Sensor Fusion and Multi-Object Tracking

Overview

Give your career a boost by mastering how to fuse information from various sensors, such as radar, lidar, and camera, for accurate object positioning and tracking of moving objects.

The target audience for this program are engineers in the automotive industry who need to tackle problems related to perceiving the traffic situation around an autonomous vehicle. This course is also aimed at students with a bachelor's degree who want to pursue master level studies in automotive engineering.

This program is derived from master level courses.

It starts by introducing the basics of Bayesian statistics and recursive estimation theory, and then gradually introduces more advanced concepts. The program offers a unique opportunity to gain practical knowledge in sensor fusion and multi-object tracking algorithms (filters).

By the end of this program, you will be able to contribute to the development of sensor fusion and tracking applications for self-driving vehicles.

Most of the involved methods, however, are more general and can be used for surveillance or to track, for example, biological cells, sports athletes, or space debris.

University:

Provider:

edX  Professional Certificate
Categories:

Autonomous Vehicles Courses, Bayesian Statistics Courses

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Taught by

Lars Hammarstrand, Yuxuan Xia, Karl Granström and Lennart Svensson

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Subjects