In this article, we simulate an ensemble of cooperating, mobile sensing agents that implement the cyclic stochastic optimization (CSO) algorithm in an attempt to survey, track, and follow multiple targets. In the CSO algorithm proposed, each agent uses its sensed measurements, its shared information, and its predictions of other agents’ future motion to decide on its next action. This decision is selected to minimize a loss function that decreases as the uncertainty in the target state estimates decreases. Only noisy measurements of this loss function are available to each agent, and, in this study, each agent attempts to minimize this function by calculating its gradient. This article examines, via simulation-based experiments, the implications and applicability of CSO convergence in three dimensions.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Three-Dimensional Swarming Using Cyclic Stochastic Optimization


    Contributors:


    Publication date :

    2022-04-01


    Size :

    2163813 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





    SWARMING FLIGHTS CONTROLLING METHOD AND SWARMING FLIGHTS CONTROLLING SYSTEM

    MOON SUNG TAE / KIM DO YOON / CHOI JOON MIN | European Patent Office | 2020

    Free access


    Swarming UAS II

    M. Dabkowski / J. Cook / R. Kewley | NTIS | 2010