Schedule: 09.09.2019 - 09.12.2019
Contact information for the course (applies in this implementation):
Office hours: Please send an email to book an appointment.
Exercises and Project work
Dr. Muhammad Emzir (email@example.com), Office F307, Rakentajanaukio 2
Teaching Period (valid 01.08.2018-31.07.2020):
I-II 2018-2019 (autumn)
Learning Outcomes (valid 01.08.2018-31.07.2020):
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.
Content (valid 01.08.2018-31.07.2020):
The course content includes: Probabilistic modeling of dynamic systems, sensor models, batch estimation, Kalman and extended Kalman filtering, bootstrap particle filtering.
Assessment Methods and Criteria (valid 01.08.2018-31.07.2020):
Project work, exercises, and final examination
Workload (valid 01.08.2018-31.07.2020):
36 h contact teaching, 97 h independent studies
Study Material (valid 01.08.2018-31.07.2020):
Gustafsson: Statistical Sensor Fusion (2012), handouts
Details on the course materials (applies in this implementation):
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 mandatory).
Prerequisites (valid 01.08.2018-31.07.2020):
Basics of linear algebra and calculus, basic programming knowledge (MATLAB or Python), basics of statistics.
Grading Scale (valid 01.08.2018-31.07.2020):
Registration for Courses (valid 01.08.2018-31.07.2020):
Further Information (valid 01.08.2018-31.07.2020):
Language class 3: English
Details on the schedule (applies in this implementation):
Lectures: Lectures are held on Wednesdays, 14:15 - 16:00 (except for the first lecture on Monday, Sep 9, 2019, 14:15 - 16:00) in F175b, Health Technology House, Otakaari 3.Exercises: Exercise sessions are held on Mondays, 14:15 - 16.00 in F175b, Health Technology House, Otakaari 3, starting on Monday, Sep 16, 2019.