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

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  • Youssef El Gaouti

    (École Supérieure des Techniques Aéronautiques et de Construction Automobile, ESTACA’Lab—Paris-Saclay, F-78180 Montigny-le-Bretonneux, France)

  • Fouad Khenfri

    (École Supérieure des Techniques Aéronautiques et de Construction Automobile, ESTACA’Lab—Laval, F-53000 Laval, France)

  • Mehdi Mcharek

    (École Supérieure des Techniques Aéronautiques et de Construction Automobile, ESTACA’Lab—Paris-Saclay, F-78180 Montigny-le-Bretonneux, France)

  • Cherif Larouci

    (École Supérieure des Techniques Aéronautiques et de Construction Automobile, ESTACA’Lab—Paris-Saclay, F-78180 Montigny-le-Bretonneux, France)

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.

Suggested Citation

  • Youssef El Gaouti & Fouad Khenfri & Mehdi Mcharek & Cherif Larouci, 2024. "Enhanced Unmanned Aerial Vehicle Localization in Dynamic Environments Using Monocular Simultaneous Localization and Mapping and Object Tracking," Mathematics, MDPI, vol. 12(11), pages 1-17, May.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:11:p:1619-:d:1399105
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    References listed on IDEAS

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    1. Mohamed, Nader & Al-Jaroodi, Jameela & Jawhar, Imad & Idries, Ahmed & Mohammed, Farhan, 2020. "Unmanned aerial vehicles applications in future smart cities," Technological Forecasting and Social Change, Elsevier, vol. 153(C).
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