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A self driving car project using Reinforcement learning

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Self Driving Pi

This is the repo for John Papetti III and Mark Zhang's self driving car project for the Wardlaw + Hartridge School 2019 Family Science Night (FSN)

An Intro to Self Driving Car

In this project, a self driving robot is created using a Raspberry Pi 3. The robot can successfully follow a road (black strip on the white surface) using machine learning models. The program process the pixel data from a webcam and control the robot's movement. A 80-to-2 dimension autoencoder was used to reduce the dimension space of the environment. DQN, a reinforcement learning model, was used to learn how to drive. The DQN network was trained in a computer simulation before being implemented on the actual robot.