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Modeling ℝ³ needle steering in Uppaal
Citation Link: https://doi.org/10.15480/882.4623
Publikationstyp
Conference Paper
Date Issued
2022-03-21
Sprache
English
Author(s)
TORE-DOI
First published in
Number in series
355
Start Page
40
End Page
59
Citation
Electronic proceedings in theoretical computer science 355: 40-59 (2022)
Contribution to Conference
Publisher DOI
Scopus ID
ArXiv ID
Publisher
NICTA
Medical cyber-physical systems are safety-critical, and as such, require ongoing verification of their correct behavior, as system failure during run time may cause severe (or even fatal) personal damage. However, creating a verifiable model often conflicts with other application requirements, most notably regarding data precision and model accuracy, as efficient model checking promotes discrete data (over continuous) and abstract models to reduce the state space. In this paper, we approach the task of medical needle steering in soft tissue around potential obstacles. We design a verifiable model of needle motion (implemented in Uppaal Stratego) and a framework embedding the model for online needle steering. We mitigate the conflict by imposing boundedness on both the data types, reducing from R3 to Z3 when needed, and the motion and environment models, reducing the set of allowed local actions and global paths. In experiments, we successfully apply the static model alone, as well as the dynamic framework in scenarios with varying environment complexity and both a virtual and real needle setting, where up to 100% of targets were reached depending on the scenario and needle.
DDC Class
004: Informatik
Publication version
publishedVersion
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2203.09884v1.pdf
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1.2 MB
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