Udacity's Self-Driving Car Nanodegree project files and notes.
This repository contains project files and lecture notes for Udacity's Self-Driving Car Engineer Nanodegree program which I started working on on 27 October, 2016.
The Self-Driving Car Engineer is an online certification intended to prepare students to become self-driving car engineers. The program was developed by Udacity in partnership with Mercedes-Benz, NVIDIA, Otto, DiDi, BMW, McLaren and NextEv.
See also: My notes for Udacity's Machine Learning Nanodegree.
- `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.
- `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)
- Combining lidar and radar data to track objects in the environment using Kalman filters.
- Locate a car relative to the world (Align a car and sensors to the map).
- Use particle filters to localise the vehicle.
- Fundamental concepts of robotic control.
- Build algorithms to steer car and wheels so as to meet an objective.
- Path Planning: Finding a sequence of steps in a maze (navigating cities, parking lots)
- Put your code in a self-driving car