# panda-gym
Set of robotic environments based on PyBullet physics engine and gymnasium.
[](https://pypi.org/project/panda-gym/)
[](https://pepy.tech/project/panda-gym)
[](LICENSE.txt)
[](https://github.com/qgallouedec/panda-gym/actions/workflows/build.yml)
[](https://codecov.io/gh/qgallouedec/panda-gym)
[](https://github.com/psf/black)
[](https://arxiv.org/abs/2106.13687)
## Documentation
Check out the [documentation](https://panda-gym.readthedocs.io/en/latest/).
## Installation
### Using PyPI
```bash
pip install panda-gym
```
### From source
```bash
git clone https://github.com/qgallouedec/panda-gym.git
pip install -e panda-gym
```
## Usage
```python
import gymnasium as gym
import panda_gym
env = gym.make('PandaReach-v3', render_mode="human")
observation, info = env.reset()
for _ in range(1000):
action = env.action_space.sample() # random action
observation, reward, terminated, truncated, info = env.step(action)
if terminated or truncated:
observation, info = env.reset()
env.close()
```
You can also [](https://colab.research.google.com/github/qgallouedec/panda-gym/blob/master/examples/PickAndPlace.ipynb)
## Environments
| | |
| :------------------------------: | :--------------------------------------------: |
| `PandaReach-v3` | `PandaPush-v3` |
|  |  |
| `PandaSlide-v3` | `PandaPickAndPlace-v3` |
|  |  |
| `PandaStack-v3` | `PandaFlip-v3` |
|  |  |
## Baselines results
Baselines results are available in [rl-baselines3-zoo](https://github.com/DLR-RM/rl-baselines3-zoo) and the pre-trained agents in the [Hugging Face Hub](https://huggingface.co/sb3).
## Citation
Cite as
```bib
@article{gallouedec2021pandagym,
title = {{panda-gym: Open-Source Goal-Conditioned Environments for Robotic Learning}},
author = {Gallou{\'e}dec, Quentin and Cazin, Nicolas and Dellandr{\'e}a, Emmanuel and Chen, Liming},
year = 2021,
journal = {4th Robot Learning Workshop: Self-Supervised and Lifelong Learning at NeurIPS},
}
```
Environments are widely inspired from [OpenAI Fetch environments](https://openai.com/blog/ingredients-for-robotics-research/).
Raw data
{
"_id": null,
"home_page": "https://github.com/qgallouedec/panda-gym",
"name": "panda-gym",
"maintainer": "",
"docs_url": null,
"requires_python": "",
"maintainer_email": "",
"keywords": "",
"author": "Quentin GALLOU\u00c9DEC",
"author_email": "gallouedec.quentin@gmail.com",
"download_url": "https://files.pythonhosted.org/packages/b5/9e/788dfd05db546f0e141181cf5d72c284e3106b7956a9de1cddc95b2bf503/panda_gym-3.0.4.tar.gz",
"platform": null,
"description": "# panda-gym\n\nSet of robotic environments based on PyBullet physics engine and gymnasium.\n\n[](https://pypi.org/project/panda-gym/)\n[](https://pepy.tech/project/panda-gym)\n[](LICENSE.txt)\n[](https://github.com/qgallouedec/panda-gym/actions/workflows/build.yml)\n[](https://codecov.io/gh/qgallouedec/panda-gym)\n[](https://github.com/psf/black)\n[](https://arxiv.org/abs/2106.13687)\n\n## Documentation\n\nCheck out the [documentation](https://panda-gym.readthedocs.io/en/latest/).