https://github.com/thomas-bouvier/floppy-bird

Flappy Bird-like game including a Q-learning algorithm and a neural network-based algorithm (NEAT) for artificial intelligence
https://github.com/thomas-bouvier/floppy-bird

artificial-intelligence evolutionary-algorithm flappy-bird genetic-algorithm neat neural-network q-learning

Last synced: 6 months ago
JSON representation

Flappy Bird-like game including a Q-learning algorithm and a neural network-based algorithm (NEAT) for artificial intelligence

• Host: GitHub
• URL: https://github.com/thomas-bouvier/floppy-bird
• Owner: thomas-bouvier
• License: other
• Created: 2017-06-13T16:45:29.000Z (about 8 years ago)
• Default Branch: master
• Last Pushed: 2020-03-27T14:30:44.000Z (about 5 years ago)
• Last Synced: 2024-12-12T21:41:30.730Z (6 months ago)
• Topics: artificial-intelligence, evolutionary-algorithm, flappy-bird, genetic-algorithm, neat, neural-network, q-learning
• Language: C
• Homepage:
• Size: 40.5 MB
• Stars: 6
• Watchers: 3
• Forks: 3
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
# floppy-bird

## Game

### Installation

#### For Windows (with CodeBlocks) :

Download SDL2 for mingw (in development libraries) from https://www.libsdl.org/download-2.0.php

Extract the folder i686-w64-mingw.

Download SDL2_ttf, SDL2_mixer and SDL2_image the same way.

Create an environment variable named SDLPATH, that contains the path to the SDL folder.

Don't forget to add the necessary .dll files in your project directory (SDL2.dll, SDL2_ttf.dll, SDL2_mixer.dll, SDL2_image.dll, libfreetype-6.dll and libpng16-16.dll)

Now you can compile and run the project with the custom Makefile provided.

#### For Linux :

Install the SDL2 :

	sudo apt-get install libsdl2-dev

Also install the complementary libraries SDL2_mixer, SDL2_ttf and SDL2_image

	sudo apt-get install libsdl2-ttf-dev

	sudo apt-get install libsdl2-mixer-dev

	sudo apt-get install libsdl2-image-dev

Now you can compile and run the project with the Makefile provided with the sources.

### Configuration

Two configuration files are provided in game/src/conf.

One is made for Windows with Codeblocks, the other for Linux, but feel free to modify these paths if you change anything.

## Robot

### Hardware

The robot is made from 3D printed parts. All parts (STL files) can be found in robot/cad_files/stl_files.

To build the robot, you need the following parts :

* Boitier camera x1

* Pied camera x2

* Support stylet x1

* support_ipad x1

* Raspberry pi 3 x1

* Pi camera V2.0 x1

* Stylus x1

* Servomotor SG90s x1

* M3 screw 22mm x2

* M3 nut x2

**Printing parameters :**

* Material : PLA

* Layer height : 0,2mm

* Supports : yes

### Configuration

The raspberry pi needs some libraries to get all the programs running properly. Here are the main steps to install the libraries :

**1st step : update and upgrade the firmware**

    sudo apt-get update && apt-get upgrade -y

**2nd step : instalation of the librairies**

    sudo apt-get install -y cmake git gcc g++ libx11-dev libxt-dev libxext-dev libgraphicsmagick1-dev libcv-dev libhighgui-dev

**3rd step : clone userland repository**

    mkdir -p ~/git/raspberrypi

    cd ~/git/raspberrypi

    git clone https://github.com/raspberrypi/userland.git

    cd userland

    ./buildme

**4th step : clone raspicam_cv repository** (allows us to control the Pi camera within the programs)

    mkdir -p ~/git

    cd ~/git

    git clone https://github.com/robidouille/robidouille.git

    cd robidouille/raspicam_cv

    mkdir objs

    make

### Usage

To run the project :

    sudo ./colourTrack

note : Super user is needed because of the access to the hardware PWM

Some options are available :

    -l loadFileName : load working space and structures (trackers...) from the load File

    -s saveFileName : save working space and structures (trackers...) into the save File

    -d logFileName : Save data into a log file

    -i : run the basic IA

    -q : run the q-learning IA

    -n : run the neat IA

    -v : verbose mode

Example :

    sudo ./colourTrack -l config -i

    # run the program loading the config file and start the basic IA