- Robotics
- Control Systems
- Linear Algebra
- Mathematical Modeling
- Global Positioning Systems
- Deep Learning
- Estimation
- Applied Mathematics
- Computer Vision
- Machine Learning Methods
State Estimation and Localization for Self-Driving Cars
Completed by Patrick Jiaqian Lu
August 25, 2024
26 hours (approximately)
Patrick Jiaqian Lu'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
