Cyber-physischer Zwilling Framework zur Generierung menschlicher Bewegungsdaten in der Intralogistik
DOI:
https://doi.org/10.2195/lj_Proc_avsar_de_202112_01Keywords:
Cyber-physical twin, Cyber-physischer Zwilling, Datengenerierung, HAR (Human Activity Recognition), Menschliche Aktivitätserkennung, Simulation, data generationAbstract
Recognizing human movements, interpreting them and assigning relevant activities for the analysis of manual processes are central challenges of Human Activity Recognition (HAR). These challenges are preceded by training a classifier with data. The creation of these training data sets, consisting of data acquisition, annotation and revision of time series, requires immense effort. For this reason, HAR methods are mainly tested on simple everyday situations. A new form of data set creation is necessary to develop HAR methods for complex environments such as intralogistics. This contribution proposes a framework to reduce the effort of data acquisition by using cyber-physical twins.Published
2021-12-13
How to Cite
Avsar, H., Niemann, F., Reining, C., & ten Hompel, M. (2021). Cyber-physischer Zwilling Framework zur Generierung menschlicher Bewegungsdaten in der Intralogistik. Logistics Journal: Proceedings, (17). https://doi.org/10.2195/lj_Proc_avsar_de_202112_01
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