Back to State Estimation and Localization for Self-Driving Cars
University of Toronto

State Estimation and Localization for Self-Driving Cars

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).

Status: Mathematical Modeling
Status: Robotics
AdvancedCourse27 hours

Featured reviews

AQ

5.0Reviewed Feb 8, 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.

YC

5.0Reviewed Mar 9, 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!

EJ

5.0Reviewed Dec 13, 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.

JG

5.0Reviewed Apr 18, 2023

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

GN

5.0Reviewed 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.

GH

5.0Reviewed Apr 28, 2019

one of best experiences. But the course requires a steep learning curve. The discussion forums are really helpful

DM

5.0Reviewed Jun 21, 2025

The course is highly informative and offers excellent opportunities to gain practical, hands-on skills essential for real-world autonomous vehicle applications.

MP

5.0Reviewed Jun 12, 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...

MM

5.0Reviewed May 21, 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!

RL

5.0Reviewed Apr 26, 2019

It provides a hand-on experience in implementing part of the localization process...interesting stuff!! Kind of time-consuming so be prepared.

WS

5.0Reviewed 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.

SI

4.0Reviewed Jul 16, 2020

Thank you for this absolutely fantastic course. Kalman filters and state estimation in general is a concept that I've tried to understand for a long time, and I'm glad to have finally understood it!

All reviews

Showing: 20 of 136

Jon Hauris
1.0
Reviewed Jun 4, 2019
MachWave
3.0
Reviewed Jul 1, 2019
Radovan Miucic
1.0
Reviewed Jun 7, 2019
Asad Qureshi
5.0
Reviewed Feb 9, 2020
Wit Sirawit
5.0
Reviewed Oct 14, 2019
Guruprasad M Hegde
5.0
Reviewed Apr 29, 2019
Remon Girard
5.0
Reviewed Aug 12, 2019
Hemanth Kumar K
5.0
Reviewed May 23, 2021
River Liu
5.0
Reviewed Apr 27, 2019
D.B
1.0
Reviewed Apr 5, 2020
Joachim Schmidtchen
5.0
Reviewed Jun 11, 2019
Qi Wen
5.0
Reviewed Jan 11, 2021
Carlos Argueta
5.0
Reviewed Mar 19, 2021
Muhammad Hameem Safwat Husain Javid Iqbal
5.0
Reviewed Aug 12, 2019
carlos sanoja
5.0
Reviewed Dec 5, 2019
anis
5.0
Reviewed Dec 6, 2019
Georgios Tepteris
5.0
Reviewed Jul 30, 2019
Deleted Account
5.0
Reviewed Nov 17, 2019
Kasra Dalvand
1.0
Reviewed Oct 12, 2020
Andrea Baldacci
1.0
Reviewed Jun 16, 2020