Self Driving Car Engineer Nanodegree Udacity

December 2020 to June 2021 course work By Ian Whittal, P.Eng

Nanodegree applying computer vision and deep learning to automotive problems, including detecting lane lines, predicting steering angles, and more. I learned sensor fusion, which was used to filter data from an array of sensors in order to perceive the environment. The Capstone of the entire Self-Driving Car Engineer Nanodegree Program is "Carla", the Udacity self-driving car, and the Robot Operating System that controls her. I worked to combine what I've learned over the course of the entire Nanodegree Program to run my code on Carla, a real self-driving car.

PART 1
Computer Vision, Deep Learning, and Sensor Fusion
Here, I first become an expert in applying Computer Vision and Deep Learning on automotive problems. I will teach the car to detect lane lines, predict steering angle, and more all based on just camera data, along with working with lidar and radar data.

Project: Finding Lane Lines - Camera Computer Vision
Project: Advanced Lane Finding - Camera Computer Vision
Project: Traffic Sign Classifier - Deep Learning - Classifier
Project: Behavioral Cloning - Deep Learning - Regression
Project: Extended Kalman Filters - Sensor Fusion - LIDAR / RADAR data

PART 2
Localization, Path Planning, Control, and System Integration
Here, I expand on my sensor knowledge to localize and control the vehicle. I evaluate sensor data from camera, radar, lidar, and GPS, and use these in closed-loop controllers that actuate the vehicle, finishing by combining all my skills on a real self-driving car under system integration!

Project: Kidnapped Vehicle - Particle Filter - Vehicle Localization - GPS/LIDAR data
Project: Highway Driving Path Planning - Trajectory Generation
Project: PID Controller - Control Theory
Project: System Integration - Capstone - Programming a Real Self Driving Vehicle
Project: Optimize Your GitHub Profile
Project: Improve Your LinkedIn Profile