Pinned Repositories
CarND-Advanced-Lane-Finding
Applied advanced Computer Vision techniques for real-time lane line detection
CarND-Behavioral-Cloning
Designed an Artificial Neural Network (CNN) to learn road features and generate steering predictions
CarND-Capstone
Integrated solution of a self-driving car system built with ROS – Using waypoint navigation and traffic light classification – Tested on simulator and test track at Palo Alto, California.
CarND-Extended-Kalman-Filter
Implemented an Extended Kalman Filter (EKF) to track position and velocity of a moving object on basis of LIDAR and RADAR measurements
CarND-Functional-Safety
Documented functional safety of a Lane Assistance system according to ISO 26262
CarND-Kidnapped-Vehicle
Created a 2 dimensional Particle Filter to localize a vehicle's position and yaw, given a map, initial GPS estimate plus noisy sensor and control data
CarND-Model-Predictive-Control
Implemented an advanced process control method (MPC) to optimize actuation inputs for a self-driving car's simulation, involving application of Kinematic model and cost function tuning
CarND-Path-Planning
Designed an algorithm to generate trajectories for a simulated self-driving car, autonomously maneuvering through dense highway traffic by making decisions based on a simple finite-state machine
CarND-Unscented-Kalman-Filter
Improved non-linear equation handling for object tracking using an Unscented Kalman Filter (UKF) for LIDAR and RADAR measurements
CarND-Vehicle-Detection
Trained a linear classifier (SVM) for real-time vehicle detection and tracking and combined results with previous project lane finding
albert-killer's Repositories
albert-killer/CarND-Path-Planning
Designed an algorithm to generate trajectories for a simulated self-driving car, autonomously maneuvering through dense highway traffic by making decisions based on a simple finite-state machine
albert-killer/CarND-Functional-Safety
Documented functional safety of a Lane Assistance system according to ISO 26262
albert-killer/CarND-Kidnapped-Vehicle
Created a 2 dimensional Particle Filter to localize a vehicle's position and yaw, given a map, initial GPS estimate plus noisy sensor and control data
albert-killer/CarND-Model-Predictive-Control
Implemented an advanced process control method (MPC) to optimize actuation inputs for a self-driving car's simulation, involving application of Kinematic model and cost function tuning
albert-killer/CarND-Unscented-Kalman-Filter
Improved non-linear equation handling for object tracking using an Unscented Kalman Filter (UKF) for LIDAR and RADAR measurements
albert-killer/CarND-Vehicle-Detection
Trained a linear classifier (SVM) for real-time vehicle detection and tracking and combined results with previous project lane finding
albert-killer/CarND-Advanced-Lane-Finding
Applied advanced Computer Vision techniques for real-time lane line detection
albert-killer/CarND-Behavioral-Cloning
Designed an Artificial Neural Network (CNN) to learn road features and generate steering predictions
albert-killer/CarND-Capstone
Integrated solution of a self-driving car system built with ROS – Using waypoint navigation and traffic light classification – Tested on simulator and test track at Palo Alto, California.
albert-killer/CarND-Extended-Kalman-Filter
Implemented an Extended Kalman Filter (EKF) to track position and velocity of a moving object on basis of LIDAR and RADAR measurements
albert-killer/CarND-PID-Controller
Set up a PID controller which computes the steering angle of a simulated vehicle in order to keep it on track, given CTE and velocity