- Estimation
- Spatial Analysis
- Computer Vision
- Control Systems
- Mathematical Modeling
- Machine Learning Methods
- Global Positioning Systems
- Data Integration
- Linear Algebra
State Estimation and Localization for Self-Driving Cars
Completed by Vladislav Germanovich Shubnikov
February 17, 2024
26 hours (approximately)
Vladislav Germanovich Shubnikov'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
