Analysis of the Operation of Industrial Trucks based on Position Data
Schyga
Jakob
Rose
Hendrik
Hinckeldeyn
Johannes
Kreutzfeldt
Jochen
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.
Analysekonzept
Analysis Concept
Bewegungserkennung
Flurförderzeug
Indoor-Localization
Indoor-Lokalisierung
Industrial Truck
Movement detection
Warehouse
Warenlager
620
periodical
academic journal
Logistics Journal : Proceedings
2021
17
2021
2192-9084
urn:nbn:de:0009-14-54415
10.2195/lj_Proc_schyga _en_202112_01
http://nbn-resolving.de/urn:nbn:de:0009-14-54415
schyga2021