Sensor Fusion and Non-linear Filtering for Automotive Systems
link Source: www.edx.org
date_range Starts on May 5, 2021
event_note Ends on June 30, 2021
list 8 sequences
assignment Level : Advanced
chat_bubble_outline Language : English
card_giftcard 1,120 point
Logo My Mooc Business

Top companies choose Edflex to build in-demand career skills.

Get started
Users' reviews
-
starstarstarstarstar
0 reviews

Key Information

credit_card Free access
verified_user Fee-based Certificate
timer 80 hours in total

About the content

In this course, we will introduce you to the fundamentals of sensor fusion for automotive systems. Key concepts involve Bayesian statistics and how to recursively estimate parameters of interest using a range of different sensors.

The course is designed for students who seek to gain a solid understanding of Bayesian statistics and how to use it to fuse information from different sensors. We emphasize object positioning problems, but the studied techniques are applicable much more generally. The course contains a series of videos, quizzes and hand-on assignments where you get to implement many of the key techniques and build your own sensor fusion toolbox.

The course is self-contained, but we highly recommend that you also take the course ChM015x: Multi-target Tracking for Automotive Systems. Together, these courses give you an excellent foundation to tackle advanced problems related to perceiving the traffic situation around an autonomous vehicle using observations from a variety of different sensors, such as, radar, lidar and camera.

  • Basics of Bayesian statistics and recursive estimation theory
  • Describe and model common sensors, and their measurements
  • Compare typical motion models used for positioning, in order to know when to use them in practical problems
  • Describe the essential properties of the Kalman filter (KF) and apply it on linear state space models
  • Implement key nonlinear filters in Matlab, in order to solve problems with nonlinear motion and/or sensor models
  • Select a suitable filter method by analysing the properties and requirements in an application

more_horiz Read more
more_horiz Read less
report_problem

Prerequisite

Mathematical statistics and MATLAB.

dns

Syllabus

Section 1 - Introduction and Primer in statistics
Section 2 - Bayesian statistics (Week 1)
Section 3 - State space models and optimal filters (Week 1)
Section 4 - The Kalman filter and its properties (Week 2-3)
Section 5 - Motion and measurements models (Week 2-3)
Section 6 - Non-linear filtering (Week 4)
Section 7 - Particle filter (Week 5)

record_voice_over

Instructors

Lars Hammarstrand
PhD, Electrical engineering
Chalmers University of Technology

store

Content Designer

Chalmers University of Technology
Chalmers University of Technology
assistant

Platform

Edx

Harvard University, the Massachusetts Institute of Technology, and the University of California, Berkeley, are just some of the schools that you have at your fingertips with EdX. Through massive open online courses (MOOCs) from the world's best universities, you can develop your knowledge in literature, math, history, food and nutrition, and more. These online classes are taught by highly-regarded experts in the field. If you take a class on computer science through Harvard, you may be taught by David J. Malan, a senior lecturer on computer science at Harvard University for the School of Engineering and Applied Sciences. But there's not just one professor - you have access to the entire teaching staff, allowing you to receive feedback on assignments straight from the experts. Pursue a Verified Certificate to document your achievements and use your coursework for job and school applications, promotions, and more. EdX also works with top universities to conduct research, allowing them to learn more about learning. Using their findings, edX is able to provide students with the best and most effective courses, constantly enhancing the student experience.

You are the designer of this MOOC?
What is your opinion on this resource ?
Content
5/5
Platform
5/5
Animation
5/5