What the Master Thesis is about/background to the problem to investigate
There are many methods for how to estimate the 6D pose of an object in an rgbd (color and depth) image. Traditional methods have recently met competition from Deep Learning based methods. This project aims to evaluate the leading traditional and learning based methods to where we currently find the state of the art.
The master thesis work focuses on the following/example of research questions
Do a state of the art search of traditional and learning based methods and get an understanding of how they works (Eg. nvlabs.github.io/FoundationPose/). Compare some of them based on at least these criteria:
- Localization performance, false positive/false negative
- Localization accuracy
- Speed
- Ease of use
Prerequisites
Good skills and high interest in areas such as machine vision, machine learning and programming.
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 12 000 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 90 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
