Drone Position Tracking System based on Object Detection and ArUco Marker for Autonomous Navigation Applications

Hendra Bagus Arie Wicaksana; Ronny Mardiyanto; Astria Nur Irfansyah

doi:10.1109/ISITIA63062.2024.10668046

Drone Position Tracking System based on Object Detection and ArUco Marker for Autonomous Navigation Applications

Hendra Bagus Arie Wicaksana^*
, Ronny Mardiyanto
, Astria Nur Irfansyah

^*Corresponding author for this work

Department of Electrical Engineering
Institut Teknologi Sepuluh Nopember

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

7 Citations (Scopus)

Abstract

In an autonomous navigation system, the drone needs to know its position continuously to navigate properly to the destination. In indoor environments, localization using GPS (Global Positioning System) often results in poor accuracy due to various factors such as building structures that affect GPS signal reception. In this paper, we propose an indoor drone position-tracking system based on visual sensing from the drone camera. Two types of artificial visual markers such as ArUco markers and 3D object markers are used as references to determine the relative position of the drone. The estimated drone position is obtained by computing the translation vectors of the artificial visual markers in the vision of the drone camera. The estimation results with the combination of object detection and ArUco markers show an average accuracy of 10 cm with a range of 0.1 - 8 meters.

Original language	English
Title of host publication	2024 International Seminar on Intelligent Technology and Its Applications
Subtitle of host publication	Collaborative Innovation: A Bridging from Academia to Industry towards Sustainable Strategic Partnership, ISITIA 2024 - Proceeding
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	131-135
Number of pages	5
Edition	2024
ISBN (Electronic)	9798350378573
DOIs	https://doi.org/10.1109/ISITIA63062.2024.10668046
Publication status	Published - 2024
Event	25th International Seminar on Intelligent Technology and Its Applications, ISITIA 2024 - Hybrid, Mataram, Indonesia Duration: 10 Jul 2024 → 12 Jul 2024

Conference

Conference	25th International Seminar on Intelligent Technology and Its Applications, ISITIA 2024
Country/Territory	Indonesia
City	Hybrid, Mataram
Period	10/07/24 → 12/07/24

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

ArUco marker
autonomous navigation
camera
drones
object
position tracking

Access to Document

10.1109/ISITIA63062.2024.10668046

Cite this

Wicaksana, H. B. A., Mardiyanto, R., & Irfansyah, A. N. (2024). Drone Position Tracking System based on Object Detection and ArUco Marker for Autonomous Navigation Applications. In 2024 International Seminar on Intelligent Technology and Its Applications: Collaborative Innovation: A Bridging from Academia to Industry towards Sustainable Strategic Partnership, ISITIA 2024 - Proceeding (2024 ed., pp. 131-135). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISITIA63062.2024.10668046

Wicaksana, Hendra Bagus Arie ; Mardiyanto, Ronny ; Irfansyah, Astria Nur. / Drone Position Tracking System based on Object Detection and ArUco Marker for Autonomous Navigation Applications. 2024 International Seminar on Intelligent Technology and Its Applications: Collaborative Innovation: A Bridging from Academia to Industry towards Sustainable Strategic Partnership, ISITIA 2024 - Proceeding. 2024. ed. Institute of Electrical and Electronics Engineers Inc., 2024. pp. 131-135

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abstract = "In an autonomous navigation system, the drone needs to know its position continuously to navigate properly to the destination. In indoor environments, localization using GPS (Global Positioning System) often results in poor accuracy due to various factors such as building structures that affect GPS signal reception. In this paper, we propose an indoor drone position-tracking system based on visual sensing from the drone camera. Two types of artificial visual markers such as ArUco markers and 3D object markers are used as references to determine the relative position of the drone. The estimated drone position is obtained by computing the translation vectors of the artificial visual markers in the vision of the drone camera. The estimation results with the combination of object detection and ArUco markers show an average accuracy of 10 cm with a range of 0.1 - 8 meters.",

keywords = "ArUco marker, autonomous navigation, camera, drones, object, position tracking",

author = "Wicaksana, \{Hendra Bagus Arie\} and Ronny Mardiyanto and Irfansyah, \{Astria Nur\}",

note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 25th International Seminar on Intelligent Technology and Its Applications, ISITIA 2024 ; Conference date: 10-07-2024 Through 12-07-2024",

year = "2024",

doi = "10.1109/ISITIA63062.2024.10668046",

language = "English",

pages = "131--135",

booktitle = "2024 International Seminar on Intelligent Technology and Its Applications",

