This repository contains my project submissions for Udacity's self driving car nano degree.

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.

Program Outline:

Computer Vision and Deep Learning

In this term, you'll become an expert in applying Computer Vision and Deep Learning on automotive problems. You will teach the car to detect lane lines, predict steering angle, and more all based on just camera data!

Deep Learning

• Project 2: Traffic Sign Classifier (Deep Learning) - Use tensorflow to train a convolution neural network capable of detecting road side traffic signs.
• Project 3: Behavioural Cloning (Deep Learning): Train a car to drive in a 3D simulator using a deep neural network.

Computer Vision

• Project 1: Finding Lane Lines (Intro to Computer Vision): Introductory project which used basic computer vision techniques like canny edge and hough transforms to detect lane lines
• Project 4: Advanced Lane Lines (Computer Vision): Use of image thresholding, warping and fitting lanes lines to develop a more robust method of detecting lane lines on a road
• Project 5: Vehicle Detection (Computer Vision): Use of HOG and SVM to detect vehicles on a road

Sensor Fusion, Localisation and Control

In this term, you'll learn how to use an array of sensor data to perceive the environment and control the vehicle. You'll evaluate sensor data from camera, radar, lidar, and GPS, and use these in closed-loop controllers that actuate the vehicle.

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.

• Project 1: Extended Kalman Filter
• Project 2: Unscented Kalman Filter
• Project 3: Kidnapped Vehicle
• Project 4: PID Control
• Project 5: MPC [Model Predictive Control]

Path Planning, Concentrations, and Systems

In this term, you'll learn how to plan where the vehicle should go, how the vehicle systems work together to get it there, and you'll perform a deep-dive into a concentration of your choice. Path Planning: Finding a sequence of steps in a maze (navigating cities, parking lots) Put your code in a self-driving car