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: Deep Learning
Status: Mathematical Modeling
AdvancedCourse27 hours

Featured reviews

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.

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...

FI

4.0Reviewed Sep 24, 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

SS

4.0Reviewed Aug 12, 2019

For new learners, this course provides the beginner to intermediate knowledge. The explanation with examples are quite interesting and easy.

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.

MI

5.0Reviewed Aug 11, 2019

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

JG

5.0Reviewed Apr 18, 2023

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

ZR

5.0Reviewed 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.

DC

5.0Reviewed May 17, 2019

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

TM

5.0Reviewed Jun 11, 2024

This is an eye-opening course on how to utilize statistical analysis for engineering applications, and in particular, autonomous systems, as such it is very useful and captivating course!!!

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.

CA

5.0Reviewed Mar 19, 2021

Challenging but very fun. Not for beginners, you certainly need to know your math and be good enough a coding. Very recommended introduction to state estimation.

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