Outdoor Warehouse Management: UAS-Driven Precision Tracking of Stacked Steel Bars
Assia Belbachir, Antonio M. Ortiz, Erik T. Hauge, Ahmed Nabil Belbachir, Giusy Bonanno, Emanuele Ciccia, Giorgio Felline
TL;DR
This paper introduces a drone-based system for tracking stacked steel bars in outdoor warehouses using QR codes and relative positioning, offering a scalable solution without relying on GPS or RFID.
Contribution
The key novelty is an infrastructure-free method for product positioning using relative spatial relationships and trust-ability scoring.
Findings
The system achieves over 94% positioning accuracy in indoor settings.
It maintains 80% accuracy in outdoor environments despite occlusion and varying illumination.
The method was validated in real-world industrial scenarios.
Abstract
Accurately identifying the positions of products in outdoor environments-such as warehouses or industrial yards-presents unique challenges due to variable lighting, weather conditions, and the lack of fixed infrastructure. This work presents a vision-based drone system for product localization using QR code detection and relative positioning. The proposed system enables a UAV to autonomously scan an area, extract QR codes from captured video frames, and compute the spatial relationships between products using a trust-ability graph. Unlike traditional GPS- or RFID-based methods, our approach does not rely on external infrastructure, making it scalable and adaptable for outdoor and semi-structured environments. We demonstrate that the proposed algorithm achieves over 94% positioning accuracy in indoor settings and 80% in outdoor environments, even under occlusion and varying illumination.…
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Taxonomy
TopicsRobotics and Sensor-Based Localization · Indoor and Outdoor Localization Technologies · Smart Parking Systems Research