What is gym-ignition?¶
gym-ignition is a framework to create reproducible robotics environments for reinforcement learning research.
The aims of the project are the following:
Provide unified APIs for interfacing with both simulated and real robots.
Implement the simulation backend interfacing with the Ignition Gazebo simulator.
Enable a seamless switch of all the physics engines supported by Ignition Gazebo.
Guarantee the reproducibility and the scalability of the simulations by using the simulator as a library, without relying on any network transport.
Simplify the development of OpenAI Gym environments for robot learning research.
gym-ignition targets both control and robot learning research domains:
Researchers in robotics and control can simulate their robots with familiar tools like Gazebo and URDF, without the need to rely on any middleware.
Researchers in robot learning can quickly develop new robotic environments that can scale to hundreds of parallel instances.
To know more about why we started developing gym-ignition, why we selected Ignition Gazebo for our simulations, and what are our long-term goals, visit the Motivations page.
We are building an entire ecosystem around gym-ignition, if you’re interested have a look to the other projects:
ScenarI/O and |
Robot Models |
Ignition Plugins |
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