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.. code-block:: bash
IsaacLab
├── .vscode
├── CONTRIBUTING.md
├── CONTRIBUTORS.md
├── LICENSE
├── isaaclab.bat
├── isaaclab.sh
├── pyproject.toml
├── README.md
├── docs
├── docker
├── source
│ ├── isaaclab
│ ├── isaaclab_assets
│ ├── isaaclab_mimic
│ ├── isaaclab_rl
│ └── isaaclab_tasks
├── scripts
│ ├── benchmarks
│ ├── demos
│ ├── environments
│ ├── imitation_learning
│ ├── reinforcement_learning
│ ├── tools
│ ├── tutorials
├── tools
└── VERSION
Isaac Lab is built on the same back end as Isaac Sim. As such, it exists as a collection of **extensions** that can be assembled into **applications**.
The ``source`` directory contains the majority of the code in the repository and the specific extensions that compose Isaac lab, while ``scripts`` containing python scripts for launching customized standalone apps (Like our workflows).
These are the two primary ways of interacting with the simulation and Isaac lab supports both!
Checkout this `Isaac Sim introduction to workflows <https://docs.isaacsim.omniverse.nvidia.com/latest/introduction/workflows.html>`__ for more details.
Extensions
~~~~~~~~~~
The extensions that compose Isaac Lab are kept in the ``source`` directory. To simplify the build process, Isaac Lab directly use `setuptools <https://setuptools.readthedocs.io/en/latest/>`__. It is strongly recommend that you adhere to this process if you create your own extensions using Isaac Lab.
The extensions are organized as follows:
* **isaaclab**: Contains the core interface extension for Isaac Lab. This provides the main modules for actuators,
objects, robots and sensors.
* **isaaclab_assets**: Contains the extension with pre-configured assets for Isaac Lab.
* **isaaclab_tasks**: Contains the extension with pre-configured environments for Isaac Lab.
* **isaaclab_mimic**: Contains APIs and pre-configured environments for data generation for imitation learning.
* **isaaclab_rl**: Contains wrappers for using the above environments with different reinforcement learning agents.
Standalone
~~~~~~~~~~
The ``scripts`` directory contains various standalone applications written in python.
They are structured as follows:
* **benchmarks**: Contains scripts for benchmarking different framework components.
* **demos**: Contains various demo applications that showcase the core framework :mod:`isaaclab`.
* **environments**: Contains applications for running environments defined in :mod:`isaaclab_tasks` with
different agents. These include a random policy, zero-action policy, teleoperation or scripted state machines.
* **tools**: Contains applications for using the tools provided by the framework. These include converting assets,
generating datasets, etc.
* **tutorials**: Contains step-by-step tutorials for using the APIs provided by the framework.
* **workflows**: Contains applications for using environments with various learning-based frameworks. These include different
reinforcement learning or imitation learning libraries.
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