This chapter presents an autonomous navigation system based on computer vision for unmanned aerial vehicles (UAVs). The emerging area of autonomous UAV has shown rapid development in the field of structural health monitoring (SHM) for the collection of important structural data from civil infrastructure. Much of previous research has been focused on the use of magnetic compass sensor-based methods for control and localization of UAV in GPS-denied environments. However, these methods are vulnerable to magnetic interference of the surrounding environment and result in poor control of UAV with dangerous levels of path deviations. Therefore, this chapter suggests the use of unique small fiducial markers that are unsusceptible to magnetic interference and can be permanently attached to walls or ceilings of structures to enable robust autonomous flight of UAVs. A pseudo markers map is created where the location of each marker is stored in a marker’s library. The markers are detected by the UAV during the flight and the prebuilt library information is used to localize UAV’s position in the whole structure. It has been shown through various experiments that the use of computer vision-based technique can significantly improve the control of UAV in challenging indoor and outdoor GPS-denied environments. This marker-based localization method is a low-cost, flexible, and practical solution to realize true autonomous UAVs in civil structures such as bridges, parkade, and buildings.


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    Titel :

    Fiducial Marker–Based Localization of Autonomous UAV for Structural Health Monitoring


    Weitere Titelangaben:

    Conf.Proceedings of Society


    Beteiligte:
    Walber, Chad (Herausgeber:in) / Stefanski, Matthew (Herausgeber:in) / Seidlitz, Stephen (Herausgeber:in) / Waqas, Ali (Autor:in) / Cha, Young-Jin (Autor:in)

    Kongress:

    Society for Experimental Mechanics Annual Conference and Exposition ; 2023 ; Orlando, FL, USA June 05, 2023 - June 08, 2023



    Erscheinungsdatum :

    2023-11-22


    Format / Umfang :

    7 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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