Exploring a multi-sensor picking process in the future warehouse


Diete, Alexander ; Sztyler, Timo ; Weiland, Lydia ; Stuckenschmidt, Heiner



DOI: https://doi.org/10.1145/2968219.2968270
URL: http://dl.acm.org/citation.cfm?doid=2968219.296827...
Additional URL: http://publications.wim.uni-mannheim.de/informatik...
Document Type: Conference or workshop publication
Year of publication: 2016
Book title: UbiComp/ISWC'16 Adjunct : Adjunct proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2016 ACM International Symposium on Wearable Computers
Page range: 1755-1758
Conference title: UbiComp/ISWC 2016 Adjunct
Location of the conference venue: Heidelberg, Germany
Date of the conference: 12.-16.9.2016
Publisher: Lukowicz, Paul
Place of publication: New York, NY
Publishing house: ACM
ISBN: 978-1-4503-4462-3
Publication language: English
Institution: School of Business Informatics and Mathematics > Practical Computer Science II: Artificial Intelligence (Stuckenschmidt 2009-)
Subject: 004 Computer science, internet
Abstract: Recognizing, validating, and optimizing activities of workers in logistics is increasingly aided by smart devices like glasses, gloves, and sensor enhanced wristbands. We present a system that augments picking processes with smart glasses and wristband that incorporates different types of sensors including ultrasonic, pressure, and inertial. We focus on low barriers for the adoption as well as the combination of video and inertial sensors. For that purpose, we create a new semi-supervised dataset to evaluate the feasibility of our approach. The system recognizes and monitors activities like grabbing and releasing of objects that are essential for order picking tasks.




Dieser Eintrag ist Teil der Universitätsbibliographie.




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