\n\n## Installation\n\n### Using PyPI\n\n```bash\npip install panda-gym\n```\n\n### From source\n\n```bash\ngit clone https://github.com/qgallouedec/panda-gym.git\npip install -e panda-gym\n```\n\n## Usage\n\n```python\nimport gymnasium as gym\nimport panda_gym\n\nenv = gym.make('PandaReach-v3', render_mode=\"human\")\n\nobservation, info = env.reset()\n\nfor _ in range(1000):\n action = env.action_space.sample() # random action\n observation, reward, terminated, truncated, info = env.step(action)\n\n if terminated or truncated:\n observation, info = env.reset()\n\nenv.close()\n```\n\nYou can also [](https://colab.research.google.com/github/qgallouedec/panda-gym/blob/master/examples/PickAndPlace.ipynb)\n\n## Environments\n\n| | |\n| :------------------------------: | :--------------------------------------------: |\n| `PandaReach-v3` | `PandaPush-v3` |\n|  |  |\n| `PandaSlide-v3` | `PandaPickAndPlace-v3` |\n|  |  |\n| `PandaStack-v3` | `PandaFlip-v3` |\n|  |  |\n\n## Baselines results\n\nBaselines results are available in [rl-baselines3-zoo](https://github.com/DLR-RM/rl-baselines3-zoo) and the pre-trained agents in the [Hugging Face Hub](https://huggingface.co/sb3).\n\n## Citation\n\nCite as\n\n```bib\n@article{gallouedec2021pandagym,\n title = {{panda-gym: Open-Source Goal-Conditioned Environments for Robotic Learning}},\n author = {Gallou{\\'e}dec, Quentin and Cazin, Nicolas and Dellandr{\\'e}a, Emmanuel and Chen, Liming},\n year = 2021,\n journal = {4th Robot Learning Workshop: Self-Supervised and Lifelong Learning at NeurIPS},\n}\n```\n\nEnvironments are widely inspired from [OpenAI Fetch environments](https://openai.com/blog/ingredients-for-robotics-research/). \n\n\n",
"bugtrack_url": null,
"license": "",
"summary": "Set of robotic environments based on PyBullet physics engine and gymnasium.",
"version": "3.0.4",
"split_keywords": [],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "06f97a5b95b90ec0e8b5731ae4588d008460a99855c638348d90c4c46ebf1649",
"md5": "73c0abac9df2d19ed56809be22363b58",
"sha256": "7c52f4a357a33b55ed8eb5f109d40661f50efbc39981a7b10026db3cd5380906"
},
"downloads": -1,
"filename": "panda_gym-3.0.4-py3-none-any.whl",
"has_sig": false,
"md5_digest": "73c0abac9df2d19ed56809be22363b58",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": null,
"size": 23847,
"upload_time": "2023-01-25T10:06:41",
"upload_time_iso_8601": "2023-01-25T10:06:41.109164Z",
"url": "https://files.pythonhosted.org/packages/06/f9/7a5b95b90ec0e8b5731ae4588d008460a99855c638348d90c4c46ebf1649/panda_gym-3.0.4-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "b59e788dfd05db546f0e141181cf5d72c284e3106b7956a9de1cddc95b2bf503",
"md5": "e4f23765b4169791c62c7a76cb5dc1be",
"sha256": "a1beb7fc58e4971e677e8ef7310d6daf9107ec486e8f16895cbee1dcb8476885"
},
"downloads": -1,
"filename": "panda_gym-3.0.4.tar.gz",
"has_sig": false,
"md5_digest": "e4f23765b4169791c62c7a76cb5dc1be",
"packagetype": "sdist",
"python_version": "source",
"requires_python": null,
"size": 17647,
"upload_time": "2023-01-25T10:06:42",
"upload_time_iso_8601": "2023-01-25T10:06:42.729219Z",
"url": "https://files.pythonhosted.org/packages/b5/9e/788dfd05db546f0e141181cf5d72c284e3106b7956a9de1cddc95b2bf503/panda_gym-3.0.4.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2023-01-25 10:06:42",
"github": true,
"gitlab": false,
"bitbucket": false,
"github_user": "qgallouedec",
"github_project": "panda-gym",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"lcname": "panda-gym"
}
JSON
