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TrackSort: Predictive Tracking for Sorting Uncooperative Bulk Materials

Pfaff, Florian ORCID iD icon 1; Baum, Marcus 1; Noack, Benjamin 1; Hanebeck, Uwe D. 1; Gruna, Robin; Längle, Thomas; Beyerer, Jürgen
1 Institut für Anthropomatik und Robotik (IAR), Karlsruher Institut für Technologie (KIT)

Abstract:

Optical belt sorters are a versatile, state-of-the-art technology to sort bulk materials that are hard to sort based on only nonvisual properties. In this paper, we propose an extension to current optical belt sorters that involves replacing the line camera with an area camera to observe a wider field of view, allowing us to observe each particle over multiple time steps. By performing multitarget tracking, we are able to improve the prediction of each particle‘s movement and thus enhance the performance of the utilized separation mechanism. We show that our approach will allow belt sorters to handle new classes of bulk materials while improving cost efficiency. Furthermore, we lay out additional extensions that are made possible by our new paradigm


Postprint §
DOI: 10.5445/IR/1000051035
Veröffentlicht am 15.06.2020
Originalveröffentlichung
DOI: 10.1109/MFI.2015.7295737
Scopus
Zitationen: 19
Dimensions
Zitationen: 17
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Anthropomatik und Robotik (IAR)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2015
Sprache Englisch
Identifikator ISBN: 978-1-4799-7772-7
KITopen-ID: 1000051035
Erschienen in Proceedings of the 2015 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2015), 14-16 Sept. 2015, San Diego, CA, USA
Verlag Institute of Electrical and Electronics Engineers (IEEE)
Seiten 7-12
Nachgewiesen in Dimensions
Scopus
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