In this paper, we present a novel approach to real-time collision avoidance and path planning for unmanned aerial vehicles (UAVs) using basic camera inputs. Our system predicts the future trajectories of nearby flying objects and computes a feasible path to avoid collisions while maintaining progress toward a target destination. Unlike traditional radar- based methods, our solution requires only two parameters from the visual feed—bearing and pixel size—allowing for lightweight, real-time obstacle detection and avoidance. This approach benefits UAVs operating in shared airspaces with manned aircraft, where rapid, autonomous decision-making is essential for safety. Preliminary results show that our system can efficiently compute avoidance maneuvers and plan routes in real-time, even in dynamic environments.


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    Titel :

    Real-Time B-Spline Path Planning for Vision-Based Collision Avoidance


    Beteiligte:
    Liu, Jen-Jui (Autor:in) / Evans, Curtis P. (Autor:in) / Beard, Randal W. (Autor:in)


    Erscheinungsdatum :

    28.04.2025


    Format / Umfang :

    6092036 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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