Model-based reasoning has been applied as an autonomous control strategy on the Low Energy Neutral Atom (LENA) instrument currently flying onboard the Imager for Magnetosphere-to-Aurora Global Exploration (IMAFE) spacecraft. Explicit models of instrument subsystem responses have been constructed and are used to dynamically adapt the instrument to the spacecraft's environment. These functions are cast as part of a virtual Principal Investigator (VPI) that autonomously monitors and controls the instrument. In the VPI's current implementation, LENA's command uplink volume has been decreased significantly from its previous volume; typically, no uplinks are required for operations. This work demonstrates that a model-based approach can be used to enhance science instrument effectiveness. The components of LENA are common in space science instrumentation, and lessons learned by modeling this system may be applied to other instruments. Future work involves the extension of these methods to cover more aspects of LENA operation and the generalization to other space science instrumentation.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Using model-based reasoning for autonomous instrument operation


    Contributors:


    Publication date :

    2001-01-01


    Size :

    976279 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Autonomous vehicle operation with explicit occlusion reasoning

    WRAY KYLE HOLLINS / WITWICKI STEFAN / ZILBERSTEIN SHLOMO | European Patent Office | 2023

    Free access

    Autonomous Vehicle Operation with Explicit Occlusion Reasoning

    WRAY KYLE HOLLINS / WITWICKI STEFAN / ZILBERSTEIN SHLOMO | European Patent Office | 2021

    Free access

    Enabling Autonomous Propellant Loading: Providing Situational Awareness Through Model Based Reasoning

    Walker, Mark / Walker, William E. / Figueroa, Fernando | NTRS | 2016