Advanced Kalman Filtering and Sensor Fusion
Theory and C++ Simulation Implementation for Autonomous Vehicles and Self Driving Cars!
4.77 (830 reviews)
7 388
students
8.5 hours
content
Jul 2021
last update
$84.99
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What you will learn
How to use the Linear Kalman Filter to solve linear optimal estimation problems
How to use the Extended Kalman Filter to solve non-linear estimation problems
How to use the Unscented Kalman Filter to solve non-linear estimation problems
How to fuse in measurements of multiple sensors all running at different update rates
How to tune the Kalman Filter for best performance
How to correctly initialize the Kalman Filter for robust operation
How to model sensor errors inside the Kalman Filter
How to use fault detection to remove bad sensor measurements
How to implement the above 3 Kalman Filter Variants in C++
How to implement the LKF in C++ for a 2d Tracking Problem
How to implement the EKF and UKF in C++ for an autonomous self-driving car problem
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3730150
udemy ID
27/12/2020
course created date
16/08/2021
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