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  4. Benchmarking for the indoor localization of autonomous mobile robots in intralogistics
 
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Benchmarking for the indoor localization of autonomous mobile robots in intralogistics

Citation Link: https://doi.org/10.15480/882.9062
Other Titles
Benchmarking für die Indoor-Lokalisierung Autonomer Mobiler Roboter in der Intralogistik
Publikationstyp
Conference Paper
Date Issued
2023-09-26
Sprache
English
Author(s)
Knitt, Markus  
Technische Logistik W-6  
Elgouhary, Yousef 
Schyga, Jakob 
Technische Logistik W-6  
Rose, Hendrik 
Technische Logistik W-6  
Kreutzfeldt, Jochen  orcid-logo
Technische Logistik W-6  
TORE-DOI
10.15480/882.9062
TORE-URI
https://hdl.handle.net/11420/45145
Journal
Logistics journal / Proceedings  
Volume
2023
Article Number
5809
Citation
Logistics Journal : Proceedings 2023: 5809 (2023)
Contribution to Conference
19. Fachkolloquium
Publisher DOI
10.2195/lj_proc_knitt_de_202310_01
Publisher
WGTL, Wissenschaftliche Gesellschaft für Technische Logistik e. V.
This paper introduces a novel approach to benchmarking Indoor Localization Systems (ILS) for mobile robots in warehouse and manufacturing contexts. The study focuses on diverse localization technologies commonly used in mobile robotics and implements transparent and comparable performance metrics, an automated experimental procedure, as well as an intuitive performance visualization approach. Experiments were conducted using a custom-built robot equipped with various sensors, including LiDAR, Ultra-Wideband (UWB), and vision systems. A process for systematically analyzing the impact of environmental factors such as lighting, reflectivity, and obstacles on localization performance is proposed. The results provide insights into system robustness and accuracy under different conditions. The study enables more efficient experimental analysis of sensor fusion and optimization strategies for achieving optimal performance and offers a workflow to efficiently investigate sensor fusion concepts using real data.
Subjects
Benchmarking
Intralogistics
Intralogistik
Localization
Lokalisierung
Robotics
Robotik
DDC Class
620: Engineering
380: Commerce, Communications, Transport
Funding(s)
Automatische Generierung von Modellen für Prädikation, Testen und Monitoring cyber-physischer Systeme  
Publication version
publishedVersion
Lizenz
https://creativecommons.org/licenses/by/4.0/
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