- Algorithms
- Computer Programming
- Mathematics
- Regression
- Probability Distribution
- Mathematical Theory & Analysis
- General Statistics
- Python Programming
State Estimation and Localization for Self-Driving Cars
Completed by Riley Kenyon
May 25, 2021
26 hours (approximately)
Riley Kenyon'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
