State Estimation and Localization for Self-Driving Cars
Completed by Hong Jing Ng
June 5, 2020
26 hours (approximately)
Hong Jing Ng'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
- Category: Mathematical Modeling
- Category: Global Positioning Systems
- Category: Machine Learning Methods
- Category: Linear Algebra
- Category: Estimation
- Category: Robotics
