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Back to State Estimation and Localization for Self-Driving Cars

Learner Reviews & Feedback for State Estimation and Localization for Self-Driving Cars by University of Toronto

4.7
stars
838 ratings

About the Course

Welcome to State Estimation and Localization for Self-Driving Cars, the second course in University of Toronto’s Self-Driving Cars Specialization. We recommend you take the first course in the Specialization prior to taking this course. This course will introduce you to the different sensors and how we can use them for state estimation and localization in a self-driving car. By the end of this course, you will be able to: - Understand the key methods for parameter and state estimation used for autonomous driving, such as the method of least-squares - Develop a model for typical vehicle localization sensors, including GPS and IMUs - Apply extended and unscented Kalman Filters to a vehicle state estimation problem - Understand LIDAR scan matching and the Iterative Closest Point algorithm - Apply these tools to fuse multiple sensor streams into a single state estimate for a self-driving car For the final project in this course, you will implement the Error-State Extended Kalman Filter (ES-EKF) to localize a vehicle using data from the CARLA simulator. This is an advanced course, intended for learners with a background in mechanical engineering, computer and electrical engineering, or robotics. To succeed in this course, you should have programming experience in Python 3.0, familiarity with Linear Algebra (matrices, vectors, matrix multiplication, rank, Eigenvalues and vectors and inverses), Statistics (Gaussian probability distributions), Calculus and Physics (forces, moments, inertia, Newton's Laws)....

Top reviews

HK

May 22, 2021

The course gave a clear and an in-depth knowledge on Kalman filters and Localisation using those filters. The assignments were pretty tough but solving them was fun.

ZR

Feb 7, 2023

Video lectures arer great. Programming assignments are also well designed. I just hoped more info of how input data for the last assignment was acquired.

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76 - 100 of 136 Reviews for State Estimation and Localization for Self-Driving Cars

By Felipe M G

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Oct 26, 2020

This is a excellent course with great proffesors

By Varun J 1

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May 13, 2020

Indeed one of the best courses here at Coursera!

By Ansh S

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Aug 14, 2020

Amazing specialisation to get aquainted to SLAM

By ER G D

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Mar 23, 2021

Very informative course. I really enjoyed it!

By DHAYAPULLESAIPAVAN R

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May 26, 2021

nice but,some part are not clearly explained

By José C I G Z

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Dec 9, 2020

Awesome course and very challenging!

By 刘宇轩

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Apr 25, 2019

The projects are useful enough

By shridhar v

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Jun 8, 2020

Kalman filter was interesting

By 张志萌

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Mar 8, 2022

very good course. Thank you

By Vishwas N

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Apr 29, 2020

very nicely crafted course

By Muneeb J m

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Feb 1, 2025

it was good experience

By Johnnylee

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May 16, 2022

课程内容很充实又有意义，希望有准确的中文字幕

By Seyed M A S

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Mar 1, 2024

It was a great course

By Luis E T R

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Sep 13, 2020

An outstanding course

By Sujeet B

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Dec 7, 2020

Lot's of learning...

By Davi B

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Sep 25, 2022

Excelente curso!

By Bao N

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May 28, 2020

Many many thanks!

By MIHIR R J

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May 30, 2020

Very Infomative!

By mert s

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Oct 31, 2019

excellent course

By Satwik C

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Nov 4, 2023

Good course

By Adam A A

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Mar 2, 2021

just pefect

By ILYESS D

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Aug 5, 2024

good cours

By Arturo A E O

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Sep 2, 2020

excelente

By Cesar Q

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Oct 15, 2021

Love it!

By Matías F

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Jan 18, 2021

amazing!