The Autonomous Sciencecraft Experiment (ASE) will operate onboard the Earth Orbiter 1 mission 2004. The ASE software uses onboard continuous planning, robust task and goal-based execution, and onboard machine learning and patter recognition to radically increase science return by enabling intelligent downlink selection and autnomous retargeting. In this paper we will discuss how these AI technologies are synergistically integrated in multi-layer control architecture to enable a virtual spacecraft science agent.


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    Titel :

    Preliminary results of the autonomous sciencecraft experiment


    Beteiligte:
    Rabideau, Gregg (Autor:in) / Davies, Ashley (Autor:in) / Castano, Rebecca (Autor:in) / Cichy, Benjamin (Autor:in) / Tran, Daniel (Autor:in) / Chien, Steve (Autor:in) / Sherwood, Robert (Autor:in)

    Erscheinungsdatum :

    01.05.2004


    Medientyp :

    Preprint


    Format :

    Keine Angabe


    Sprache :

    Englisch



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