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Multi-Object Tracking for Automotive Systems

Provided by Chalmers University of Technology (ChalmersX)
10–20 hours
per week, for 10 weeks
Free

$200 USD for graded exams and assignments, plus a certificate

Learn how to localize and track dynamic objects with a range of applications including autonomous vehicles

 
 

Start Date:

Before you start

ChM013x: Sensor Fusion and Non-linear Filtering for Automotive Systems
Course opens: Aug 22, 2019
Course ends: Oct 31, 2019

What you will learn

  • A thorough understanding of multi-object tracking (MOT) and its challenge
  • Expert-level understanding of principles, theory and algorithms in modern MOT.
  • Extensive know-how for solving various MOT problems in practice.
  • Valuable experience from implementing different MOT algorithms.
 
 
 
 

Overview

Autonomous vehicles, such as self-driving cars, rely critically on an accurate perception of their environment. 

In this course, we will teach you the fundamentals of multi-object tracking for automotive systems. Key components include the description and understanding of common sensors and motion models, principles underlying filters that can handle varying number of objects, and a selection of the main multi-object tracking (MOT) filters.

The course builds and expands on concepts and ideas introduced in CHM013x: “Sensor fusion and nonlinear filtering for automotive systems”. In particular, we study how to localize an unknown number of objects, which implies various interesting challenges. We focus on cameras, laser scanners and radar sensors, which are all commonly used in vehicles, and emphasize on situations where we seek to track nearby pedestrians and vehicles. Still, most of the involved methods are more general and can be used for surveillance or to track, e.g., biological cells, sports athletes or space debris.

The course contains a series of videos, quizzes and hands-on assignments where you get to implement several of the most important algorithms.

Learn from award-winning and passionate teachers to enhance your knowledge at the forefront of research on self-driving vehicles. Chalmers is among the top engineering schools that distinguish itself through its close collaboration with industry.
 

Meet your instructors

Lennart Svensson
Professor
Chalmers University of Technology
Karl Granström
Postdoc in the Signal Processing group
Chalmers University of Technology
Yuxuan Xia
PhD student
Chalmers University of Technology

Learner testimonials

 
 

Frequently asked questions

 
 

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This course is part of:

Earn a MicroMasters® Program Certificate in 1 year if courses are taken one at a time.

View the program
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  2. 60–120 hours of effort

    Learn to design hybrid powertrains which meet the needs of modern vehicles, by combining the strengths of both electric motors and combustion engines

  3. 70–140 hours of effort

    Learn the fundamentals of passive and active safety in automotive engineering

     

  4. 70–140 hours of effort

    Learn how to model and simulate system dynamics in automotive engineering

  5. Multi-Object Tracking for Automotive Systems
  6. 60–120 hours of effort

    Learn effective tactics for making key decisions when working with autonomous, self-driving vehicles.

  7. 60–120 hours of effort

    Learn fundamental algorithms for sensor fusion and non-linear filtering with application to automotive perception systems. 

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