According to the UAV autonomous aerial refueling based on GPS/Machine Vision integration, the restrictions on the sensors during docking are analyzed. An adaptive Federal Kalman Filter (AFKF) is proposed, which is based on extended Kalman filter arithmetic, after modeling the sensors measurement models. Reference trajectory of docking is planed using cubic interpolators and docking control laws are designed with LQR. Simulation results show that the controller ensure the stabilized tracking and docking, and the AFKF outputs is continuous and stabilized during sensor failure comparing to centralize Kalman filter.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Autonomous Aerial Refueling for UAVs Based on GPS/MV



    Published in:

    Advanced Materials Research ; 433-440 ; 4087-4094


    Publication date :

    2012-01-03


    Size :

    8 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    GPS / MV Based Aerial Refueling for UAVs

    Mammarella, M. / Campa, G. / Napolitano, M. et al. | British Library Conference Proceedings | 2008


    GPS / MV Based Aerial Refueling for UAVs

    Mammarella, Marco / Campa, Giampiero / Napolitano, Marcello et al. | AIAA | 2008



    Autonomous Aerial Refueling for UAVs Using a Combined GPS-Machine Vision Guidance

    Campa, Giampiero / Fravolini, Mario Luca / Ficola, Antonio et al. | AIAA | 2004


    Vision-Based Autonomous Aerial Refueling

    Erkin, Tevfik / Abdo, Omer / Sanli, Yilmaz et al. | AIAA | 2022