Welcome to the course Basics of Sensor Fusion.
Roland Hostettler (firstname.lastname@example.org)
Office F308, Rakentajanaukio 2
hours: Generally between 13.00 and 16.00 on workdays, but requesting an
appointment by e-mail beforehand is highly recommended to ensure that
Filip Tronarp (email@example.com)
Office F322, Rakentajanaukio 2
Intended Learning Outcomes
After successfully completing this course, the participants are able to:
- explain the principles and components of sensor fusion systems,
- construct continuous- and discrete-time state-space models based on ordinary differential equations, difference equations, and physical sensor models,
- identify and explain the differences between linear and nonlinear models and their implications on sensor fusion,
- develop and compare state-space models and Kalman as well as particle filtering algorithms for solving sensor fusion problems.
Assessment Methods and Criteria
Achievement of the intended learning outcomes is assessed through an individual written exam as well as a group project work.
To pass the course, you need to:
- pass the written exam,
- pass the project.
Written exam: The written exam is a pen and paper exam. Allowed aids:
- One (1) hand-written A4 paper with notes (written by yourself, i.e., not written w/ computer, not copied from your peers, etc.)
- No lecture notes, books, etc.
The grading scale for both the exam and the project is 0-5. The final grade is the average of the written exam and the project.
The course is mainly based on lecture notes and handouts that will be
made available on the course homepage. Optionally, the students may also
purchase the textbook "Statistical Sensor Fusion" by F. Gustafsson (not
Basic knowledge of linear algebra, mathematical statistics, and calculus is required. Knowledge of signals and systems, estimation theory, and electronics may come in handy but is not required.
Lectures: Lectures are held on Wednesdays, 08:15 - 10:00 (except for the first lecture on Monday, Sep 10, 2018, 14:15 - 16:00) in R037/1199 TU6.
Preliminary schedule (may be subject to changes):