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

被引:3
作者
Vietz, Hannes [1 ]
Loecklin, Andreas [1 ]
Ammar, Hamza Ben Haj [1 ]
Weyrich, Michael [1 ]
机构
[1] Univ Stuttgart, Inst Ind Automat & Software Engn, Stuttgart, Germany
来源
2022 IEEE 27TH INTERNATIONAL CONFERENCE ON EMERGING TECHNOLOGIES AND FACTORY AUTOMATION (ETFA) | 2022年
关键词
5G; indoor positioning; mobile robots; AGV; intralogistics; deep learning; artificial intelligence; localization;
D O I
10.1109/ETFA52439.2022.9921635
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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 costefficiency 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.
引用
收藏
页数:4
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