Izvestiya of Saratov University.

Mathematics. Mechanics. Informatics

ISSN 1816-9791 (Print)
ISSN 2541-9005 (Online)


For citation:

Larkin E. V., Akimenko T. A., Bogomolov A. V. Modeling the reliability of the onboard equipment of a mobile robot. Izvestiya of Saratov University. Mathematics. Mechanics. Informatics, 2021, vol. 21, iss. 3, pp. 390-399. DOI: 10.18500/1816-9791-2021-21-3-390-399, EDN: GUSCGX

This is an open access article distributed under the terms of Creative Commons Attribution 4.0 International License (CC-BY 4.0).
Published online: 
31.08.2021
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English
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Article type: 
Article
UDC: 
631.353.3
EDN: 
GUSCGX

Modeling the reliability of the onboard equipment of a mobile robot

Autors: 
Larkin Eugene V., Tula State University
Akimenko Tatiana A., Tula State University, Russia
Bogomolov Aleksey Valer'evich, St. Petersburg Federal Research Center of the Russian Academy of Science
Abstract: 

Mobile robots with complex onboard equipment are investigated in this article. It is shown that their onboard equipment, for providing the required reliability parameters, must have fault-tolerant properties. For designing such equipment it is necessary to have an adequate model of reliability parameters evaluation. The approach, linked to the creation of the model, based on parallel semi-Markov process apparatus, is considered. At the first stage of modeling, the lifetime of the single block in a complex fault-recovery cycle is determined. Dependences for the calculation of time intervals and probabilities of wandering through ordinary semi-Markov processes for a common case are obtained. At the second stage, ordinary processes are included in the parallel one, which simulates the lifetime of the equipment lifetime as a whole. To simplify calculations, a digital model of faults with the use of the procedure of histogram sampling is proposed.  It is shown that the number of samples permits to control both the accuracy and the computational complexity of  the procedure for calculating the reliability parameters.

Acknowledgments: 
This work was supported by a grant from the President of the Russian Federation for state support of leading scientific schools of the Russian Federation (NSh2553.2020.8).
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Received: 
04.11.2019
Accepted: 
16.01.2021
Published: 
31.08.2021