This project targets both control and robot learning research domains:
- Researchers in robotics and control can simulate their robots with familiar tools like Gazebo and URDF/SDF, without the need to rely on any middleware.
- Researchers in robot learning can quickly develop new robotic environments that can scale to hundreds of parallel instances.
We provide two related subprojects to each of these categories:
- ScenarIO provides APIs to interface with the robots.
- gym-ignition helps structuring environments compatible with OpenAI Gym, while minimizing boilerplate code and providing common rigid-body dynamics utilities.
Check the sections :ref:`What is ScenarIO <what_is_scenario>` and :ref:`What is gym-ignition <what_is_gym_ignition>` for more details, and visit :ref:`Motivations <motivations>` for an extended overview.
For a quick practical introduction, visit the :ref:`Getting Started <getting_started_scenario>` page.
If you use this project for your research, please check the FAQ about :ref:`how to give credit <faq_citation>`.
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.. toctree:: :hidden: :maxdepth: 1 :caption: What what/what_is_scenario what/what_is_gym_ignition
.. toctree:: :hidden: :maxdepth: 1 :caption: Why why/motivations why/why_scenario why/why_ignition_gazebo why/why_gym_ignition
.. toctree:: :hidden: :maxdepth: 1 :caption: Installation (How) installation/support_policy installation/stable installation/nightly installation/developer
.. toctree:: :hidden: :maxdepth: 1 :caption: Getting Started getting_started/scenario getting_started/manipulation getting_started/gym-ignition
.. toctree:: :hidden: :maxdepth: 2 :caption: ScenarIO C++ API: breathe/core breathe/gazebo
.. toctree:: :hidden: :maxdepth: 2 :caption: Python Packages apidoc/scenario/scenario.bindings apidoc/gym-ignition/gym_ignition apidoc/gym-ignition-environments/gym_ignition_environments
.. toctree:: :hidden: :maxdepth: 2 :caption: Information info/faq info/limitations