This study presents a fire edge detection and tracking methodology for an autonomous small UAS (sUAS). The sUAS, onboard sensors, and wildfire are simulated to evaluate the methodology. A visible light (Vis) camera and an infrared (IR) camera are simulated onboard the sUAS to identify burnt, burning, and unburnt areas on a static wildfire bitmap. After differentiating between these areas, a form of nonlinear guidance law (NLGL) is used to generate virtual target points (VTP) that guide the sUAS so that the fire edge is kept within the camera FOV. The VTP are passed to the sUAS flight management system (FMS) in the form of waypoints. The approach was tested in simulation and demonstrated tracking curved, sharp, and linear fire edge shapes at different altitudes. Higher altitude tracking proved to demand the least control effort without sacrificing continuous tracking.


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    Titel :

    A Simulated Fire Edge Vis-IR Detection and Tracking Approach for Autonomous sUAS in STEReO


    Beteiligte:
    Joshua Baculi (Autor:in) / Corey Ippolito (Autor:in)

    Kongress:

    AIAA Science and Technology Forum and Exposition (2021 AIAA SciTech Forum) ; 2021 ; Virtual, US


    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Keine Angabe


    Sprache :

    Englisch