Verifying Performance for Autonomous Robot Missions with Uncertainty
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Abstract
Establishing performance guarantees for robot missions is especially important for C-WMD applications.
Software verification techniques, such as model checking (Clark
1999, Jhala & Majumdar 2009), can be
applied to robotic applications but characteristics of this application area, including addition of a
robot environment
model and handling
continuous
spatial location well, exacerbate state explosion, a key
weakness of
these methods. We have proposed an approach to verifying robot missions that shifts the focus from state-based analysis
onto the solution of a set of flow equations (Lyons et al. 2012).
The key novelty
introduced in this paper is a probabilistic spatial representation for flow equations. We show how this representation models the
spatial situation for robot motion with
environments
or controllers
that include discrete choice (constraints). A model such as we propose here is useful only if it can accurately predict robot motion. We conclude by
presenting three validation results that show this
approach has strong predictive power
; that is, that the
verifications it produces can be trusted.
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Date
2012
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