An interesting applications of Unmanned Aerial Systems is surveillance. Surveillance typically involves the tracking of one or several targets in an area. A key issue for this application is the autonomous decision-making to allocate UAS to targets and determine the actions to be performed by the UAS of the fleet. Since this optimal decision-making needs to deal with uncertainties, Partially Observable Markov Decision Processes (POMDPs) are proposed as models for the surveillance mission. The paper proposes a role-assignment method to alleviate the computational complexity of the application of POMDPs to multi-UAS surveillance. The method is evaluated by simulation and compared with other similar approaches. Furthermore, the system has been implemented in a testbed with real quadcopters to show some preliminary experiments of two UAS tracking two different targets.


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    Titel :

    Decentralized cooperation of multiple UAS for multi-target surveillance under uncertainties


    Beteiligte:
    Capitan, Jesus (Autor:in) / Merino, Luis (Autor:in) / Ollero, Anibal (Autor:in)


    Erscheinungsdatum :

    01.05.2014


    Format / Umfang :

    5002171 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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