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a self-learning AI drone learns to evade obstacles by NeuroEvolution through Augmenting Topologies (NEAT)

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drone-x - NeuroEvolution self learning drone

GitHub release

Contents

About

Drone-x Demo

A self learning AI drone to evade obstacles. The simulation is made using Opengl & neural network using C++

Requirements

Runtime & Development

  • C++ Compiler >= GCC 4.8.1
  • Freeglut-dev >= Freeglut 3.0.0
  • SOIL image loader library >= SOIL 1.16

Installation

To download the repo & Run the simulation:

git clone https://github.com/bokonist/drone-x
cd drone-x/simulation/drone-window
make
./drone

To uninstall & delete generation files:

make clean
rm -r gen*
rm drone

Frequently Asked Questions

Which part of the source code is the graphics simulation part?

src/drone.cpp , main.cpp & include/drone.h are the Opengl part of the code. These parts can be changed to change the simulation speed, obstacle type, menu system.

Experiencing stutter and performance lose?

Check to make sure you have a supported graphics card & install its latest driver. Run with vblank_mode=1 to enable v-sync. If you still experience stutter, then comment out the gamemode part in main.cpp and run the game in gamemode instead of window.

Is it possible to port this to windows / getting error for to_string() function?

Yes, the freeglut & soil are cross platform libraries, when compiling make sure the latest version of gcc is installed using Mingw-w64 for the latest version of g++ compiler otherwise you may get an error for to_string() function or alternatively you can add a patch for it yourself.

How fast can the simulation run/ How to speed up simulation?

In main.cpp change fps parameter value & run the game with the flag vblank_mode=0 to disable vsync. maximum framerate depends on your system configuration. Alternatively you can change the the obstacle speed parameter in drone.cpp to achieve the same effect.

Why is my system getting loud/ single core cpu usage 100%?

This is a single threaded application for ease of understanding. The graphics part and neural code is run on an infinite loop, therefore the cpu usage will be maximum 100% for a single core even if that loop is not doing anything.

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a self-learning AI drone learns to evade obstacles by NeuroEvolution through Augmenting Topologies (NEAT)

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