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Concept of automated load detection for de-palletizing using depth images and RFID data

: Prasse, Christian; Skibinski, Sebastian; Weichert, Frank; Stenzel, Jonas; Müller, Heinrich; Ten Hompel, Michael

Postprint urn:nbn:de:0011-n-1987507 (812 KByte PDF)
MD5 Fingerprint: 0de277060f2c261430dbab3678b15f42
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Created on: 20.3.2012

Institute of Electrical and Electronics Engineers -IEEE-; Institute of Electrical and Electronics Engineers -IEEE-, Malaysia Section:
IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2011. Proceedings : Penang, Malaysia, 25 -27 November 2011
New York, NY: IEEE, 2011
ISBN: 978-1-4577-1641-6
ISBN: 978-1-4577-1640-9
ISBN: 1-4577-1640-2
ISBN: 978-1-4577-1642-3
International Conference on Control System, Computing and Engineering (ICCSCE) <2011, Penang>
Conference Paper, Electronic Publication
Fraunhofer IML ()
computer vision; de-palletizing; contour check; semantic compression; data storage management; Radiofrequente Identifikation/Radiofrequenz-Identifikation (RFID); Internet der Dinge; internet of things; PMD camera; 3D imaging

In this paper, we present a novel concept for the detection of loading positions of parcels or bins on a pallet to enable automated order picking using knowledge about the packing pattern model. The approach comprises (1) a new combination of pattern model data and PMD-camera-generated point clouds and (2) a novel concept of RFID data management using a Binary data on Tag / Schema on Net and semantic coding approach. The latter enables the use of additional services like storing of loading positions on auto-id devices (RFID-tags) in a wider concept of the Internet of Things, while the former presents an alternative approach in the context of contour check and position detection of unit loads for automated de-palletizing.