- Deep Learning
- Computer Vision
- Mathematical Modeling
- Control Systems
- Estimation
- Global Positioning Systems
- Machine Learning Methods
- Linear Algebra
- Robotics
- Applied Mathematics
State Estimation and Localization for Self-Driving Cars
Completed by Ignacio Ortega Coronado
August 13, 2020
26 hours (approximately)
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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
