- Machine Learning Methods
- Deep Learning
- Mathematical Modeling
- Computer Vision
- Applied Mathematics
- Control Systems
- Estimation
- Global Positioning Systems
- Robotics
- Linear Algebra
State Estimation and Localization for Self-Driving Cars
Completed by Sujay Yegateela
August 18, 2020
26 hours (approximately)
Sujay Yegateela'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
