Table of contents

The course is connected to the following study programs

Teaching language

Norwegian or English

Recommended previous knowledge

ING100, MAS239 or equivalent.

Learning outcomes

On successful completion of the course, the student should be able to:

  • understand basic operating principles of different sensors and measurement techniques
  • describe and implement mathematical models of measurement systems
  • combining sensors data represented in different coordinate systems (reference frames) using sensor fusion
  • transform the state variables and measurements between different coordinate systems (reference frames)
  • set up kinematic models for robots
  • use the most common sensors for tasks such as localization, navigation, and manipulation

Contents

Instrumentation and usage of sensors, robot localization and navigation, robot kinematics and odometry modelling, transformation between different coordinate systems, sensor uncertainty and statistical models, sensors for measuring distances such as LIDARs and radars, signal noise and losses, analog and digital signals, signal sampling, point cloud processing, sensor fusion techniques such as the Kalman filter, use of encoders for predicting robot movement in a dead reckoning algorithm, experimental work with sensors and robots, for example mobile robots.

Examinations

Portfolio consisting of tests and a written assigment. Graded assessment. More information about the portfolio will be given in Canvas. There will not be arranged a postponed exam for the portfolio.

Offered as a free-standing course

Yes
Last updated from FS (Felles studentsystem) Oct. 15, 2026 9:34:41 AM