The 4IPLAY project wants to develop innovative solution to demonstrate in relevant environments the concept of repeatable automated visual inspection of infrastructures as bridges based on autonomous drones. 4IPLAY builds on the know-how experience of a multi-disciplinary research team and is focus on three main pillars: (i) automated acquisition and processing of multi-spectral data using artificial intelligence approaches; (ii) advanced flight control logics which are tailored for the conditions encountered in the proximity of large infrastructures; (iii) distributed multi-drone architectures to support real time cooperative navigation and offline trajectory reconstruction. The analysis of images using artificial intelligence approaches will be one of the pillar, with a focus on the detection of defects also using generative techniques to augments dataset. Two key aspects are analyzed for the control system: the definition of a data-driven model for ceiling and wall effects and a disturbance-rejection control system for an Unmanned Aerial Vehicle. The research on cooperative multi-drone systems includes 1-to-N planning and control, as well as tight integration of cooperative navigation and distributed sensing. The paper introduces the main research areas of the project and provides an overview of current progress.


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    Titel :

    4IPLAY - Improving Intelligent Infrastructure Inspection by Pushing UAS Level of Autonomy in Challenging Environments




    Erscheinungsdatum :

    03.06.2024


    Format / Umfang :

    9966406 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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