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    Getting it Right the First time: Robot Mission Guarantees in the Presence of Uncertainty

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    GIRTFT_iros13_v7_finalv1.pdf (601.1Kb)
    Date
    2013
    Author
    Lyons, Damian M.
    Arkin, Ronald C.
    Nirmal, P.
    Jiang, Shu
    Liu, Tsung-Ming
    Deeb, J.
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    Abstract
    Certain robot missions need to perform predictably in a physical environment that may only be poorly characterized in advance. We have previously developed an approach to establishing performance guarantees for behavior-based controllers in a process-algebra framework. We extend that work here to include random variables, and we show how our prior results can be used to generate a Dynamic Bayesian Network for the coupled system of program and environment model. Verification is reduced to a filtering problem for this network. Finally, we present validation results that demonstrate the effectiveness of the verification of a multiple waypoint robot mission using this approach.
    URI
    http://hdl.handle.net/1853/50051
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    • Mobile Robot Laboratory [187]
    • Mobile Robot Laboratory Publications [187]

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