- Robotics
- Global Positioning Systems
- Deep Learning
- Mathematical Modeling
- Linear Algebra
- Applied Mathematics
- Computer Vision
- Estimation
- Control Systems
- Machine Learning Methods
State Estimation and Localization for Self-Driving Cars
Completed by Abdullah Enes DORUK
September 28, 2020
26 hours (approximately)
Abdullah Enes DORUK's account is verified. Coursera certifies their successful completion of State Estimation and Localization for Self-Driving Cars
What you will learn
Understand the key methods for parameter and state estimation used for autonomous driving, such as the method of least-squares
Develop a model for typical vehicle localization sensors, including GPS and IMUs
Apply extended and unscented Kalman Filters to a vehicle state estimation problem
Apply LIDAR scan matching and the Iterative Closest Point algorithm
Skills you will gain
