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Кудрявцев, Константин Яковлевич

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Институт интеллектуальных кибернетических систем
Цель ИИКС и стратегия развития - это подготовка кадров, способных противостоять современным угрозам и вызовам, обладающих знаниями и компетенциями в области кибернетики, информационной и финансовой безопасности для решения задач разработки базового программного обеспечения, повышения защищенности критически важных информационных систем и противодействия отмыванию денег, полученных преступным путем, и финансированию терроризма.
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Кудрявцев
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Константин Яковлевич
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2020 - 20212
2
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Автор: Возненко, Тимофей Игоревич × Имеет файлы: Yes ×

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    The Command Interpretation in Decomposition Method of Multi-Channel Control for a Robotic Device
    (2020) Voznenko, T. I.; Gridnev, A. A.; Chepin, E. V.; Kudryavtsev, K. Y.; Возненко, Тимофей Игоревич; Гриднев, Александр Александрович; Чепин, Евгений Валентинович; Кудрявцев, Константин Яковлевич
    © 2020 The Authors. Published by Elsevier B.V.Multi-channel control is a way of control using a few different channels simultaneously. The example of the multi-channel system is the extended brain-computer interface (extended-BCI) where voice, gesture and BCI control channels are used at the same time. However, this way of control is redundant: One command can be executed using different control channels. Because of each channel have errors of both types the control using few channels simultaneously can increase unwanted influence on robotic device control. One way to decrease this effect is to decompose the multi-channel control method into one composite channel. That composed channel should be defined based on some parameter and the best way of control. In this article, we consider MTnP parameter. During decomposition of the multi-channel system, command information not in composed channel is usually ignored. In this article, we propose a way of this information interpretation to improve the multi-channel control decomposition method for a robotic wheelchair using the extended-BCI.
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    Algorithm for Multi-Channel Robotic Device Control Based on Minimizing Bayesian Risk
    (2021) Voznenko, T. I.; Kudryavtsev, K. Y.; Возненко, Тимофей Игоревич; Кудрявцев, Константин Яковлевич
    © 2020 Elsevier B.V.. All rights reserved.Currently, mobile robotic devices are widely used in various fields of human activity, which imposes high requirements on the reliability of their operation. Improving the reliability and quality of control of mobile robotic devices is possible through the use of multi-channel control systems. Signals coming from different control channels are subject to various interference, which can lead to wrong decisions. In this regard, the problem of minimizing the risk of making an incorrect control decision is urgent. This paper gives a theoretical justification for the algorithm for choosing a control command for a multi-channel control system of a mobile robotic device. The algorithm is based on minimizing the Bayesian risk of choosing an erroneous command. To implement the algorithm, it is necessary to have statistical information about the quality of functioning of each control channel.