@inproceedings{83985d79dac2485bbd6022fdf042f8d7,
title = "Vertical trajectory analysis using QR code detection for drone delivery application",
abstract = "The advent of the internet and fast-processing computers have enabled drones to fly autonomously for a variety of applications. Most of the research focuses on horizontal trajectory planning and mapping for autonomous navigation. In this study, we propose a method to address the urban last-mile drone delivery problem. The paper suggests an autonomous vertical trajectory scanning method that could be used to analyse the appropriate level and unit in an apartment building. The QR code embedded with the level and unit number information is used as a marker that can be detected by the drone{\textquoteright}s visual recognition framework. The suggested method aims to conduct real-time detection of the apartment at every level using consistent trajectory tracking. The experiments are tested indoors for 3 levels and 10 unique QR codes, comparing with 4 different trajectory planning patterns to analyse the most efficient trajectory. The parallel path is observed to be the most optimum for maximum area coverage and the quickest arrival to the desired destination.",
keywords = "Drone sensing, Trajectory scan, Path planning, Navigation, QR code, Drone delivery",
author = "Avishkar Seth and Alice James and Endrowednes Kuantama and Subhas Mukhopadhyay and Richard Han",
year = "2023",
doi = "10.1007/978-3-031-29871-4_48",
language = "English",
isbn = "9783031298707",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer, Springer Nature",
pages = "476--483",
editor = "Suryadevara, {Nagender Kumar} and Boby George and Jayasundera, {Krishanthi P.} and Mukhopadhyay, {Subhas Chandra}",
booktitle = "Sensing technology",
address = "United States",
note = "15th International Conference on Sensing Technology, ICST 2022 ; Conference date: 05-12-2022 Through 07-12-2022",
}