Fusing Lidar and Radar DataEnroll In Nanodegree
This course is a part of the Self-Driving Car Engineer Nanodegree Program.
Vehicles use many different sensors to understand the environment. Sensor fusion uses different types of Kalman filters - mathematical algorithms - to combine data from these sensors and develop a consistent understanding of the world.
This course is part of a Nanodegree Program. It is a step towards a new career in Self-Driving Car Engineer.
Enhance your skill set and boost your hirability through innovative, independent learning.
C++, Calculus, Linear Algebra
See the Technology Requirements for using Udacity.
By the end of this course, you will be able to program Kalman filters to fuse together radar and lidar data to track an object. You will be able to build extended Kalman filters and unscented Kalman filters to fuse together nonlinear data.
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