QR-Code Based Visual Servoing and Target Recognition to Improve Payload Release Accuracy in Air Delivery Missions using Fully Autonomous Quad-Copter UAV
DOI:
https://doi.org/10.15294/rji.v3i1.4430Keywords:
Computer Vision (CV), Image Based Visual Servoing (IBVS), Delivery DronesAbstract
Abstract. Unmanned Aerial Vehicles (UAVs) are increasingly utilized for package delivery due to their efficiency and automation capabilities. UAVs can execute autonomous flight missions using Global Positioning System (GPS)-based navigation. However, challenges arise in the final stage of delivery, known as the last-mile delivery problem. The limitations of GPS-based navigation, the absence of recipient authentication, and shifting drop-off points create reliability and safety concerns. External factors such as varied environmental topography further contribute to delivery inaccuracies, highlighting the need for a more precise approach.
Purpose: Many studies have explored UAV navigation and delivery systems, but challenges in last-mile delivery remain unresolved. This research introduces an improved UAV delivery system using computer vision (CV) and image-based visual servoing (IBVS) with QR Codes as location markers. The aim is to enhance UAV navigation accuracy and recipient verification, ensuring more reliable package deliveries.
Methods/Study design/approach: The study implements a CV-based navigation system where QR Codes serve as landing markers for UAVs. Image processing is conducted using a companion computer linked to the UAV's flight control system. The IBVS method enables UAVs to adjust their position in real-time, minimizing GPS errors. Recipient verification is performed through QR Code scanning before releasing the package. The system is tested through computer simulations and real flight experiments to assess accuracy and effectiveness.
Result/Findings: Experimental results demonstrate that UAVs equipped with the IBVS method can successfully complete package delivery missions with improved accuracy. GPS errors are corrected by aligning the UAV's position with QR Code markers, and recipient authentication is verified before package release. Real-flight tests confirm that this approach significantly enhances UAV delivery reliability compared to conventional GPS-based navigation.
Novelty/Originality/Value: This research presents a novel integration of computer vision and UAV navigation for addressing last-mile delivery challenges. By leveraging IBVS and QR Code-based authentication, UAVs can perform fully autonomous, precise, and secure package deliveries. This method offers a viable solution to improve UAV-based logistics, reducing delivery errors and enhancing operational safety.