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