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        "author": "Diego Ferigo",
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            "Development Status :: 5 - Production/Stable",
            "Framework :: Robot Framework",
            "Intended Audience :: Developers",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: GNU Lesser General Public License v2 or later (LGPLv2+)",
            "Operating System :: POSIX :: Linux",
            "Programming Language :: Python :: 3 :: Only",
            "Programming Language :: Python :: 3.8",
            "Programming Language :: Python :: 3.9",
            "Programming Language :: Python :: Implementation :: CPython",
            "Topic :: Games/Entertainment :: Simulation",
            "Topic :: Scientific/Engineering :: Artificial Intelligence",
            "Topic :: Scientific/Engineering :: Physics",
            "Topic :: Software Development"
        ],
        "description": "<p align=\"center\">\n<h1 align=\"center\">gym-ignition</h1>\n</p>\n\n<div align=\"center\">\n<table>\n    <tbody>\n         <tr>\n            <td align=\"center\">\n                <a href=\"https://github.com/robotology/gym-ignition/actions\">\n                <img src=\"https://github.com/robotology/gym-ignition/workflows/CI/CD/badge.svg\" alt=\"CICD\" />\n                </a>\n                <a href=\"https://github.com/robotology/gym-ignition/actions\">\n                <img src=\"https://github.com/robotology/gym-ignition/workflows/Docker%20Images/badge.svg\" alt=\"Docker Images\" />\n                </a>\n                <a href=\"https://www.codacy.com/gh/robotology/gym-ignition/dashboard?utm_source=github.com&amp;utm_medium=referral&amp;utm_content=robotology/gym-ignition&amp;utm_campaign=Badge_Grade\">\n                <img src=\"https://api.codacy.com/project/badge/Grade/5536b05f8be94483b64ee883e7170a39\" alt=\"Codacy Badge\" />\n                </a>\n            </td>\n        </tr>   \n        <tr>\n            <td align=\"center\">\n                <a href=\"https://pypi.org/project/gym-ignition/\">\n                <img src=\"https://img.shields.io/pypi/v/gym-ignition.svg\" />\n                </a>\n                <a href=\"https://pypi.org/project/gym-ignition/\">\n                <img src=\"https://img.shields.io/pypi/pyversions/gym-ignition.svg\" />\n                </a>\n                <a href=\"https://pypi.org/project/gym-ignition/\">\n                <img src=\"https://img.shields.io/pypi/status/gym-ignition.svg\" />\n                </a>\n                <a href=\"https://pypi.org/project/gym-ignition/\">\n                <img src=\"https://img.shields.io/pypi/format/gym-ignition.svg\" />\n                </a>\n                <a href=\"https://pypi.org/project/gym-ignition/\">\n                <img src=\"https://img.shields.io/pypi/l/gym-ignition.svg\" />\n                </a>\n            </td>\n        </tr>\n    </tbody>\n</table>\n</div>\n\n||||\n|:---:|:---:|:---:|\n| ![][pendulum] | ![][panda] | ![][icub] |\n\n[icub]: https://user-images.githubusercontent.com/469199/99262746-9e021a80-281e-11eb-9df1-d70134b0801a.png\n[panda]: https://user-images.githubusercontent.com/469199/99263111-0cdf7380-281f-11eb-9cfe-338b2aae0503.png\n[pendulum]: https://user-images.githubusercontent.com/469199/99262383-321fb200-281e-11eb-89cc-cc31f590daa3.png\n\n## Description\n\n**gym-ignition** is a framework to create **reproducible robotics environments** for reinforcement learning research.\n\nIt is based on the [ScenarIO](scenario/) project which provides the low-level APIs to interface with the Ignition Gazebo simulator.\nBy default, RL environments share a lot of boilerplate code, e.g. for initializing the simulator or structuring the classes\nto expose the `gym.Env` interface.\nGym-ignition provides the [`Task`](python/gym_ignition/base/task.py) and [`Runtime`](python/gym_ignition/base/runtime.py)\nabstractions that help you focusing on the development of the decision-making logic rather than engineering.\nIt includes [randomizers](python/gym_ignition/randomizers) to simplify the implementation of domain randomization\nof models, physics, and tasks.\nGym-ignition also provides powerful dynamics algorithms compatible with both fixed-base and floating-based robots by\nexploiting [robotology/idyntree](https://github.com/robotology/idyntree/) and exposing\n[high-level functionalities](python/gym_ignition/rbd/idyntree).\n\nGym-ignition does not provide out-of-the-box environments ready to be used.\nRather, its aim is simplifying and streamlining their development.\nNonetheless, for illustrative purpose, it includes canonical examples in the\n[`gym_ignition_environments`](python/gym_ignition_environments) package.\n\nVisit the [website][website] for more information about the project.\n\n[website]: https://robotology.github.io/gym-ignition\n\n## Installation\n\n1. First, follow the installation instructions of [ScenarIO](scenario/).\n2. `pip install gym-ignition`, preferably in a [virtual environment](https://docs.python.org/3.8/tutorial/venv.html).\n\n## Contributing\n\nYou can visit our community forum hosted in [GitHub Discussions](https://github.com/robotology/gym-ignition/discussions).\nEven without coding skills, replying user's questions is a great way of contributing.\nIf you use gym-ignition in your application and want to show it off, visit the\n[Show and tell](https://github.com/robotology/gym-ignition/discussions/categories/show-and-tell) section!\nYou can advertise there your environments created with gym-ignition.\n\nPull requests are welcome.\n\nFor major changes, please open a [discussion](https://github.com/robotology/gym-ignition/discussions)\nfirst to propose what you would like to change.\n\n## Citation\n\n```bibtex\n@INPROCEEDINGS{ferigo2020gymignition,\n    title={Gym-Ignition: Reproducible Robotic Simulations for Reinforcement Learning},\n    author={D. {Ferigo} and S. {Traversaro} and G. {Metta} and D. {Pucci}},\n    booktitle={2020 IEEE/SICE International Symposium on System Integration (SII)},\n    year={2020},\n    pages={885-890},\n    doi={10.1109/SII46433.2020.9025951}\n} \n```\n\n## License\n\n[LGPL v2.1](https://choosealicense.com/licenses/lgpl-2.1/) or any later version.\n\n---\n\n**Disclaimer:** Gym-ignition is an independent project and is not related by any means to OpenAI and Open Robotics.\n\n\n",
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