What the Master Thesis is about/background to the problem to investigate
Hand-eye alignment is the procedure of establishing a common coordinate system between a robot (industrial or cobot) and a vision sensor. This typically involves comparing several sensor observations of an object with corresponding positions reported by the robot, to determine how to transform sensor coordinates into robot coordinates.
The object localization accuracy of machine vision systems for Robot Guidance, such as the ones developed by SICK, is highly dependent on how accurately the hand-eye alignment transformation has been estimated. As a measure of the quality, the total reprojection error is often used. This does however not say anything about the possible sources to the error or the magnitude of their individual contributions, making it near impossible to know what to address when results are not satisfactory.
The master thesis work focuses on the following/example of research questions
Investigate and gain understanding of possible error sources that affect hand-eye alignment and consequently object localization accuracy, including but not limited to:
Develop methods/algorithms for finding and measuring contributions from the individual sources such that the result can be presented in an understandable way for a user to act on.
Prerequisites
Good skills, high interest in areas such as machine vision, robotics, programming, mathematics, and useability.
Contact
For more information about the position, contact:
Andreas Wrangsjö, Team Manager, Robot Guidance Systems, +46 728 530 320
or
Sarah Lantz, HR Business Partner, +46 739 10 99 37.
Welcome with your application 20th of October at the latest!
SICK is a world-leading supplier of sensors and sensor solutions for industrial applications. We are 11 000 employees in 50 countries and our headquarter is located in Freiburg, Germany. SICK in Linköping is an innovation center for Machine Vision and we are 80 committed employees with a big interest in image processing and visualization. For more than 35 years, our team at SICK Linköping has successfully developed and delivered software for technically leading products within the field of 2D and 3D vision, as well as system solutions for i.e. robot guidance and quality control.
At SICK in Linköping, we are very proud of being a healthy and attractive workplace. For many years, we have been elected as one of the best workplaces in Sweden according to the survey Great Place to Work, the latest award is from 2023. We work actively to reduce our climate footprint and we are active in various ways to contribute to the society and to increase diversity at our workplace.
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We are the People and Culture team at SICK Linköping. We can answer all your question on recruitment, life at SICK Linköping, student opportunities or and much more.
Charlotte Axelsson
charlotte.axelsson@sick.se
+46 739 20 99 50
Sarah Lantz
sarah.lantz@sick.se
+46 739 10 99 37
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