Drone Technology for Efficient Warehouse Product Localization

Assia Belbachir, Antonio Ortiz, Erik Hauge, Ahmed Belbachir, Giusy Bonanno, Emanuele Ciccia, Giorgio Felline

2024

Abstract

This paper presents a novel drone-based strategy for enhancing stock-monitoring systems, specifically focusing on the accurate localization of products within defined areas. Traditional localization techniques, which are often reliant on technologies such as RFID or precision positioning systems, face substantial limitations in terms of accuracy and operational efficiency. To address these issues, we introduce an advanced relative positioning system, uniquely designed to identify and accurately position steel bars relative to each other in an outdoor warehouse environment. The developed approach significantly improves localization precision and speed over conventional methods. Our analysis includes an evaluation of the system’s performance, demonstrating advancements in self-localization capabilities. Results indicate a marked enhancement in the accuracy and efficiency of stock monitoring, showcasing the system’s potential applicability to a diverse range of products and environments.

Paper Citation

in Harvard Style

Belbachir A., Ortiz A., Hauge E., Belbachir A., Bonanno G., Ciccia E. and Felline G. (2024). Drone Technology for Efficient Warehouse Product Localization. In Proceedings of the 21st International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO; ISBN 978-989-758-717-7, SciTePress, pages 357-364. DOI: 10.5220/0012947900003822

in Bibtex Style

@conference{icinco24,
author={Assia Belbachir and Antonio Ortiz and Erik Hauge and Ahmed Belbachir and Giusy Bonanno and Emanuele Ciccia and Giorgio Felline},
title={Drone Technology for Efficient Warehouse Product Localization},
booktitle={Proceedings of the 21st International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO},
year={2024},
pages={357-364},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012947900003822},
isbn={978-989-758-717-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 21st International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO
TI - Drone Technology for Efficient Warehouse Product Localization
SN - 978-989-758-717-7
AU - Belbachir A.
AU - Ortiz A.
AU - Hauge E.
AU - Belbachir A.
AU - Bonanno G.
AU - Ciccia E.
AU - Felline G.
PY - 2024
SP - 357
EP - 364
DO - 10.5220/0012947900003822
PB - SciTePress