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Kursteilnehmer-Bewertung und -Feedback für State Estimation and Localization for Self-Driving Cars von University of Toronto

641 Bewertungen
106 Bewertungen

Über den Kurs

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)....


13. Okt. 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.

8. Feb. 2020

One of the most exciting courses ever had in terms of learning and understanding. Kalman filter is a fascinating concept with infinite applications in real life on daily basis.

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51 - 75 von 105 Bewertungen für State Estimation and Localization for Self-Driving Cars

von Karthik B K

29. Juni 2019

Really Advanced and Challenging Course with great scope of gaining knowledge.

von Mehran R

15. Sep. 2020

It requires a bit of external studying, but in general, it's a great course.

von huseyin t

14. Feb. 2021

Perfect lecture. Nicely designed assignments and very nice reading advices.

von Levente K

1. März 2019

Sometimes hard, but still pretty much fun to solve all the problems :)

von 78 F V R S

15. Okt. 2020

I had an amazing experience got to learn new things from this course

von Ahmed E

12. Apr. 2020

This course was very useful. It will significantly help in my career

von Stefan M

15. Aug. 2019

From my point of view a very interesting and well prepared course.

von Kosinski K

25. Mai 2020

The great course! Very good presentations and nice projects.


13. Nov. 2020

Great Experience. I had learned some much from this course.

von UMAR T

4. März 2020

The last assignment for this module is very challenging.

von Akash B

16. Juni 2020

Course was good, need more guidance for calculations.

von Guillermo P G

13. Mai 2020

Amazing course, congratulations, I have learnt a lot!

von jinglong

27. Mai 2020

very nice tutorials for autonomous driving beginner.


8. Okt. 2019

it's really nice, and amazing course. I enjoyed it

von Felipe M G

26. Okt. 2020

This is a excellent course with great proffesors

von Varun J

13. Mai 2020

Indeed one of the best courses here at Coursera!

von Ansh S

14. Aug. 2020

Amazing specialisation to get aquainted to SLAM

von Jose C I G Z

9. Dez. 2020

Awesome course and very challenging!

von 刘宇轩

25. Apr. 2019

The projects are useful enough

von Shridhar N V

8. Juni 2020

Kalman filter was interesting

von Vishwas N

29. Apr. 2020

very nicely crafted course

von Luis E T R

13. Sep. 2020

An outstanding course

von Sujeet B

7. Dez. 2020

Lot's of learning...


28. Mai 2020

Many many thanks!


30. Mai 2020

Very Infomative!