School of Science and Technology

Course Syllabus

General aims for second cycle education

Second-cycle courses and study programmes shall involve the acquisition of specialist knowledge, competence and skills in relation to first-cycle courses and study programmes, and in addition to the requirements for first-cycle courses and study programmes shall
- further develop the ability of students to integrate and make autonomous use of their knowledge
- develop the students' ability to deal with complex phenomena, issues and situations, and
- develop the students' potential for professional activities that demand considerable autonomy, or for research and development work.

(Higher Education Act, Chapter 1, Section 9)

Knowledge and understanding
The student shall after the completion of the course:
have good knowledge of state-of-the-art algorithms using statistical estimation techniques for solving tasks that are central to mobile robotics, and understand their mathematical background.

Applied knowledge and skills
Completing this course, the student will be able to:
develop software for common robot tasks (such as localisation and classification).

Making judgments and attitudes
Completing this course, the student will have an increased capability to:
understand the virtues and limitations of statistical approaches to solving robotics problems.

The course has the following contents:
- Mathematical statistics: Bayes" theorem, probability distributions, generative and discriminative models
- Kalman filters
- Particle filters
- Monte Carlo optimisation
- Robot motion and sensor models
-SLAM (simultaneous localisation and mapping)
- Data association
-Random fields (Markov random fields and conditional random fields)
- Classification

Lectures and a project assignment.

Students who have been admitted to and registered on a course have the right to receive tuition and/or supervision for the duration of the time period specified for the particular course to which they were accepted (see, the university's admission regulations (in Swedish)). After that, the right to receive tuition and/or supervision expires.

For further information, see the university's local examination regulations (in Swedish).

According to the Higher Education Ordinance, Chapter 6, Section 18, a grade is to be awarded on the completion of a course, unless otherwise prescribed by the university. The university may prescribe which grading system shall apply. The grade is to be determined by a teacher specifically appointed by the university (an examiner).

According to regulations on grading systems for first- and second-cycle education (vice-chancellor's decision 2010-10-19, reg. no. CF 12-540/2010), one of the following grades is to be used: fail, pass, or pass with distinction. The vice-chancellor or a person appointed by the vice-chancellor may decide on exceptions from this provision for a specific course, if there are special reasons.

Grades used on course are Fail (U), Pass (G) or Pass with Distinction (VG).

For further information, see the university's local examination regulations (in Swedish).

The applicant must have completed a Bachelor degree, comparable to a Swedish Bachelor degree, from an institution of higher education of three years or more. The Bachelor degree must include courses in mathematics: calculus, algebra and computer engineering: programming, algorithms and data structures. If the applicant's first language is not English, knowledge in English must be documented by an internationally recognized proficiency test.

For further information, see the university's admission regulations (in Swedish).

Students who have previously completed higher education or other activities are, in accordance with the Higher Education Ordinance, entitled to have these credited towards the current programme, providing that the previous studies or activities meet certain criteria.

For further information, see the university's local credit transfer regulations (in Swedish).

The course will be taught in English.


Reading List and Other Teaching Materials

Required Reading

Ytterligare material kan utdelas under kursens gång.
Additional material (e.g., scientific papers) may be assigned by the instructor(s).

See this Course Syllabus as PDF