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Automatic Calibration and Update of a Digital Twin for Plug & Produce

Mattias Bennulf,Sudha Ramasamy,Xiaoxiao Zhang,Fredrik Danielsson,Janardhanan Swathanandan

Published 2025 in Italian National Conference on Sensors

ABSTRACT

Highlights What are the main findings? A digital twin, consisting of an automated path planner and a simulation model, is proposed for an industrial robot to automatically adapt to new locations of resources that have been moved. The system should update the digital twin with calibrated values of the resource locations due to the tight tolerances in the processes and physical limitations of placing resources out precisely. What are the implications of the main findings? Using the proposed system, the manufacturing can still function if resources are moved around frequently. The camera-based solution for automating the measurement of resource locations was implemented in a physical demonstrator. Abstract This article presents a system for automatically updating a digital twin model, used for automated path planning of an industrial robot. The digital twin needs to be accurately calibrated in relation to the resource locations due to the physical limitations of placing resources out precisely. The process considered is a surface roughness measurement of aerospace metal parts that requires high positional accuracy. The scenario takes place in a robot cell that is a Plug & Produce system, where resources can be added and removed in minutes, allowing fast reconfiguration of the production resources. This means that an automated path planner is required for the robot to adapt to new locations of these resources automatically. A digital twin is proposed, consisting of a robot path planner and a simulation model that is updated when resources are added to the system. The resources should automatically appear in the simulation and be placed at an accurate location. The purpose of automating these steps is to make the update of the digital twin faster during production and remove the requirement for expert knowledge.

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