Towards Automated 3D reconstruction in SME factories and Digital Twin Model generation

Abstract

This paper presents preliminary results towards the development of digital twin models for Small to Medium Enterprise (SME) factories in a partially automated and cost-effective manner. In many cases it is desirable to obtain a 3D model of a factory floor and machinery, that can be used for visualization of Digital Twin models. Current commercial 3D reconstruction solutions involve the use of high-end LiDAR sensors which increase the cost of the 3D scanning process and suppose a barrier for SME factories on their path towards Industry 4.0. The paper presents a comparison of 3D reconstruction results using low-cost sensors including a Zenfone AR mobile phone, an Intel RealSense ZR300 and a Kinect v2. The small size and weight of the sensors make it possible to be mounted on small unmanned aerial vehicles and enable future 3D reconstruction in an autonomous manner. The data was processed using an open source Simultaneous Localization and Mapping (SLAM) library RTAB-Map. The results were compared with a professional 3D scan using a GeoSLAM LiDAR. Experimental results from a scanning of a university research lab with a small simulated production line and two UR3 industrial manipulators is presented. The obtained 3D model was used to generate a simple Digital Twin model that can be visualized using a VR headset.