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Applied robot technology ELE610

The course is split into 2 parts: Image acquisition including image processing in Python, Robotstudio for robot control.

Course description for study year 2021-2022. Please note that changes may occur.

Course code




Credits (ECTS)


Semester tution start

Spring, Autumn

Number of semesters


Exam semester

Spring, Autumn

Language of instruction

English, Norwegian

Offered by

Faculty of Science and Technology, Department of Electrical Engineering and Computer Science

Learning outcome
The student should know how to:  1) Calibrate and use both simple and advanced cameras to capture images and transfer them to the target platform. 2) Use an industrial robot (ABB) and make simple programs for it. 3) Use the Python programming language to capture and process images and to communicate with an industrial robot.
This course gives an introduction to robot control and control of tools and sensors used in a robotic system. The course has two equal sized parts with 4 assignments in each part. The first part uses an image acquisition test rig to take images and transfer them to the target platform in (near to) real time. The second part is focused on the programming of industrial robots (ABB robots). It gives an introduction to RobotStudio and RAPID programming. There will be both computer simulations as well as programming of physical robots. Finally, in a larger assignment, the two previous parts shall be combined to locate pucks using a camera and pick and place the pucks using the robot. These tasks are controlled from a PC programmed with Python.
Required prerequisite knowledge
Form of assessment Weight Duration Marks Aid
9 compulsory laboratory exercises 1/1 Pass - Fail

All assignments must be passed to pass the course. No exam.

Coursework requirements
Electronic Course in Health, Safety and Environment
Completion of mandatory lab assignments are to be made at the times and in the groups that are assigned and published. Absence due to illness or for other reasons must be communicated as soon as possible to the laboratory personnel. One cannot expect that provisions for completion of the lab assignments at other times are made unless prior arrangements with the laboratory personnel have been agreed upon.
Course teacher(s)
Course coordinator: Karl Skretting
Course teacher: Morten Mossige
Course teacher: Jon Fidjeland
Course teacher: Trygve Christian Eftestøl
Laboratory Engineer: Ståle Freyer
Study Program Director: Tormod Drengstig
Head of Department: Tom Ryen
Method of work
There will be 4 hours of laboratory sessions and up to 2 hours of lectures per week. Completion of mandatory lab assignments are to be made at the times and in the groups that are assigned and published at Canvas.
Open for
Control Engineering and Circuit Design - Bachelor's Degree Programme City and Regional Planning - Master of Science Computer Science - Master's Degree Programme Robot Technology and Signal Processing - Master's Degree Programme Industrial Asset Management - Master's Degree Programme Petroleum Engineering - Master of Science Degree Programme Societal safety - Master's degree programme Technical Societal Safety - Master's Degree Programme
Course assessment
Form and/or discussion.
Overlapping courses
Course Reduction (SP)
Applied signal processing (MIK200) 3
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