OpenGL-based Gym Environment (legacy)#

What you will need

  • Implementing Basic Robot Behaviors

What you will get

  • Experience with running and testing on the Duckietown simulator

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Warning

This package is obsolete, it has been superseeded by the Duckiematrix Gym environment, available here.

Introduction to the Gym-Duckietown Simulator#

Gym-Duckietown is a simulator for the Duckietown universe, written in pure Python/OpenGL (Pyglet). It places your agent, a Duckiebot, inside an instance of a Duckietown: a loop of roads with turns, intersections, obstacles, Duckie pedestrians, and other Duckiebots.

Gym-Duckietown is fast, open, and very customizable. What started as a lane-following simulator has evolved into a fully functioning autonomous driving simulator that you can use to train and test your Machine Learning, Reinforcement Learning, Imitation Learning, or even classical robotics algorithms. Gym-Duckietown offers a wide range of tasks, from simple lane-following to full city navigation with dynamic obstacles. Gym-Duckietown also ships with features, wrappers, and tools that can help you bring your algorithms to the real robot, including domain-randomization, accurate camera distortion, and differential-drive physics (and most importantly, realistic waddling).

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The development Gym Duckietown simulator has ended with the previous version of the codebase (daffy), therefore it is recommended that you refer to the daffy documentation for details about its use and features.