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Minimal OpenAI gym interface for Gazebo Robots

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Gazebo-OpenAIGym

Minimal OpenAI gym interface for Gazebo Robots

This repository takes inspiration from the now deprecated gym-gazebo (https://github.com/erlerobot/gym-gazebo). However, this implementation is much more lightweight, facilitating easy usage with the Turtlebot like robots.

We also include an implementation of the Dueling DQN [1] RL agent with this repository for an user to get started.

This has been tested with ROS Kinetic, Ubuntu 16.04.

For the DeepRL agent, we use PyTorch 1.0.1.

Instructions

[1] Clone the repository

[2] For intializing an environment, pass the location of the launch file when creating the environment. We include an example world file in the /worlds directory.

[3] Run rllearn.py with the required dependencies to begin learning on your gazebo world. Change the reward functions in the TurtlebotGym.py file to suit your needs.

References

[1] Dueling Network Architectures for Deep Reinforcement Learning, Ziyu Wang, Tom Schaul, Matteo Hessel, Hado van Hasselt, Marc Lanctot, Nando de Freitas

[2] Gym-Gazebo, https://github.com/erlerobot/gym-gazebo

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