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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

MI

Aug 12, 2019

Very interesting course if you want to learn about the different filters used in self driving cars for sensor fusion

FI

Sep 25, 2019

Challenging course, specially the assignments. The extra literature resources are great. The explanations and examples on the videos could improve. Step by step Hands On examples would fit great

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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 27, 2020

This is a excellent course with great proffesors

By Varun J 1

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May 14, 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 24, 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 10, 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 9, 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 2, 2024

It was a great course

By Luis E T R

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Sep 14, 2020

An outstanding course

By Sujeet B

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Dec 8, 2020

Lot's of learning...

By Davi B

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Sep 26, 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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Nov 1, 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 3, 2020

excelente

By Cesar Q

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Oct 16, 2021

Love it!

By Matías F

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Jan 19, 2021

amazing!