Vertical trajectory analysis using QR code detection for drone delivery application

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1 Citation (Scopus)


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’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.

Original languageEnglish
Title of host publicationSensing technology
Subtitle of host publicationproceedings of ICST'15
EditorsNagender Kumar Suryadevara, Boby George, Krishanthi P. Jayasundera, Subhas Chandra Mukhopadhyay
Place of PublicationCham
PublisherSpringer, Springer Nature
Number of pages8
ISBN (Electronic)9783031298714
ISBN (Print)9783031298707, 9783031298738
Publication statusPublished - 2023
Event15th International Conference on Sensing Technology, ICST 2022 - Sydney, Australia
Duration: 5 Dec 20227 Dec 2022

Publication series

NameLecture Notes in Electrical Engineering
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119


Conference15th International Conference on Sensing Technology, ICST 2022


  • Drone sensing
  • Trajectory scan
  • Path planning
  • Navigation
  • QR code
  • Drone delivery


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