The Autonomous Sciencecraft Experiment (ASE) will fly onboard the Air Force TechSat 21 constellation of three spacecraft scheduled for launch in 2006. ASE uses onboard continuous planning, robust task and goal-based execution, model-based mode identification and reconfiguration, and onboard machine learning and pattern recognition to radically increase science return by enabling intelligent downlink selection and autonomous retargeting. In this paper we discuss how these AI technologies are synergistically integrated in hybrid multi-layer control architecture to enable to virtual spacecraft science agent. Demonstration of these capabilities in a flight environment will open up tremendous new opportunities in planetary science, space physics, and earth science that would be unreachable without this technology.


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    Title :

    The autonomous sciencecraft experiment


    Contributors:
    Sherwood, R. (author) / Chien, S. (author) / Castano, R. (author) / Rabideau, G. (author)


    Publication date :

    2003-01-01


    Size :

    1388577 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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