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Update gym-ignition README
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<h1 align="center">gym-ignition</h1>
</p>

<p align="center">
<b><a href="https://github.com/robotology/gym-ignition#description">Description</a></b>
•
<b><a href="https://github.com/robotology/gym-ignition#setup">Setup</a></b>
•
<b><a href="https://github.com/robotology/gym-ignition#citation">Citation</a></b>
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<b><a href="https://robotology.github.io/gym-ignition/master/index.html">Website</a></b>
</p>

<div align="center">
<p><br/></p>
<table>
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<td align="left">General</td>
<td align="center">
<a href="https://isocpp.org">
<img src="https://img.shields.io/badge/standard-C++17-blue.svg?style=flat&logo=c%2B%2B" alt="C++ Standard" />
</a>
<a href="https://github.com/robotology/gym-ignition">
<img src="https://img.shields.io/github/languages/code-size/robotology/gym-ignition.svg" alt="Size" />
</a>
<a href="https://github.com/robotology/gym-ignition/blob/master/LICENSE">
<img src="https://img.shields.io/badge/license-LGPL-19c2d8.svg" alt="Size" />
</a>
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<td align="left">CI/CD</td>
<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" />
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<td align="left"><code>gym-ignition</code></td>
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<a href="https://pypi.org/project/gym-ignition/">
<img src="https://img.shields.io/pypi/v/gym-ignition.svg" />
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<p><br/></p>
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| ![][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.

The project consists of the following components:
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).

- [**`ScenarI/O`**](cpp/scenario/core):
*Scene Interfaces for Robot Input / Output* is a C++ abstraction layer to interact with simulated and real robots.
- [**`Gazebo ScenarI/O`**](cpp/scenario/gazebo):
Implementation of the ScenarI/O interfaces to interact with the [Ignition Gazebo](https://ignitionrobotics.org) simulator.
We provide Python bindings with functionalities comparable to popular alternatives like
[pybullet](https://github.com/bulletphysics/bullet3) and [mujoco-py](https://github.com/openai/mujoco-py).
- [**`gym_ignition`**](python/gym_ignition):
A Python package with the tooling to create OpenAI Gym environments for robot learning.
It provides abstractions like `Task` and `Runtime` to help developing environments that can be executed transparently
on all the ScenarI/O implementations (different simulators, real robots, ...).
The package also contains resources for inverse kinematics and multi-body dynamics supporting floating-based robots
based on the [iDynTree](https://github.com/robotology/idyntree) library.
- [**`gym_ignition_environments`**](python/gym_ignition_environments):
Demo environments created with `gym_ignition` and [`gym-ignition-models`](https://github.com/dic-iit/gym-ignition-models)
that show the recommended structure.

This project provides the complete implementation of ScenarI/O for the Ignition Gazebo simulator.
We expose all the physics engines supported by Ignition Gazebo.
Currently, the default and only physics engine is [DART](https://github.com/dartsim/dart).
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.

We are currently working on backends based on robotic middleware to transparently execute the environments developed
with `gym_ignition` on real robots.
Visit the [website][website] for more information about the project.

If you're interested to know the reasons why we started developing gym-ignition and why we selected Ignition Gazebo for
our simulations, visit the _Motivations_ section of the [website](https://robotology.github.io/gym-ignition).
[website]: https://robotology.github.io/gym-ignition

## Setup
## Installation

1. Install the Ignition suite following the [official instructions](https://ignitionrobotics.org/docs/edifice).
1. Execute `pip install gym-ignition`, preferably in a virtual environment.
1. First, follow the installation instructions of [ScenarIO](scenario/).
2. `pip install gym-ignition`, preferably in a [virtual environment](https://docs.python.org/3.8/tutorial/venv.html).

**Note**: `gym-ignition` currently only supports the latest version of the ignition suite. For more information on supported versions please refer to the [Support Policy](https://robotology.github.io/gym-ignition/master/installation/support_policy.html).
## Contributing

You can visit our community forum hosted in [GitHub Discussions](https://github.com/robotology/gym-ignition/discussions).
Even without coding skills, replying user's questions is a great way of contributing.
If you use gym-ignition in your application and want to show it off, visit the
[Show and tell](https://github.com/robotology/gym-ignition/discussions/categories/show-and-tell) section!
You can advertise there your environments created with gym-ignition.

Then, for some simple examples, visit the _Getting Started_ section of the [website](https://robotology.github.io/gym-ignition).
Pull requests are welcome.

You can decide to install only the C++ resources if you are not interested in using Python.
We also offer a constantly updated pre-release channel with the last development updates.
You can find all the details about the different types of installations we support in the [website](https://robotology.github.io/gym-ignition).

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| ![](https://user-images.githubusercontent.com/469199/99262383-321fb200-281e-11eb-89cc-cc31f590daa3.png) | ![](https://user-images.githubusercontent.com/469199/99263111-0cdf7380-281f-11eb-9cfe-338b2aae0503.png) | ![](https://user-images.githubusercontent.com/469199/99262746-9e021a80-281e-11eb-9df1-d70134b0801a.png) |
For major changes, please open a [discussion](https://github.com/robotology/gym-ignition/discussions)
first to propose what you would like to change.

## Citation

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}
```

## License

[LGPL v2.1](https://choosealicense.com/licenses/lgpl-2.1/) or any later version.

---

**Disclaimer:** Gym-Ignition is an independent project and is not related by any means to OpenAI and Open Robotics.
**Disclaimer:** Gym-ignition is an independent project and is not related by any means to OpenAI and Open Robotics.

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