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Quantitative Reliability Assessment for Mobile Cooperative Systems

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Computer Safety, Reliability, and Security (SAFECOMP 2016)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 9923))

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Abstract

This article proposes a systematic approach to statistical testing for cooperative systems consisting of autonomous mobile agents. Based on Coloured Petri Net models of cooperative behaviour, it analyses different sources of randomness and defines an automatic test case generation procedure to derive cooperative scenarios according to a given operational profile. As an example, the approach is applied to a model of trolleys moving within a common environment. The results allow for quantitative reliability estimations of cooperative behaviour on the basis of statistical sampling theory.

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References

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Acknowledgment

The authors gratefully acknowledge that part of the work presented was carried out within the European Research Programme ARTEMIS (Advanced Research and Technology for Embedded Intelligence and Systems), project R5-COP (Reconfigurable ROS-based Resilient Reasoning Robotic Co-operating Systems), supported by the German Federal Ministry of Education and Research (BMBF).

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Correspondence to Francesca Saglietti .

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Appendix

Appendix

See Tables 2, 3, 4, 5, 6 and 7.

Table 2. Initial function availability of robots (-: function unavailable, X: function available)
Table 3. Risk level and charging facility per area (-: normal, X: risky, N: no charge, Y: charge)
Table 4. Probability of areas being mission targets
Table 5. Probability of areas being mission targets with given functional demands
Table 6. Probability of segment types being robot starting positions
Table 7. Failure probability of robot functions in normal and risky areas

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Saglietti, F., Spengler, R., Meitner, M. (2016). Quantitative Reliability Assessment for Mobile Cooperative Systems. In: Skavhaug, A., Guiochet, J., Schoitsch, E., Bitsch, F. (eds) Computer Safety, Reliability, and Security. SAFECOMP 2016. Lecture Notes in Computer Science(), vol 9923. Springer, Cham. https://doi.org/10.1007/978-3-319-45480-1_10

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  • DOI: https://doi.org/10.1007/978-3-319-45480-1_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-45479-5

  • Online ISBN: 978-3-319-45480-1

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