An integrated sensing approach that fuses vision and range information to land an autonomous class 1 unmanned aerial system (UAS) controlled by e-modification model reference adaptive control is presented. The navigation system uses a feature detection algorithm to locate features and compute the corresponding range vectors on a coarsely instrumented landing platform. The relative translation and rotation state is estimated and sent to the flight computer for control feedback. A robust adaptive control law that guarantees uniform ultimate boundedness of the adaptive gains in the presence of bounded external disturbances is used to control the flight vehicle. Experimental flight tests are conducted to validate the integration of these systems and measure the quality of result from the navigation solution. Robustness of the control law amidst flight disturbances and hardware failures is demonstrated. The research results demonstrate the utility of low-cost, low-weight navigation solutions for navigation of small, autonomous UAS to carryout littoral proximity operations about unprepared shipdecks.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    A CAMERA AND RANGE SENSOR FUSION APPROACH FOR AUTONOMOUS NAVIGATION SYSTEMS DRIVEN BY ROBUST ADAPTIVE CONTROL


    Contributors:


    Publication date :

    2024-01-01


    Size :

    22 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




    Adaptive Sensor Fusion of Camera, GNSS and IMU for Autonomous Driving Navigation

    Ren, Weining / Jiang, Kun / Chen, Xinxin et al. | IEEE | 2020



    Sensor Fusion for Autonomous Mobile Robot Navigation

    Plascencia, Alfredo | BASE | 2008

    Free access

    Multi-sensor data fusion for autonomous vehicle navigation through adaptive particle filter

    Hossein, Tehrani Nik Nejad / Mita, Seiichi / Han Long, | IEEE | 2010


    RANGE-Robust autonomous navigation in GPS-denied environments

    Bachrach, A. / Prentice, S. / He, R. et al. | British Library Online Contents | 2011