Title:
Getting it Right the First time: Robot Mission Guarantees in the Presence of Uncertainty
Getting it Right the First time: Robot Mission Guarantees in the Presence of Uncertainty
Author(s)
Lyons, Damian M.
Arkin, Ronald C.
Nirmal, P.
Jiang, Shu
Liu, Tsung-Ming
Deeb, J.
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.
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Date Issued
2013
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Text
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Paper