Ivan l. Ermolov
Doctor of Technical Science, Professor, Ishlinsky Institute for Problems in Mechanics of the Russian Academy of Sciences (IPMech RAS), Deputy Director, 101-1, pr. Vernadskogo, Moscow, 119526, Russia, ermolov@ipmnet.ru, ORCID: 0000-0002-8458-7982
Sergey P. Khripunov
Doctor of Technical Science, Professor, V.A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences, Leading Research Scientist, 65, Profsoyuznaya ul., Moscow, 117997, Russia, hsp61@ipu.ru
Received November 15, 2022
Abstract
Unmanned systems often function in new, non-predetermined environment. This demands flexible and simultaneously stable function of these systems. This can be implemented by their adaptation and, as a final goal, self-learning or self-organization in control systems. Autonomous functioning in extreme environment requires self-learning drastically. Such environment can be hostile towards unmanned systems, it may contain sophisticated communication conditions. All these are deteriorated by poor on-board control algorithms. In some of such cases unmanned systems may become inefficient or, even more, useless in some cases. This brings to front necessity to create adaptive self-learning control systems for robots. These should be capable to generate efficient, or even optimal decisions in extreme environment. This paper presents on of possible approaches to create self-learning control systems based on so called decision along analogues.
Key words
Unmanned system, robots' autonomy, self-learning.
Acknowledgements
The present work was partially supported by the Ministry of Science and Higher Education within the framework of the Russian State Assignment under contract No.АААА-А20-120011690138-6).
DOI
10.31776/RTCJ.11106
Bibliographic description
Ermolov, I.I. and Khripunov, S.P. (2023). A possible approach to the creation of self-learning control systems for autonomous robots. Robotics and Technical Cybernetics, 11(1), pp.45-50.
UDC identifier:
004.896:007.52
References
