Specialized knowledge and experience in self-driving car technologies is crucial to building successful autonomous vehicles. As a graduate of Udacity’s highly selective Self-Driving Car Nanodegree, I’ve completed numerous studies and projects which provide me with the skills to build safe, efficient, and comfortable self-driving car software platforms.
All of my completed projects, including full source code, are available for viewing and cloning on my Github account. Please click through any project to learn more about my work!
Perception – Computer Vision and Deep Learning
- Convolutional Neural Networks for object classification (such as traffic signs)
- Advanced image processing techniques for lane line finding
- Advanced image processing and convolutional neural networks for vehicle detection and tracking
- Behavioral Cloning to learn to steer a car only by watching existing drivers
- Transfer Learning to adapt cutting-edge deep learning research for self-driving car applications
- Semantic Segmentation to facilitate scene understanding through high-performance identification of image regions
Perception – Sensors
- Particle Filters for vehicle localization
- Path Planning for determining valid, safe, optimal, and comfortable routing for vehicles to a destination
- PID Control for basic steering, throttle, braking, and other systems
- Model Predictive Control for advanced control when optimizing across speed, comfort, location, etc
- Systems Integration for putting all of these techniques together in a real life Lincoln MKZ