Indoor positioning systems (IPSs) can make an important contribution to the analysis and optimization of internal transport processes. The overall aim of this work is to examine how position data can be used to analyze the operation of industrial trucks in warehouses. This is achieved by presenting a concept for the analysis of industrial truck operations based merely on position data. The concept consists of a signal processing scheme to derive kinematic data and three analysis methods – Monitoring, Area analysis, and Motion analysis. Schemes for the signal processing and detection of motion events were developed and implemented as part of the TrOpLocerApp (Truck Operation Localization Analyzer-Application) for recording, displaying, and processing position data, according to the proposed system concept. The TrOpLocer-App source code is published under an open-source license and is publicly available on GitLab [RS21]. Different filter algorithms were examined, as part of the signal processing scheme, from which the low pass Butterworth filter has shown the best results in static experiments. Validation of the motion detection scheme shows good detection quality for distinct events in a realistic movement experiment.

Subjects

Analysis Concept

Indoor-Localization

Warehouse

Industrial Truck

Movement Detection

Analysekonzept

Indoor-Lokalisierung

Warenlager

Flurförderzeug

Bewegungserkennung

DDC Class

380: Handel, Kommunikation, Verkehr

Publication version

publishedVersion

Lizenz

https://www.hbz-nrw.de/produkte/open-access/lizenzen/dppl/fdppl/f-DPPL_v1_de_11-2004

Name

schyga_en_2021.pdf

Size

1.32 MB

Format

Adobe PDF

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Analysis of the operation of industrial trucks based on position data