Programming a robotic car

Udacity Nanodegree Project 4: Example of reinforcement learning. Training a Smartcab to drive on a rectangular grid.

Artificial Neural Networks based autonomous remote controlled car

Self driving care simulation in 2d written in rust using rust-deeplearning

Visualizations for understanding the regressed wheel steering angle for self driving cars

Lane Finding Project for Self-Driving Car ND

First Project Udacity's Self-Driving NanoDegree

Recognize lines from video/image inputs

Lane Finding Project for Self-Driving Car ND

Detected highway lane lines on a video stream. Used OpencV image analysis techniques to identify lines, including Hough Transforms and Canny edge detection.

Wrote the Assembly Language program for a self-driving robotic car that would follow a single black line on a given track.

Second Project of the Udacity Self-Driving Car Nanodegree Program

The Udacity open source self-driving car project

Predict steering angle of a self driving car using behaviorial cloning

Classify Traffic Signs.

Udacity Project 1

Deep Learning Project to Teach a Car to Drive Autonomously Using Only Camera Images.

Built and trained a deep neural network to classify traffic signs, using TensorFlow. Experimented with different network architectures. Performed image pre-processing and validation to guard against overfitting.