Description:
gymignition 1.3.1
gym-ignition
Description
gym-ignition is a framework to create reproducible robotics environments for reinforcement learning research.
It is based on the 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 and Runtime
abstractions that help you focusing on the development of the decision-making logic rather than engineering.
It includes 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 and exposing
high-level functionalities.
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 package.
Visit the website for more information about the project.
Installation
First, follow the installation instructions of ScenarIO.
pip install gym-ignition, preferably in a virtual environment.
Contributing
You can visit our community forum hosted in GitHub 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 section!
You can advertise there your environments created with gym-ignition.
Pull requests are welcome.
For major changes, please open a discussion
first to propose what you would like to change.
Citation
@INPROCEEDINGS{ferigo2020gymignition,
title={Gym-Ignition: Reproducible Robotic Simulations for Reinforcement Learning},
author={D. {Ferigo} and S. {Traversaro} and G. {Metta} and D. {Pucci}},
booktitle={2020 IEEE/SICE International Symposium on System Integration (SII)},
year={2020},
pages={885-890},
doi={10.1109/SII46433.2020.9025951}
}
License
LGPL v2.1 or any later version.
Disclaimer: Gym-ignition is an independent project and is not related by any means to OpenAI and Open Robotics.
License
For personal and professional use. You cannot resell or redistribute these repositories in their original state.
Customer Reviews
There are no reviews.
