Repository organization

Repository organization#

IsaacLab
├── .vscode
├── CONTRIBUTING.md
├── CONTRIBUTORS.md
├── LICENSE
├── isaaclab.bat
├── isaaclab.sh
├── pyproject.toml
├── README.md
├── docs
├── docker
├── source
│   ├── isaaclab                   # core framework
│   ├── isaaclab_physx             # PhysX backend (requires Isaac Sim)
│   ├── isaaclab_ovphysx           # standalone PhysX backend (requires ovphysx)
│   ├── isaaclab_ov                # OVRTX renderer backend (requires ovrtx)
│   ├── isaaclab_newton            # Newton backend (kit-less)
│   ├── isaaclab_assets            # pre-configured robot & sensor assets
│   ├── isaaclab_tasks             # pre-built RL/IL environments
│   ├── isaaclab_tasks_experimental # Warp-accelerated environments
│   ├── isaaclab_rl                # RL library wrappers
│   ├── isaaclab_mimic             # imitation learning & data generation
│   ├── isaaclab_teleop            # teleoperation & XR
│   ├── isaaclab_visualizers       # external visualizer backends
│   ├── isaaclab_contrib           # community-contributed extensions
│   ├── isaaclab_experimental      # Warp-accelerated manager and environment variants
│   ├── extensions                 # legacy Omniverse extension wrappers
│   └── standalone                 # standalone tutorials & workflows
├── scripts
│   ├── benchmarks
│   ├── demos
│   ├── environments
│   ├── imitation_learning
│   ├── reinforcement_learning
│   ├── sim2sim_transfer
│   ├── tools
│   └── tutorials
├── tools
└── VERSION

Isaac Lab supports the PhysX and Newton physics engines through backend packages. The default PhysX path runs through Isaac Sim, while ovphysx supports standalone PhysX workflows without launching Isaac Sim and Newton provides a Warp-native kit-less backend. The source directory contains all packages that compose Isaac Lab, while scripts contains standalone Python applications for training, evaluation, and tooling. See Multi-Backend Architecture for details on the backend system, and Isaac Lab Ecosystem for a full package-layer overview.

Submodules#

The packages under source/ are installed as Python packages using setuptools. They are organized into three groups:

Core, physics backends, and renderers

  • isaaclab: The core framework. Provides sim (simulation context and configuration), InteractiveScene, asset and sensor base classes and factory interfaces (assets, sensors), environment base classes (envs), the manager system (managers), composable MDP term library (mdp), actuator models (actuators), low-level controllers (controllers), procedural terrain generation (terrains), and human-input device support (devices).

  • isaaclab_physx: PhysX-backed implementations of articulations, rigid bodies, deformable objects, Fabric views, the Isaac RTX renderer, and USD spawners. Requires Isaac Sim.

  • isaaclab_ovphysx: Standalone PhysX backend variant using ovphysx and the TensorBindingsAPI. Requires the ovphysx package and can run without launching Isaac Sim.

  • isaaclab_ov: OVRTX renderer backend for RTX-based tiled camera rendering. Requires the ovrtx package and can run without Isaac Sim.

  • isaaclab_newton: Newton-backed implementations of articulations, rigid bodies, rigid object collections, cameras, USD spawners, and the Warp renderer. Supports kit-less installation without Isaac Sim.

Tasks and assets

  • isaaclab_assets: Pre-configured configclass dataclasses for a wide range of robots (Franka, Unitree, ANYmal, Spot, Allegro, humanoids, quadcopters, and more) and sensors (Velodyne, GelSight).

  • isaaclab_tasks: Registered gymnasium environments for reinforcement and imitation learning, organized as manager-based and direct tasks across locomotion, manipulation, navigation, and classic control domains.

  • isaaclab_tasks_experimental: Experimental task implementations under active development, not yet part of the stable task suite.

Optional Additions

  • isaaclab_rl: Thin wrappers that adapt Isaac Lab environments to the interfaces expected by RSL-RL, skrl, Stable Baselines 3, and RL Games.

  • isaaclab_mimic: APIs and pre-configured environments for data generation and imitation learning, including cuRobo-based motion planners and a dataset-generation pipeline.

  • isaaclab_teleop: Teleoperation session orchestration with OpenXR / CloudXR support, device retargeters for manipulators and humanoids, and gamepad / spacemouse / keyboard input.

  • isaaclab_visualizers: Supplementary visualizer backends (Isaac Sim Kit, Newton, Rerun, Viser) that work with any physics backend.

  • isaaclab_contrib: Community-contributed features: multirotor assets, TacSL visuo-tactile sensors, drone thrust controllers, and more.

  • isaaclab_experimental: Pre-production core experiments including Warp-accelerated manager and environment variants.

Standalone#

The scripts directory contains standalone Python applications. They are structured as follows:

  • benchmarks: Scripts for benchmarking different framework components.

  • demos: Demo applications that showcase the core framework isaaclab.

  • environments: Scripts for running environments defined in isaaclab_tasks with different agents (random policy, zero-action policy, teleoperation, scripted state machines).

  • imitation_learning: Applications for training and evaluating policies with imitation learning libraries (e.g. robomimic).

  • reinforcement_learning: Applications for training and evaluating policies with RL libraries (e.g. rsl_rl, rl_games, sb3, skrl).

  • sim2sim_transfer: Scripts for transferring policies trained in one simulator to another.

  • tools: Applications for using framework tools such as converting assets and generating datasets.

  • tutorials: Step-by-step tutorials for using the APIs provided by the framework.