Andrey Glushko's repositories
CarND-Path-Planning-Project
In this project, the goal is to design a path planner that is able to create smooth, safe paths for the car to follow along a 3 lane highway with traffic. A successful path planner will be able to keep inside its lane, avoid hitting other cars, and pass slower moving traffic all by using localization, sensor fusion, and map data.
CarND-PID-Control-Project
PID controller in C++ to maneuver the vehicle around the track
P4-Advanced-Lane-Finding
P4-Advanced-Lane-Finding
P5-Vehicle-Detection
Vehicle detection based on HOG and SVM
CarND-MPC-Project
Self-driving car
P3-Behavioral_Cloning_Project
Deep learning to train an autonomous vehicle to mimic human driving
Statistical-Learning
Statistical Learning, Stanford
CarND-Unscented-Kalman-Filter-Project
Self-Driving Car Nanodegree Term 2 Project 3: Lidar and Radar Fusion with Unscented Kalman Filter on C++
P2-Traffic-Sign-Classifier
Build a Traffic Sign Recognition Classifier
CarND-Extended-Kalman-Filter-Project
Udacity Self-Driving Car Nanodegree Term 2 Project 1: Lidar and Radar Fusion with Extended Kalman Filters in C++
CarND-Kidnapped-Vehicle-Project
Self-Driving Car Nanodegree Term 2 Project 3: Particle Filter for vehicle localization on C++
CarND-Kidnapped-Vehicle-Project-Visualization
CarND-Kidnapped-Vehicle-Project-Visualization
CarND-MPC-Project-1
CarND Term 2 Model Predictive Control (MPC) Project
CarND-Semantic-Segmentation
Label the pixels of a road in images using a Fully Convolutional Network (FCN).
deep-learning
Repo for the Deep Learning Nanodegree Foundations program.
Machine-Learning-Stanford
Machine Learning, Matlab code
sdc-path-planning-quizzes
Quizzes in Term 3: Path Planning