Main Field of Study and progress level:
Computing Science: Second cycle, has only first-cycle course/s as entry requirements
Electronics: Second cycle, has only first-cycle course/s as entry requirements
Grading scale: Three-grade scale
Responsible department: Department of Computing Science
Established by: Faculty Board of Science and Technology, 2022-03-28
Revised by: Faculty Board of Science and Technology, 2023-02-27
A mobile robot is a robot that is capable of moving around in a physical environment. This course teaches fundamental theories and algorithms in mobile robotics, including mapping, localization, and navigation. The theory is applied by constructing software for mobile robot systems using a robotics middleware (e.g., the Robot Operating System, ROS). The course includes an introduction to a robotics middleware. The developed robot software is tested using physical robots and/or advanced simulators.
Expected learning outcomes
Knowledge and understanding After completing the course, the student should be able to:
(FSR 1) explain the operational principles of (and distinctions between) various types of mobile robot architectures
(FSR 2) give a detailed account of theories and algorithms for mapping and localization
(FSR 3) give a detailed account of theories and algorithms for path and motion planning
Competence and skills After completing the course, the student should be able to:
(FSR 4) independently construct and deploy software for an autonomous mobile robot capable of mapping, localization, path planning, and motion planning
(FSR 5) clearly document theories, algorithms, experiments, and results of a mobile robotics project and present it both orally and in the form of a written report
Judgement and approach After completing the course, the student should be able to:
(FSR 6) discuss ethical problems related to practical applications of mobile robots
At least 90 ECTS, including 15 ECTS programming and 7.5 ECTS artificial intelligence. Proficiency in English equivalent to the level required for basic eligibility for higher studies.
Form of instruction
The instruction includes lectures, group exercises, student presentations, and computer and robot labs. In addition to scheduled activities, the course requires individual work with the material.
This course uses the grade scale Fail (U), Pass (G), or Pass with distinction (VG). The theoretical part (FSRs 1-3, 6) is assessed by a written exam. The practical part (FSRs 4-5) is assessed through group assignments that include written reports and oral presentations. The grade takes into account all parts of the examination. The theoretical and practical parts have equal weight.
Adapted examination The examiner can decide to deviate from the specified forms of examination. Individual adaptation of the examination shall be considered based on the needs of the student. The examination is adapted within the constraints of the expected learning outcomes. A student that needs adapted examination shall no later than 10 days before the examination request adaptation from the Department of Computing Science. The examiner makes a decision of adapted examination and the student is notified.
This course may not be included in a degree, in whole or in part, at the same time as another course with similar content. In case of doubt, the student should consult the study counsellor at the Department of Computing Science and/or the programme coordinator for their degree programme.
If the syllabus has expired or the course has been discontinued, a student who at some point registered for the course is guaranteed at least three examinations (including the regular examination) according to this syllabus for a maximum period of two years from the syllabus expiring or the course being discontinued.
2023 week 26
Murphy Robin R. Introduction to AI robotics Second edition : Cambridge, Massachusetts : The MIT Press :  : xxiii, 620 sidor : ISBN: 9780262038485 Mandatory Search the University Library catalogue