- Estimation
- Computer Vision
- Applied Mathematics
- Mathematical Modeling
- Deep Learning
- Robotics
- Machine Learning Methods
- Linear Algebra
- Control Systems
- Global Positioning Systems
State Estimation and Localization for Self-Driving Cars
Completed by ZEINAB AHMED MOHAMED AHMED HASSAN OMAR
June 24, 2020
26 hours (approximately)
ZEINAB AHMED MOHAMED AHMED HASSAN OMAR'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
