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

4.7
stars
807 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

GN

Oct 29, 2019

best online course so far that explains kalman filter and estimation methods with examples not just focusing on theoretical ,Thanks to the Dr's and course staff who worked hard to produce this course.

WS

Oct 13, 2019

There are many interesting topics. Without the help and suggested readings from this course, I wouldn't be able to finish by myself. Also, the final project is very enlightening.

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26 - 50 of 129 Reviews for State Estimation and Localization for Self-Driving Cars

By zhen l

Apr 12, 2019

This is a fast paced course on state estimation. ES Kalman Filter is the focus of the final project. Lectures cover basics of Kalman filter very thoroughly. You need to spend quite some time to sort out complexity to finish the final project, yet the efforts are well spent. You will only graph the fundamentals after hard projects. Overall, a very well organized and executed course. Highly recommended.

By Ravi A

May 1, 2020

This course provides a lot of insights in various sensors used for pose estimation and also delves into multi sensor fusion which gives the knowledge and importance about the sensor calibration. Overall a very well taught course and the most important one for who want to pursue a career in self driving cars.

By Rama C R V

Apr 19, 2020

Firstly, I would like to start thanking Prof. Jonathan Kelley for making good illustration. I felt it could be better discussing more about sizes of covariance matrices, so that it would help in better understanding of the algebra. Overall a good taught and informative course. Thank you Coursera.

By Abdullah B A

Sep 25, 2019

excellent course with a lot of valuable and up to date information that is used in real modern self driving cars, it was challenging and very hard for me to go through but i assure you that it's worthy of the hard work required to pass it

By Mario d R

Nov 14, 2020

Excellent course. You go from learning the basic concept of state estimation and localization all the way to solving a realistic state estimation problem. The course is quite dynamic, mixing theoretical concepts with real implementation.

By Himanshu B

Jul 12, 2019

Got to learn about many concepts like least squares, Kalman filter, GNSS/INS sensing, LIDAR Sensing. Programming assignments were the most difficult part of this course. And definitely going towards the next course in the specialization.

By Shashank K S

Sep 22, 2020

Quite a mathematically extensive course, but how the instructors teach will clear all your doubts! The concepts taught apply not only to Self Driving Cars but for any general system. All in all, an excellent course for State Estimation.

By Kushagra S

Jun 19, 2020

The programming assignments given tested us on how well we understood the fundamentals of localization. The solutions were not trivial and one had to think while programming which speaks to how well these assignments were designed

By Vadim N

Sep 11, 2022

Complex, informative and thoughtful course. It can be seen that the authors spent a lot of time preparing it. For me, it was one big puzzle, which was a pleasure to pass. Thanks to the Authors for their work!

By Daniele C

Jul 30, 2020

One of the best courses I had on Coursera. Some modules are apparently easy and fast, but the whole course should be well understood in order to pass the final assignment. I had to go back and forth for th

By Gasser N

Oct 30, 2019

best online course so far that explains kalman filter and estimation methods with examples not just focusing on theoretical ,Thanks to the Dr's and course staff who worked hard to produce this course.

By Yusen C

Mar 10, 2019

Could we use C++ to program the projects?

And also, in most assignments, please make sure every requirements and additional information are CORRECT and CLEAR! Now, some of them are REALLY MISLEADING!

By Ju-Hsuan C

Feb 10, 2021

The course is informative and well constructed for learners. The final project is designed well so that we can build sensor fusion tools while applying what we have learned from this course.

By Molin D

Nov 10, 2020

Very good to learn Kalman Filter, and Extened Kalman Filter, espcially the good explanation on why it is effective, and restriction (when it is noise, etc).

By Zillur R

Feb 8, 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.

By Mohammad N M

May 22, 2020

A great Journey for anyone interested in Self Driving Cars. State estimation is vital in this field and this is a great course to start learning it!

By Jithesh

Nov 22, 2020

Well Planned course. Giving introduction level details to domain State estimation and localization. Very great detail of Kalman Filter available.

By Jairo G

Nov 26, 2020

Really interesting content and test. Definitely there are lots of advance concepts, so you will need to dedicate quite a lot of time to success.

By José A A G

Apr 19, 2023

Very challenging, nevertheless excelent for learning automation concepts, python programming, sensor fusion, probability & statistics

By Eric J

Dec 14, 2021

I have learned KF in the past. First time learning EKF. I liked the rigor in this course! Felt like a legitimate university lesson.

By Davide C

May 18, 2019

Finishing this course was quite challenging, but I did it. Thanks a lot to the professors for the clear explanations.

By Matthias P

Jun 13, 2020

A lot of fun! I learnt a lot and feel that due to the well designed assignments I really got to the bottom of it...

By Aaryaman B

Sep 6, 2020

great course but there's really a big need to provide assistance in assignments like hints, equations etc

By Eshan M “ H

May 25, 2020

Challenging, interesting and intriguing.. In simple, an awesome course for any engineering mind !

By Yan D

Feb 1, 2020

Very good course! I learned how to implement multiple sensor fusion into practice. Thank you!