{"id":13755983,"url":"https://github.com/qgallouedec/panda-gym","last_synced_at":"2025-05-15T17:01:18.201Z","repository":{"id":37911563,"uuid":"295209844","full_name":"qgallouedec/panda-gym","owner":"qgallouedec","description":"Set of robotic environments based on PyBullet physics engine and gymnasium.","archived":false,"fork":false,"pushed_at":"2024-07-23T07:27:41.000Z","size":33952,"stargazers_count":651,"open_issues_count":9,"forks_count":122,"subscribers_count":8,"default_branch":"master","last_synced_at":"2025-05-10T11:37:38.479Z","etag":null,"topics":["artificial-intelligence","deep-learning","franka-emika","machine-learning","python","reinforcement-learning","robotics"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/qgallouedec.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2020-09-13T18:13:39.000Z","updated_at":"2025-05-10T08:30:49.000Z","dependencies_parsed_at":"2024-01-12T17:34:48.634Z","dependency_job_id":"5cabbd57-763a-49d5-8c17-768095cdf789","html_url":"https://github.com/qgallouedec/panda-gym","commit_stats":{"total_commits":160,"total_committers":8,"mean_commits":20.0,"dds":0.5625,"last_synced_commit":"f3031c9d668528bceedd4010613b1f2ef5bc08bf"},"previous_names":[],"tags_count":14,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/qgallouedec%2Fpanda-gym","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/qgallouedec%2Fpanda-gym/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/qgallouedec%2Fpanda-gym/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/qgallouedec%2Fpanda-gym/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/qgallouedec","download_url":"https://codeload.github.com/qgallouedec/panda-gym/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":254384901,"owners_count":22062419,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["artificial-intelligence","deep-learning","franka-emika","machine-learning","python","reinforcement-learning","robotics"],"created_at":"2024-08-03T11:00:33.733Z","updated_at":"2025-05-15T17:01:18.135Z","avatar_url":"https://github.com/qgallouedec.png","language":"Python","funding_links":[],"categories":["Reinforcement Learning (RL) and Deep Reinforcement Learning (DRL)","Core Area","[PyBullet](https://github.com/bulletphysics/bullet3)"],"sub_categories":["RL/DRL Environments","Good Environment to Start"],"readme":"# panda-gym\n\nSet of robotic environments based on PyBullet physics engine and gymnasium.\n\n[![PyPI version](https://img.shields.io/pypi/v/panda-gym.svg?logo=pypi\u0026logoColor=FFE873)](https://pypi.org/project/panda-gym/)\n[![Downloads](https://static.pepy.tech/badge/panda-gym)](https://pepy.tech/project/panda-gym)\n[![GitHub](https://img.shields.io/github/license/qgallouedec/panda-gym.svg)](LICENSE.txt)\n[![build](https://github.com/qgallouedec/panda-gym/actions/workflows/build.yml/badge.svg?branch=master)](https://github.com/qgallouedec/panda-gym/actions/workflows/build.yml)\n[![codecov](https://codecov.io/gh/qgallouedec/panda-gym/branch/master/graph/badge.svg?token=pv0VdsXByP)](https://codecov.io/gh/qgallouedec/panda-gym)\n[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)\n[![arXiv](https://img.shields.io/badge/cs.LG-arXiv%3A2106.13687-B31B1B.svg)](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 [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](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| ![PandaReach-v3](docs/_static/img/reach.png) |         ![PandaPush-v3](docs/_static/img/push.png)         |\n|         `PandaSlide-v3`          |             `PandaPickAndPlace-v3`             |\n| ![PandaSlide-v3](docs/_static/img/slide.png) | ![PandaPickAndPlace-v3](docs/_static/img/pickandplace.png) |\n|         `PandaStack-v3`          |              `PandaFlip-v3`                    |\n| ![PandaStack-v3](docs/_static/img/stack.png) | ![PandaFlip-v3](docs/_static/img/flip.png) |\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","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fqgallouedec%2Fpanda-gym","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fqgallouedec%2Fpanda-gym","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fqgallouedec%2Fpanda-gym/lists"}