INTERACTIVE COURSE ON EKF AND
This course is intended for beginners on Extended Kalman Filter and
Simultaneous Localization And Mapping.
It is based on the principle:
programs that work; we try to understand later".
We build Extended Kalman filters and SLAM programs from scratch.
work, and we are happy. See two snapshots:
The course consists on a series of videos (8h30 total time), and
It requires very basic knowledge of the Matlab syntax. It mostly
on Octave too, except possibly for some graphics functionalities and
some symbolic computations.
To take the best profit of the course, I strongly recommend you
the following procedure:
1. Open the video file and Matlab. Place them on
both sides of the screen (you can use two
screens if you prefer).
2. Play the video. Type in your editor EXACTLY
is being typed
on the video. Follow my comments and suggestions.
3. If you do not
understand anything, don't worry: keep on going and things will come
4. Execute the files you typed and see how your
produces amazing results.
5. Use the provided m-files to help fixing some
bugs you may make.
The videos advance at a very slow pace. I recommend you adopt
code, otherwise you will soon get
you type, you will learn very quickly.
Part I: Kalman Filter (KF) and Extended Kalman Filter (EKF). Total
time: 3h 30min.
the video with the introduction to KF (44 min, 24 MB).
the video with an example of a one-dimensional KF (51 min, 28 MB).
the video with the introduction to EKF (10 min, 6 MB).
the video with an example of a two-dimensional tracker (1h 45 min,
the support m-files.
Part II: 2D SLAM based on the EKF. Total time: 5h 00 min.
the PDF with a brief introduction to the theoretical background of
the video with the introduction to SLAM (54 min, 18 MB).
the video with the elementary SLAM observation functions (34 min, 19
the video with the robot motion function (35 min, 14 MB).
the video with main SLAM program (2h 53 min, 93 MB).
the video with an interesting bug correction (2 min, 1 MB).
the support m-files and pdf-file.