计算机科学
可靠性(半导体)
工厂(面向对象编程)
定位系统
定位技术
领域(数学)
深度学习
实时计算
嵌入式系统
制造工程
系统工程
人工智能
工程类
结构工程
物理
节点(物理)
功率(物理)
程序设计语言
纯数学
量子力学
数学
作者
Hannes Vietz,Andreas Löcklin,Hamza Ben Haj Ammar,Michael Weyrich
标识
DOI:10.1109/etfa52439.2022.9921635
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 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.
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