Set of robotic environments based on PyBullet physics engine and gymnasium.
Project description
panda-gym
Set of robotic environments based on PyBullet physics engine and gymnasium.
Documentation
Check out the documentation.
Installation
Using PyPI
pip install panda-gym
From source
git clone https://github.com/qgallouedec/panda-gym.git
pip install -e panda-gym
Usage
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()
Environments
PandaReach-v3 |
PandaPush-v3 |
PandaSlide-v3 |
PandaPickAndPlace-v3 |
PandaStack-v3 |
PandaFlip-v3 |
Baselines results
Baselines results are available in rl-baselines3-zoo and the pre-trained agents in the Hugging Face Hub.
Citation
Cite as
@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.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
panda_gym-3.0.7.tar.gz
(17.8 kB
view hashes)
Built Distribution
panda_gym-3.0.7-py3-none-any.whl
(23.6 kB
view hashes)
Close
Hashes for panda_gym-3.0.7-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | cfb0b1eb1d4e59d6582ed2ac512e69e67d5c3d80862f1ca7e9bb1cd9eaaaf090 |
|
MD5 | b3a6c7338312c2aba92e5fb801c2f8bc |
|
BLAKE2b-256 | 1aaa4eb790df24fc475e8c31c960c83a4aec2991e06293eed1e06c0eab9145bb |