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Realization and validation of a collaborative automated picking system
Citation Link: https://doi.org/10.15480/882.3131
Publikationstyp
Conference Paper
Date Issued
2020-09-23
Sprache
English
Author(s)
Herausgeber*innen
TORE-DOI
TORE-URI
First published in
Number in series
29
Start Page
521
End Page
558
Citation
Hamburg International Conference of Logistics (HICL) 29: 521-558 (2020)
Contribution to Conference
Publisher
epubli
Purpose: A picking system is presented ensuring order fulfilment and enabling trans-formation from manual to automated picking using a continuous learning process. It is based on Machine Learning for object detection and realized by a human-robot collaboration to meet requirements for flexibility and adaptability. A demonstrator is implemented to show cooperation and to evaluate the learning process. Methodology: The collaborative process, system architecture, and an approach for evaluation and workload balancing for order fulfilment and learning of robots during picking have already been introduced. However, a practical application is still miss-ing. A demonstrator is implemented using an agent-based architecture (JADEX) and a physical robot (UR5e) with a camera for object detection and first empirical data are evaluated. Findings: Single components of the demonstrator are already developed, but a pending task is to implement their interaction to analyze overall system perfor-mance. This work focuses on human-robot-interaction (Emergency Call), automated generation of images extended by feedback information, and training of algorithms for object detection. Requirements of human-machine interface, technical evalua-tion of image recording, and effort of algorithm training are discussed. Originality: Many approaches for automated picking assume a static range of ob-jects. However, this approach considers a changing range as well as a concept for transformation of manual to automated picking enabled by human-robot coopera-tion and automated image recording while enabling reliable order fulfilment.
Subjects
Logistics
Industry 4.0
Digitalization
Innovation
Supply Chain Management
Artificial Intelligence
Data Science
DDC Class
330: Wirtschaft
380: Handel, Kommunikation, Verkehr
Publication version
publishedVersion
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Rieder and Verbeet (2020) - Realization and validation of a collaborative automated picking system.pdf
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