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A Path Planning Model for Stock Inventory Using a Drone

Author

Listed:
  • László Radácsi

    (Faculty of Finance and Accountancy, Budapest Business School, 1149 Budapest, Hungary)

  • Miklós Gubán

    (Faculty of Finance and Accountancy, Budapest Business School, 1149 Budapest, Hungary)

  • László Szabó

    (Faculty of Finance and Accountancy, Budapest Business School, 1149 Budapest, Hungary)

  • József Udvaros

    (Faculty of Finance and Accountancy, Budapest Business School, 1149 Budapest, Hungary)

Abstract

In this study, a model and solution are shown for controlling the inventory of a logistics warehouse in which neither satellite positioning nor IoT solutions can be used. Following a review of the literature on path planning, a model is put forward using a drone that can be moved in all directions and is suitable for imaging and transmission. The proposed model involves three steps. In the first step, a traversal path definition provides an optimal solution, which is pre-processing. This is in line with the structure and capabilities of the warehouse. In the second step, the pre-processed path determines the real-time movement of the drone during processing, including camera movements and image capture. The third step is post-processing, i.e., the processing of images for QR code identification, the interpretation of the QR code, and the examination of matches and discrepancies for inventory control. A key benefit for the users of this model is that the result can be achieved without any external orientation tools, relying solely on its own movement and the organization of a pre-planned route. The proposed model can be effective not only for inventory control, but also for exploring the structure of a warehouse shelving system and determining empty cells.

Suggested Citation

  • László Radácsi & Miklós Gubán & László Szabó & József Udvaros, 2022. "A Path Planning Model for Stock Inventory Using a Drone," Mathematics, MDPI, vol. 10(16), pages 1-19, August.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:16:p:2899-:d:886897
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    References listed on IDEAS

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    1. David Pisinger & Stefan Ropke, 2019. "Large Neighborhood Search," International Series in Operations Research & Management Science, in: Michel Gendreau & Jean-Yves Potvin (ed.), Handbook of Metaheuristics, edition 3, chapter 0, pages 99-127, Springer.
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    Cited by:

    1. Chuanyue Wang & Lei Zhang & Yifan Gao & Xiaoyuan Zheng & Qianling Wang, 2023. "A Cooperative Game Hybrid Optimization Algorithm Applied to UAV Inspection Path Planning in Urban Pipe Corridors," Mathematics, MDPI, vol. 11(16), pages 1-18, August.
    2. Zsolt Tibor Kosztyán & Zoltán Kovács, 2023. "Preface to the Special Issue on “Mathematical Methods and Operation Research in Logistics, Project Planning, and Scheduling”," Mathematics, MDPI, vol. 11(1), pages 1-3, January.

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