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Udacity's Self-Driving Car Nanodegree project files and notes.

Jupyter Notebook 92.03% HTML 6.59% Python 1.38%

self-driving-car-nd's Introduction

Udacity - Self-Driving Car NanoDegree

Udacity - Self-Driving Car NanoDegree

Self-Driving Car

Udacity's Self-Driving Car Nanodegree project files and notes.

This repository is a compilation of project files and lecture notes for Udacity's Self-Driving Car Engineer Nanodegree program which I started working on January 19, 2017.

Program Outline:

Term 1: Deep Learning and Computer Vision

1. Deep Learning

  • deep-learning-notes-and-labs: Notes on Deep Learning, Tensorflow and Keras
  • Project 2: Traffic Sign Classifier (Deep Learning)
  • Project 3: Behavioural Cloning (Deep Learning)
    • Train a car to drive in a 3D simulator using a deep neural network.
    • Input data comprises steering angles and camera images captured by driving with a keyboard / mouse / joystick in the simulator.

2. Computer Vision

  • computer-vision-notes-and-labs: Notes on Computer Vision
  • Project 1: Finding Lane Lines (Intro to Computer Vision)
  • Project 4: Advanced Lane Lines (Computer Vision)
  • Project 5: Vehicle Detection (Computer Vision)

Term 2: Sensor Fusion, Localisation and Control

1. Sensor Fusion

  • Combining lidar and radar data to track objects in the environment using Kalman filters.

2. Localisation

  • Locate a car relative to the world (Align a car and sensors to the map).
  • Use particle filters to localise the vehicle.

3. Control

  • Fundamental concepts of robotic control.
  • Build algorithms to steer car and wheels so as to meet an objective.

Term 3: Path Planning, Controlling a Self-Driving Car

  • Path Planning: Finding a sequence of steps in a maze (navigating cities, parking lots)
  • Put your code in a self-driving car

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