Computer Science, Second Cycle, AI Search Methods for Mobile Robots, 3 credits

Learning outcomes

Knowledge and understanding
After completion of this course, the student will have knowledge about three advanced applications of AI reasoning, namely: resource scheduling, robot motion planning, and multi-robot coordination. The student will understand the computational bottlenecks of different algorithms, and will have gained a deeper understanding of the limits of current state of the art methods.

Applied knowledge and skills
Completing this course, the student will be able to formulate real-world problems as search problems, and sketch methods to solve them based on heuristic, sampling-based and constraint-based search algorithms. The student will be able to develop solutions for particular applications that are relevant in industry, namely, scheduling, robot motion planning, and coordination of fleets of autonomous robots.

Making judgments and attitudes
Completing this course, the student will be able to judge the suitability of a particular approach to automated reasoning for a given problem, have an understanding of the capabilities and limitations of the considered algorithms. Furthermore, the student will understand how problem structure relates to computational overhead.

Content

• Overview of systematic and local search methods.
• Introduction to constraint reasoning, backtracking search, k-consistency.
• Temporal constraint reasoning, constraint-based resource scheduling.
• Lattice- and sampling-based robot motion planning algorithms.
• State of the art methods for multi-robot motion planning, coordination and control.

Examinations and grades

Exercises, 1.5 credits (Code: A001)
Grades used are Fail (U), Pass (G) or Pass with Distinction (VG).

Seminar Presentation, 1.5 credits (Code: A002)
Grades used are Fail (U), Pass (G) or Pass with Distinction (VG).

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 determine which grading system is to be used. The grade must be determined by a teacher specifically nominated by the university (the examiner).

In accordance with university regulations on grading systems for first and second-cycle courses and study programmes (Vice-Chancellor’s decision ORU 2018/00929), one of the following grades is to be used: fail (U), pass (G) or pass with distinction (VG). For courses included in an international master’s programme (60 or 120 credits) or offered to the university’s incoming exchange students, the A to F grading scale is to be used. The vice-chancellor, or a person appointed by them, may decide on exceptions from this provision for a specific course, if there are special grounds for doing so.

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

For students with a documented disability, the university may approve applications for adapted or other modes of assessment.

For further information, see the university's local examination regulations.

Specific entry requirements

At least 180 credits including 15 credits programming as well as qualifications corresponding to the course "English 5"/"English A" from the Swedish Upper Secondary School.

For further information, see the university's admission regulations.

Other provisions

The course is given in English.

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.

Reading list and other learning resources

Additional Reading

Dechter, Rina (2003)
Constraint Processing The Morgan Kaufmann Series in Artificial Intelligence
Elsevier Science, 480 sidor

LaValle, Steven (2006)
Planning algorithms
Cambridge university press, 831 sidor

Russell, Stuart, Norvig, Peter (2010)
Artificial Intelligence, A modern Approach Prentice Hall
Prentice Hall, 1132 sidor

Additional material (research articles) will be distributed during the course.