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Robot-human-learning for robotic picking processes

In: Artificial Intelligence and Digital Transformation in Supply Chain Management: Innovative Approaches for Supply Chains. Proceedings of the Hamburg International Conference of Logistics (HICL), Vol. 27

Author

Listed:
  • Rieder, Mathias
  • Verbeet, Richard

Abstract

Purpose: This research paper aims to create an environment which enables robots to learn from humans by algorithms of Computer Vision and Machine Learning for object detection and gripping. The proposed concept transforms manual picking to highly automated picking performed by robots. Methodology: After defining requirements for a robotic picking system, a process model is proposed. This model defines how to extend traditional manual picking and which human-robot-interfaces are necessary to enable learning from humans to improve the performance of robots' object detection and gripping. Findings: The proposed concept needs a pool of images to train an initial setup of a convolutional neural network by the YOLO-Algorithm. Therefore, a station with two cameras and a flexible positioning system for image creation is presented by which the necessary number of images can be generated with little effort. Originality: A digital representation of an object is created based on the generated images of this station. The original idea is a feedback loop including human workers after a not successful object detection or gripping which enables robots in service to extend their ability to recognize and pick objects.

Suggested Citation

  • Rieder, Mathias & Verbeet, Richard, 2019. "Robot-human-learning for robotic picking processes," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Blecker, Thorsten & Ringle, Christian M. (ed.), Artificial Intelligence and Digital Transformation in Supply Chain Management: Innovative Approaches for Supply Chains. Proceedings of the Hamburg Int, volume 27, pages 87-114, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    • Handle: RePEc:zbw:hiclch:209370
    DOI: 10.15480/882.2466
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    Citations

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    Cited by:

    1. Feldt, Julia & Kontny, Henning & Niemietz, Frank, 2020. "How disruptive start-ups change the world of warehouse logistics," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Blecker, Thorsten & Ringle, Christian M. (ed.), Data Science and Innovation in Supply Chain Management: How Data Transforms the Value Chain. Proceedings of the Hamburg International Conference of Lo, volume 29, pages 3-24, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    2. Rieder, Mathias & Verbeet, Richard, 2020. "Realization and validation of a collaborative automated picking system," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Blecker, Thorsten & Ringle, Christian M. (ed.), Data Science and Innovation in Supply Chain Management: How Data Transforms the Value Chain. Proceedings of the Hamburg International Conference of Lo, volume 29, pages 521-558, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.

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