Basic Information
- Course Code: SC651
- Course Name: Estimation on Lie Groups
- Course Offered In: 2023-2024
- Semester Season: Spring
- Instructors: Prof. Ravi Banavar
- Prerequisites: No hard prerequisites, basics of linear systems recommended. A lot of sophomores were able to understand the course content.
- Difficulty (1 being easy and 5 being tough): 4
Course Content
Kalman Filter, static orientation estimation, introduction to Lie groups, various algorithms for pose estimation (static and dynamic) using tools from Lie groups and differential geometry.
Feedback on Lectures
The course involved reading and understanding papers on different orientation estimation algorithms. The professor would assign a few students a paper which they had to present in class and some tutorial sessions are conducted to give an introduction to differential geometry and Lie groups.
Feedback on Evaluations
Course evaluation consisted of 3 assignments and one paper review. The assignments were not very difficult (2/5) following the lectures and involved direct implementation of some algorithms discussed. A paper related to differential geometry/lie groups/orientation estimation (basically related to the course content) from any conference/journal has to be reviewed. It was an interesting way to explore the area :)
Study Material and Resources
A drive link containing papers related to orientation estimation algorithm is shared by the professor which suffices.
Follow-up Courses
None that I know of
Final Takeaway
The course requires quite a lot of self-study and many new mathematical tools are used. However, there is help provided by the instructor and the TA which might make it easier to grasp the content if you do your part of self-study. I would recommend it for people interested in pose estimation and SLAM.