and has mature Python bindings plus a large ecosystem of environments (Meta-World, robosuite, many custom envs).
DeepMind open-sourced MuJoCo, which accelerated adoption. Researchers use it when they need reproducible rigid-body dynamics without the weight of a full game-engine stack. It is not trying to be a photoreal renderer; pair it with simple cameras or external renderers when vision matters.
If you are implementing a new RL algorithm or a small manipulation study, MuJoCo is often the lowest-friction physics core.
Who it is for
RL / control researchers; anyone building custom sim envs; students learning robot dynamics.
Key highlights
- Industry-standard contact dynamics for research
- Lightweight compared to full digital-twin stacks
- Huge ecosystem of envs and teaching materials
- Official Python bindings (mujoco) actively maintained
- Great baseline before scaling to GPU-native simulators
When to use
- Algorithm research and teaching
- Contact-rich tabletop tasks with modest visual needs
- You want fast iteration on a laptop or single GPU workstation
When not to use
- You need photoreal indoor scenes at scale (Isaac / Habitat)
- Soft-body / fluid-dominant phenomena are core to the task
- You require certified digital-twin pipelines for industry deployment
Getting started
- 1Install the official `mujoco` Python package and open a sample MJCF model.
- 2Learn MJCF structure: bodies, joints, actuators, sensors.
- 3Wrap a Gymnasium-compatible env for your task.
- 4Log contacts and joint limits — most bugs hide there.
- 5Only then plug in RL or imitation learners.
Install / setup
pip
pip install mujoco
Papers & reading
How it compares
Default research physics engine: lighter than Isaac, more standard than PyBullet for modern IL papers.
Caveats & pitfalls
- MJCF authoring has a learning curve; start from existing models.
- Visual appearance is basic unless you invest in assets/rendering.
- Different forks/bindings historically caused confusion — prefer official package.
Content reviewed 2026-07-23