Udacity - Self-Driving Car NanoDegree
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