Sensor Fusion: Extended Kalman Filter - Autonomous Car Motion Estimation

In this video we explain the theory and intuition of Extended Kalman filter and how it works?, why its needed? and when to use it?

We also apply it on a nonlinear system example of estimating the motion of an autonomous car. We derive and explain the motion model and vehicle kinematic models.

Timestamps list:
00:00 - Introduction
00:26 - Extended Kalman filter theory and intuition
04:55 - Covariance Error Propagation
06:00 - Linearization and First order Taylor approximation
08:50 - Partial derivatives and Jacobian matrix
12:07 - Extended Kalman filter equations
13:35 - Example | motion estimation of autonomous car
20:50 - Map motion model into the state space of Extended Kalman filter
28:49 - Overview of vehicle kinematic models

List of videos related:
Sensor Fusion "Linear Kalman Filter (Part 1)":    • Sensor Fusion: Linear Kalman Filter (...  
Sensor Fusion "Linear Kalman Filter (Part 2)":    • Sensor Fusion: Linear Kalman Filter (...  
Sensor Fusion: "Setting and Tuning Covariances of the Kalman Filter":    • Sensor Fusion:  Setting and Tuning Co...  

For more information about the Kalman filter, check this blog article:
https://codingcorner.org/extended-kal...

And for C++ implementation check the link:
https://codingcorner.org/extended-kal...

GitHub: https://github.com/Al-khwarizmi-780

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