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Volume 12
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Article

Enhanced Unmanned Aerial Vehicle Localization in Dynamic Environments Using Monocular Simultaneous Localization and Mapping and Object Tracking

by
Youssef El Gaouti
1,*,
Fouad Khenfri
2,
Mehdi Mcharek
1 and
Cherif Larouci
1
1
École Supérieure des Techniques Aéronautiques et de Construction Automobile, ESTACA’Lab—Paris-Saclay, F-78180 Montigny-le-Bretonneux, France
2
École Supérieure des Techniques Aéronautiques et de Construction Automobile, ESTACA’Lab—Laval, F-53000 Laval, France
*
Author to whom correspondence should be addressed.
Mathematics 2024, 12(11), 1619; https://doi.org/10.3390/math12111619
Submission received: 23 March 2024 / Revised: 19 April 2024 / Accepted: 16 May 2024 / Published: 22 May 2024
(This article belongs to the Special Issue Advanced Machine Vision with Mathematics)
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Abstract

This work proposes an innovative approach to enhance the localization of unmanned aerial vehicles (UAVs) in dynamic environments. The methodology integrates a sophisticated object-tracking algorithm to augment the established simultaneous localization and mapping (ORB-SLAM) framework, utilizing only a monocular camera setup. Moving objects are detected by harnessing the power of YOLOv4, and a specialized Kalman filter is employed for tracking. The algorithm is integrated into the ORB-SLAM framework to improve UAV pose estimation by correcting the impact of moving elements and effectively removing features connected to dynamic elements from the ORB-SLAM process. Finally, the results obtained are recorded using the TUM RGB-D dataset. The results demonstrate that the proposed algorithm can effectively enhance the accuracy of pose estimation and exhibits high accuracy and robustness in real dynamic scenes.
Keywords: computer vision; UAV localization; object tracking; dynamic environment computer vision; UAV localization; object tracking; dynamic environment

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MDPI and ACS Style

El Gaouti, Y.; Khenfri, F.; Mcharek, M.; Larouci, C. Enhanced Unmanned Aerial Vehicle Localization in Dynamic Environments Using Monocular Simultaneous Localization and Mapping and Object Tracking. Mathematics 2024, 12, 1619. https://doi.org/10.3390/math12111619

AMA Style

El Gaouti Y, Khenfri F, Mcharek M, Larouci C. Enhanced Unmanned Aerial Vehicle Localization in Dynamic Environments Using Monocular Simultaneous Localization and Mapping and Object Tracking. Mathematics. 2024; 12(11):1619. https://doi.org/10.3390/math12111619

Chicago/Turabian Style

El Gaouti, Youssef, Fouad Khenfri, Mehdi Mcharek, and Cherif Larouci. 2024. "Enhanced Unmanned Aerial Vehicle Localization in Dynamic Environments Using Monocular Simultaneous Localization and Mapping and Object Tracking" Mathematics 12, no. 11: 1619. https://doi.org/10.3390/math12111619

APA Style

El Gaouti, Y., Khenfri, F., Mcharek, M., & Larouci, C. (2024). Enhanced Unmanned Aerial Vehicle Localization in Dynamic Environments Using Monocular Simultaneous Localization and Mapping and Object Tracking. Mathematics, 12(11), 1619. https://doi.org/10.3390/math12111619

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