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.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

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


    Contributors:


    Publication date :

    2025-04-28


    Size :

    6092036 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




    DYNAMIC DIFFUSION MAPS-BASED PATH PLANNING FOR REAL-TIME COLLISION AVOIDANCE OF MOBILE ROBOTS

    Hong, Sanghyun / Lu, Jianbo / Filev, Dimitar P. | British Library Conference Proceedings | 2018



    Sampling-Based Path Planning for UAV Collision Avoidance

    Lin, Yucong / Saripalli, Srikanth | IEEE | 2017