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Wicaksana, HBA, Mardiyanto, R & Irfansyah, AN 2024, Drone Position Tracking System based on Object Detection and ArUco Marker for Autonomous Navigation Applications. in 2024 International Seminar on Intelligent Technology and Its Applications: Collaborative Innovation: A Bridging from Academia to Industry towards Sustainable Strategic Partnership, ISITIA 2024 - Proceeding. 2024 edn, Institute of Electrical and Electronics Engineers Inc., pp. 131-135, 25th International Seminar on Intelligent Technology and Its Applications, ISITIA 2024, Hybrid, Mataram, Indonesia, 10/07/24. https://doi.org/10.1109/ISITIA63062.2024.10668046

Drone Position Tracking System based on Object Detection and ArUco Marker for Autonomous Navigation Applications. / Wicaksana, Hendra Bagus Arie; Mardiyanto, Ronny ; Irfansyah, Astria Nur.
2024 International Seminar on Intelligent Technology and Its Applications: Collaborative Innovation: A Bridging from Academia to Industry towards Sustainable Strategic Partnership, ISITIA 2024 - Proceeding. 2024. ed. Institute of Electrical and Electronics Engineers Inc., 2024. p. 131-135.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Drone Position Tracking System based on Object Detection and ArUco Marker for Autonomous Navigation Applications

AU - Wicaksana, Hendra Bagus Arie

AU - Mardiyanto, Ronny

AU - Irfansyah, Astria Nur

PY - 2024

Y1 - 2024

N2 - In an autonomous navigation system, the drone needs to know its position continuously to navigate properly to the destination. In indoor environments, localization using GPS (Global Positioning System) often results in poor accuracy due to various factors such as building structures that affect GPS signal reception. In this paper, we propose an indoor drone position-tracking system based on visual sensing from the drone camera. Two types of artificial visual markers such as ArUco markers and 3D object markers are used as references to determine the relative position of the drone. The estimated drone position is obtained by computing the translation vectors of the artificial visual markers in the vision of the drone camera. The estimation results with the combination of object detection and ArUco markers show an average accuracy of 10 cm with a range of 0.1 - 8 meters.

AB - In an autonomous navigation system, the drone needs to know its position continuously to navigate properly to the destination. In indoor environments, localization using GPS (Global Positioning System) often results in poor accuracy due to various factors such as building structures that affect GPS signal reception. In this paper, we propose an indoor drone position-tracking system based on visual sensing from the drone camera. Two types of artificial visual markers such as ArUco markers and 3D object markers are used as references to determine the relative position of the drone. The estimated drone position is obtained by computing the translation vectors of the artificial visual markers in the vision of the drone camera. The estimation results with the combination of object detection and ArUco markers show an average accuracy of 10 cm with a range of 0.1 - 8 meters.

KW - ArUco marker

KW - autonomous navigation

KW - camera

KW - drones

KW - object

KW - position tracking

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U2 - 10.1109/ISITIA63062.2024.10668046

DO - 10.1109/ISITIA63062.2024.10668046

M3 - Conference contribution

AN - SCOPUS:85208430268

SP - 131

EP - 135

BT - 2024 International Seminar on Intelligent Technology and Its Applications

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 25th International Seminar on Intelligent Technology and Its Applications, ISITIA 2024

Y2 - 10 July 2024 through 12 July 2024

ER -

Wicaksana HBA, Mardiyanto R , Irfansyah AN. Drone Position Tracking System based on Object Detection and ArUco Marker for Autonomous Navigation Applications. In 2024 International Seminar on Intelligent Technology and Its Applications: Collaborative Innovation: A Bridging from Academia to Industry towards Sustainable Strategic Partnership, ISITIA 2024 - Proceeding. 2024 ed. Institute of Electrical and Electronics Engineers Inc. 2024. p. 131-135 doi: 10.1109/ISITIA63062.2024.10668046

Drone Position Tracking System based on Object Detection and ArUco Marker for Autonomous Navigation Applications

Abstract

Conference

UN SDGs

Keywords

Access to Document

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