This repository originated from an university project within the scope of autonomous robotic systems (ARS) and was uesed to train a cleaning robot based on an evolutionary algorithm (EA). The legacy code can be found in the release section with the tag ARS-EA.

Now, the repository is used to simulate the OpenRC, a 3D printable racing car. The aim of this project is to equip the car with sensors to enable autonoums driving based on a trained agent. If you want to build such a car on your own, head to thingiverse: OpenRC Print Files

The installation candidates can be found in the release section and are installed as Python package. Alternatively, follow these steps to build and install the simulator for your system.

1. Clone the repository

git clone https://github.com/Huntler/OpenRC-Simulator.git

2. Build & Install

Within the cloned repository, type:

pip install .

The simulator delivers a map editor to create maps (editing maps is WIP), a testing environment to load a trained agent on a map (WIP), a training mode which disables the GUI for maximum efficiency, and a manual mode to test a created map.

The map editor is a handy tool to create scenarios with different levels of complexity. To start the editor, call:

openrc-sim --name <MAP_NAME> --create

Replace <MAP_NAME> with a name of your choice. With the window opened, press p to start drawing mode and add some walls to your map. If you have finished adding walls, press p again. Finally, press r to place the car at a spot of your liking. Do not forget to save your creation my pressing s.

There is an option to manually drive the car on your map.

openrc-sim --name <MAP_NAME> --manual

The code tries to sqeeuze as much performance as possible when enabling training mode. Therefore, the GUI is disabled when training an agent.

openrc-sim --name <MAP_NAME> --train <CONFIG_NAME>

Replace <CONFIG_NAME> with a configuration as yaml-file which is read and passed as parameters to the simulated OpenRC. E.g.:

WIP

Configuration files are always stored in $HOME/.openrc-sim/config/ on linux and %appdata%/OpenRC-Sim/config on windows. The config editor is WIP.

Trained agents can be loaded into a simulation of your liking as follows:

openrc-sim --agent <MODEL_NAME> --name <MAP_NAME> --simulation 

[ ] Train on all maps randomly [ ] Print training progress [ ] Convert simulation to OpenAI Gym