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.

The course has very advanced material and I value this course a lot. However I am very confused at some key concepts and didn't understand many details conceptually. For example it is not clear what is the difference between EKF and ES-EKF.

Also, for the final project the formulas have been given. I implemented the project using the formulas, but I didn't understand deeply enough the meaning of those formulas. For example what does Kalman Gain represent.

Maybe the topic is just so advanced, or maybe I should be reading more resources outside the lectures. But I finished the course with the feeling that I have a lot to learn in the space of localization and state estimation.

The content of the course is great, very useful and applicable ! The lectures are well told, animations are brilliant. I rate this course as 4 stars due to a low feedback activity from the teaching staff.

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!

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