Programplaner og emneplaner - Student
ACIT5930 Master's Thesis, Phase 3 Course description
- Course name in Norwegian
- Master's Thesis, Phase 3
- Study programme
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Master's Programme in Applied Computer and Information Technology
- Weight
- 30.0 ECTS
- Year of study
- 2025/2026
- Curriculum
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SPRING 2026
- Schedule
- Programme description
- Course history
-
Introduction
The master's thesis is a specialized individual research project. Phase 3 is dedicated to final analysis and/or prototype development and writing the Master's thesis. Prototypes and/or other products that are developed as part of the project can also be part of the final thesis.
In addition, there will be a series of workshops on the academic writing and effective communication of the thesis project, building on the workshops in Phase 1 and 2. Students will develop an awareness of the conventions of academic writing and the writing process and use a range of analytical tools and methods to develop their writing and writing practices as part of writing their thesis.
Guidelines for master's theses at the Faculty can be found here: Retningslinjer for masteroppgaver ved Fakultet for teknologi, kunst og design - Student - minside (oslomet.no)
Required preliminary courses
The student should have the following outcomes upon completing the course:
Knowledge:
Upon successful completion of the course, the student should have:
- advanced knowledge on robotic and autonomous systems components and architecture
- advanced knowledge in modeling kinematics and dynamics of robotic systems
- advanced knowledge in common sensor and actuator technologies used in robotics
- have advanced knowledge of algorithms and methods used in state estimation, navigation, and motion planning
- a good understanding of the Robot Operating System (ROS) and software architectures used in robotic and autonomous systems
Skills:
Upon successful completion of the course, the student can:
- analyze a robotic and autonomous systems with regard to its components, architecture, and their purpose
- model and analyze kinematic and dynamics of robotic systems
- apply a number of algorithms and methods in state estimation, navigation, and motion planning
- analyze and implement solutions based on Robot Operating System (ROS)
General competence:
Upon successful completion of the course, the student can:
- discuss the role of robotic and autonomous systems in a number of practical applications
- analyze how robotic and autonomous systems operate and design specific components using ROS and other software tools.
Learning outcomes
This course will feature weekly lectures and lab work to provide both theoretical and hands- on experience. Students will work in groups and complete assignments given to them. The student will supplement the lectures and lab with their own reading. The students will also work on a individual project.
Content
Teaching and learning methods
The following coursework must be approved before the student can take the exam:
Four assignments in groups of 1-3 students (1000 - 2000 words per assignment)
Course requirements
The assessment will be based on two part-exams:
1) Individual project report (4000-6000 words). The project report counts 80% of the final grade.
2) Individual project presentation (10 minutes). The presentations will be open to public. The oral examination counts 20% of the final grade
Both exams must be passed in order to pass the course.
The oral examination cannot be appealed.
New/postponed exam
In case of failed exam or legal absence, the student may apply for a new or postponed exam. New or postponed exams are offered within a reasonable time span following the regular exam. The student is responsible for registering for a new/postponed exam within the time limits set by OsloMet. The Regulations for new or postponed examinations are available in Regulations relating to studies and examinations at OsloMet.
Assessment
All aids are permitted, provided the rules for plagiarism and source referencing are complied with.
Permitted exam materials and equipment
Grade scale A-F.
Grading scale
Two internal examiners. External examiner is used periodically.
Examiners
Alex Alcocer
Course contact person
Knowledge of linear algebra, vector calculus and basic statistics and probability. Knowledge of programming in python and basic introductory course on control or dynamical systems is recommended.