Deep learning-based 5G indoor positioning in a manufacturing environment

Indoor positioning systems are an enabling technology for many current developments in the manufacturing field like digital twins and robot fleet management. Utilizing 5G for positioning promises high accuracy, reliability, and cost-efficiency due to shared hardware usage for communication and posit...

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Bibliographic Details
Published in2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA) pp. 1 - 4
Main Authors Vietz, Hannes, Locklin, Andreas, Ben Haj Ammar, Hamza, Weyrich, Michael
Format Conference Proceeding
LanguageEnglish
Published IEEE 06.09.2022
Subjects
5G mobile communication
AGV
artificial intelligence
Deep learning
Digital twins
Hardware
indoor positioning
intralogistics
localization
Manufacturing
mobile robots
Production facilities
Reliability
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Summary:Indoor positioning systems are an enabling technology for many current developments in the manufacturing field like digital twins and robot fleet management. Utilizing 5G for positioning promises high accuracy, reliability, and cost-efficiency due to shared hardware usage for communication and positioning. Which positioning technique suits 5G-bases positioning best for manufacturing is still an open research question. This paper presents a deep learning approach for 5G-based positioning. The first results of our research work in progress obtained at the research factory ARENA 2036 indicate a positioning accuracy in the centimeter range.
DOI:10.1109/ETFA52439.2022.9921635