AI & Cloud enabled vision system for agile teach-in of assembly processes

AI & Cloud enabled vision system for agile teach-in of assembly processes

The SpinEye project incorporates a human-robotic collaboration, premised on AI vision-system, which detects screw positions, provides Cloud inrastructure for training, monitoring and enhancement of the detection model.

The solution

A robust specialised Artificial Intelligence (AI) scheme that has been extensively trained on the collected data and validated on various samples has been adopted. This module is responsible for detecting and accurately localising screw holes on PCBs. Additionally, a teach-in user friendly interface, the so-called URcap, has been implemented for simplifying the hand-eye calibration process. Finally, a SpinEye low-cost box that controls the communication interfaces between all the components has been included.


Every day, millions of screws and bolts are mounted in the European manufacturing industry by employees with handheld screwdrivers in everything from windows to cars & electronic products. The Trinity demonstrator shows how to automate high/Mix – low/volume productions involving screw assembly task, by introducing an easy-to use camera system - SpinEye which is fast to setup and program.
Using camera technology in assembly tasks reduce the time it takes to program and deploy cobots for screw driving tasks.


Customers that will deploy SpinEye and will benefit from faster changeover between tasks, while there is also no need for highly skilled workers to set up an assembly task. The quality rate will be increased, as the vision system will be able to detect slight mispositions of the fixture and adjust the cobot’s instructions.

Facts and figures

  • Technology Area:

    Human-Robot Collaboration

  • End User:

    Electronic & Automotive industry and companies having final

  • Start Date - End Date:

    01/11/2021 - 31/08/2022

  • Duration:

    11 months

  • FSTP Funding:

    125,016,00 €

  • TRL Level at Start:


  • TRL Level at End:


  • Number of early adopters raised:


  • Project results
    back to success stories
    Subscribe to newsletter

    Please subscribe to our mailing list to be the first one informed about the new open calls, events and other hot news!

      Please check if the email you entered is correct
      All done!

      Your have successfully subscribed to Trinity newsletter.