Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Framework for developing OpenAI Gym robotics environments simulated with Ignition Gazebo
| Date | Stars |
|---|---|
| 2026-07-25 | 251 |
| 2026-07-28 | 251 |
| 2026-07-30 | 251 |
| 2026-08-06 | 251 |
Today
— stars today
This week
— stars this week
This month
— stars this month
Momentum
0.0
growth rate 0.00%/day
<p align="center">
<h1 align="center">gym-ignition</h1>
</p>
<div align="center">
<table>
<tbody>
<tr>
<td align="center">
<a href="https://github.com/robotology/gym-ignition/actions">
<img src="https://github.com/robotology/gym-ignition/workflows/CI/CD/badge.svg" alt="CICD" />
</a>
<a href="https://github.com/robotology/gym-ignition/actions">
<img src="https://github.com/robotology/gym-ignition/workflows/Docker%20Images/badge.svg" alt="Docker Images" />
</a>
<a href="https://www.codacy.com/gh/robotology/gym-ignition/dashboard?utm_source=github.com&utm_medium=referral&utm_content=robotology/gym-ignition&utm_campaign=Badge_Grade">
<img src="https://api.codacy.com/project/badge/Grade/5536b05f8be94483b64ee883e7170a39" alt="Codacy Badge" />
</a>
</td>
</tr>
<tr>
<td align="center">
<a href="https://pypi.org/project/gym-ignition/">
<img src="https://img.shields.io/pypi/v/gym-ignition.svg" />
</a>
<a href="https://pypi.org/project/gym-ignition/">
<img src="https://img.shields.io/pypi/pyversions/gym-ignition.svg" />
</a>
<a href="https://pypi.org/project/gym-ignition/">
<img src="https://img.shields.io/pypi/status/gym-ignition.svg" />
</a>
<a href="https://pypi.org/project/gym-ignition/">
<img src="https://img.shields.io/pypi/format/gym-ignition.svg" />
</a>
<a href="https://pypi.org/project/gym-ignition/">
<img src="https://img.shields.io/pypi/l/gym-ignition.svg" />
</a>
</td>
</tr>
</tbody>
</table>
</div>
> ⚠️ **Warning** ⚠️
>
> This project is no longer actively maintained, and development has stalled.
> For an in-depth description of the current status and actionable steps to revive development, please consult [robotology/gym-ignition#430]([url](https://github.com/robotology/gym-ignition/issues/430)).
||||
|:---:|:---:|:---:|
| ![][pendulum] | ![][panda] | ![][icub] |
[icub]: https://user-images.githubusercontent.com/469199/99262746-9e021a80-281e-11eb-9df1-d70134b0801a.png
[panda]: https://user-images.githubusercontent.com/469199/99263111-0cdf7380-281f-11eb-9cfe-338b2aae0503.png
[pendulum]: https://user-images.githubusercontent.com/469199/99262383-321fb200-281e-11eb-89cc-cc31f590daa3.png
## Description
**gym-ignition** is a framework to create **reproducible robotics environments** for reinforcement learning research.
It is based on the [ScenarIO](scenario/) project which provides the low-level APIs to interface with the Ignition Gazebo simulator.
By default, RL environments share a lot of boilerplate code, e.g. for initializing the simulator or structuring the classes
to expose the `gym.Env` interface.
Gym-ignition provides the [`Task`](python/gym_ignition/base/task.py) and [`Runtime`](python/gym_ignition/base/runtime.py)
abstractions that help you focusing on the development of the decision-making logic rather than engineering.
It includes [randomizers](python/gym_ignition/randomizers) to simplify the implementation of domain randomization
of models, physics, and tasks.
Gym-ignition also provides powerful dynamics algorithms compatible with both fixed-base and floating-based robots by
exploiting [robotology/idyntree](https://github.com/robotology/idyntree/) and exposing
[high-level functionalities](python/gym_ignition/rbd/idyntree).
Gym-ignition does not provide out-of-the-box environments ready to be used.
Rather, its aim is simplifying and streamlining their development.
Nonetheless, for illustrative purpose, it includes canonical examples in the
[`gym_ignition_environments`](python/gym_ignition_environments) package.
Visit the [website]Excerpt of 5,582 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:b4eb0a387d981389, topic:robotics, topic:simulation, desc:robotics
matched fp:b4eb0a387d981389, topic:reinforcement-learning, topic:openai-gym, readme:reinforcement learning