The expansion of mobile sensors, like robots and uncrewed aerial vehicles (UAVs), across diverse applications such as remote sensing, monitoring, and communication relay, has been exponential. Yet, ensuring their safe and successful operation depends crucially on optimized deployment tailored to the application requirements while constrained by various limitations. This study focuses on the optimization of robot/UAV trajectories under these constraints. However, implementing constraints poses considerable challenges. To this end, a framework for constrained deployment optimization of wireless robotic swarms is proposed. This framework formulates as a quadratic-programming problem which utilizes Bézier curves to model trajectories and predict their states over a time horizon. Constraints are systematically categorized and embedded in the Bézier curve formulation. This framework offers ease of adoption to various scenarios and flexibility in accommodating different mobile sensor dynamics, constraints, and deployment strategies.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    A Framework for Constrained Deployment Optimization of Wireless Mobile Sensor Networks


    Beteiligte:


    Erscheinungsdatum :

    07.10.2024


    Format / Umfang :

    591301 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Unmanned Aerial Vehicles in Wireless Sensor Networks: Automated Sensor Deployment and Mobile Sink Nodes

    Marchal Gomez, Juan / Wiedemann, Thomas / Shutin, Dmitriy | Springer Verlag | 2018



    An Incremental Self-Deployment Algorithm for Mobile Sensor Networks

    Howard, A. / Mataric, M. J. / Sukhatme, G. S. | British Library Online Contents | 2002



    Voronoi-Based Cooperative Node Deployment Algorithm in Mobile Sensor Networks

    Ghahroudi, Mahsa Sadeghi / Shahrabi, Alireza / Boutaleb, Tuleen | IEEE | 2020