Effect of data capture and calibration methods on the accuracy of extrinsic transformations

This topic outlines an internship opportunity focused on exploring the effects of data capture and calibration methods on the accuracy of extrinsic transformations between camera and robot coordinates in vision-guided robotics.

• Internship focus and goal: The project aims to investigate different strategies for capturing and calibrating the transformation matrix between camera and robot coordinates to determine their impact on calibration accuracy. This involves working with vision algorithms and robot positioning for applications like bin picking and quality inspection.
• Learning objectives: Interns will learn to steer collaborative robots in industrial settings, gather quality image data, explore various extrinsic calibration approaches, and set up experiments to compare these methods.

CANDIDATE PROFILE

Suitable candidates should have at least a bachelor's degree in engineering or science, knowledge of algebra and programming, and be proactive team players with good communication skills.

PRACTICAL DETAILS

The internship lasts between 2 to 6 months at Flanders Make in Kortrijk, Belgium, with all necessary resources provided. Only EEA or Swiss nationals are eligible for internships, while the thesis option is limited to Belgian university students.