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• W4372279241 endingPage "300" @default.
• W4372279241 startingPage "300" @default.
• W4372279241 abstract "Delivery drones typically perform delivery by suspending the parcel vertically or landing the drone to drop off the package. However, because of the constrained landing area and the requirement for precise navigation, delivering items to customers who reside in multi-story apartment complexes poses a unique challenge. This research paper proposes a novel drone delivery system for multi-story apartment buildings with balconies that employ two methods for Vertical Grid Screening (VGS), i.e., Grid Screening (GS) and Square Screening (SS), to detect unique markers to identify the precise balcony that needs to receive the product. The developed drone has a frame size of 295 mm and is equipped with a stereo camera and a ranging sensor. The research paper also explores the scanning and trajectory methods required for autonomous flight to accurately approach the marker location. The proposed machine learning system is trained on a YOLOv5 model for image recognition of the marker, and four different models and batch sizes are compared. The 32-batch size with a 960 × 1280 resolution model provides an average of 0.97 confidence for an extended range. This system is tested outdoors and shows an accuracy of 95% for a planned trajectory with 398 ms detection time as a solution for last-mile delivery in urban areas." @default.
• W4372279241 created "2023-05-07" @default.
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• W4372279241 date "2023-05-04" @default.
• W4372279241 modified "2023-10-01" @default.
• W4372279241 title "Drone High-Rise Aerial Delivery with Vertical Grid Screening" @default.
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• W4372279241 doi "https://doi.org/10.3390/drones7050300" @default.
• W4372279241 hasPublicationYear "2023" @default.
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