- Machine Learning Methods
- Control Systems
- Applied Mathematics
- Robotics
- Estimation
- Global Positioning Systems
- Mathematical Modeling
- Deep Learning
- Linear Algebra
- Computer Vision
State Estimation and Localization for Self-Driving Cars
Completed by Tatsuhiko Nakamine
September 10, 2021
26 hours (approximately)
Tatsuhiko Nakamine'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
