Programplaner og emneplaner - Student
ACIT4820 Applied Robotics and Autonomous Systems Course description
- Course name in Norwegian
- Applied Robotics and Autonomous Systems
- Study programme
-
Master's Programme in Applied Computer and Information TechnologyMaster's Programme in Applied Computer and Information Technology, Elective modules
- Weight
- 10.0 ECTS
- Year of study
- 2020/2021
- Curriculum
-
FALL 2020
- Schedule
- Programme description
- Course history
-
Introduction
Bestått-Ikke bestått.
Recommended preliminary courses
Knowledge of linear algebra, vector calculus and basic statistics and probability.
Required preliminary courses
The following required coursework must be approved before the student can take the exam:
Four assignments in groups of 1 - 3 students (1000 - 2000 words per assignment)
Learning outcomes
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 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 applying 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.
Content
Topics covered in this course:
- Robot kinematics and dynamics
- Robotics sensors and actuators
- Navigation, state estimation and filtering algorithms
- Motion planning
- Computer vision and visual servoing
- ROS Robot Operating System
- Introduction to ML/AI methods in robotics
Teaching and learning methods
All, computer with MATLAB and Simulink.
Course requirements
Two internal examiners. External examiner is used periodically.
Assessment
Associate Professor Tiina Komulainen
Permitted exam materials and equipment
Basic course in control theory, linear systems and system dynamics. Basic understanding of matrix algebra, statistics, and programming using MATLAB or similar.
Grading scale
- Data driven dynamic modelling (system identification)
- State estimation
- Model-based PID-tuning methods
- Multivariable control algorithms
- Predictive control algorithms
- Implementation, testing and validation with numerical simulation.
Examiners
Two internal examiners. External examiner is used periodically.