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Photoneo is a leading provider of robotic vision and intelligence. Based on a patented 3D technology, Photoneo developed the world’s highest-resolution and highest-accuracy 3D camera, thus unlocking the full potential of powerful, reliable, and fast machine learning.

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Bin picking application in a university lab

POSTED 07/06/2021

Partner:

JAMK University of Applied Sciences

 

Problem:

The JAMK University of Applied Sciences provides robotics testing and piloting services, training, and RDI activities for external companies. The companies are interested in testing bin picking and 3D machine vision solutions for their needs. These applications have different kinds of requirements and Photoneo PhoXi 3D Scanner proved to be adaptable and suitable for a wide range of use cases.

JAMK students are studying machine vision as part of their automation engineering studies. 3D machine vision is major sensing technology in robotics and with this kind of solutions and systems, the university was able to set up a modern laboratory environment for education in this field.

 

Solution:

PhoXi 3D Scanner M + Bin Picking Studio

One of the applications is an automated process of tiles picking. This task comprises the detection and picking of tiles in a pile of tiles as delivered by the supplier. The major challenge of the application is the arrangement of tiles – being tightly stacked next to each other with minimal contrast between the tile edges and their top surfaces. Another challenge resided in the height of the pile, which is dramatically changing during the bin picking process. This means that the focus area of the deployed 3D vision changes as well.

Besides the Bin Picking Studio and PhoXi 3D Scanner from Photoneo, the application deploys collaborative robots UR5 and TM12.

 

Discussion:

The plug & play and easy-to-use Photoneo system enabled getting the application ready within a few days instead of weeks. Another advantage of Photoneo solution is that it does not require any specific illumination.

The case study is a proof-of-concept, successfully demonstrating how traditional manual labor can be reduced using automation solutions, freeing human workers for other, less monotonous and health-detrimental tasks.