Thesis - Targetless Alignment of Multiple 3D Cameras

When multiple 3D cameras acquire images of the same object, one gets multiple point clouds from different points of view. There is often a wish for aligning (or registering) these into a single point cloud. One approach is to use a target with known features, to estimate the alignment of the cameras. However, it is often difficult to ensure all cameras see the appropriate features of the target.

Global Registration methods often perform registration without specific known landmarks or features.
The thesis suggestion is to investigate the usage of recent global registration methods such as Deep Global Registration for use as a targetless alignment procedure.

In this master thesis you will get an opportunity to work with real hardware to solve industry close and relevant problems.

The master thesis work focuses on the following/example of research questions

• What benefits and drawbacks does various modern global registration methods have?
• Can a targetless alignment procedure be built on top of these methods?
• How could a targetless alignment be achieved when it’s not possible to get overlap between the point clouds?

 Prerequisites

The thesis requires knowledge in image processing and mathematics.

Contact

For more information about the position, contact:

Andreas Öberg, Application Developer, andreas.oberg@sick.se

or

Charlotte Axelsson, HR Manager, charlotte.axelsson@sick.se

Welcome with your application 14^th 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 2021. 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.