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Название: Informative modeling of subjective reality for intellectual anthropomorphic robots
Авторы: Dolganov, A. G.
Letnev, K. Y.
Дата публикации: 2020
Издатель: IOP Publishing Ltd
Библиографическое описание: Dolganov A. G. Informative modeling of subjective reality for intellectual anthropomorphic robots / A. G. Dolganov, K. Y. Letnev // IOP Conference Series: Materials Science and Engineering. — 2020. — Vol. 966. — Iss. 1. — 12084.
Аннотация: This research is aimed at solving the problem of safeguarding robot operation by modeling the subjective reality of an intellectual anthropomorphic robot. Analysis has been carried out on trends in designing advanced robot control systems and methods of improving the safety of robot usage. The following conclusions are drawn: the risk of causing damage to human life, health or property increases when people interact with robots; it is necessary to combine neural network control systems with expert control systems in order to enhance the intellect of a robot and raise the level of trust held by humans towards robots; developing norms and regulations, designing collaborative robots, drawing visualization diagrams for safety zones cannot really provide the depth of robot socialization sufficient for the human society; an informative model of the subjective reality could be integrated into an intellectual anthropomorphic robot to provide a safer 'human-robot' interaction. Such an approach should result in achieving the greatest trust of humans and their safety due to anthropomorphic conversion of both the external design of a robot and its internal control structure. By its nature, the research is interdisciplinary - it is run in the fields of artificial intelligence and philosophy of subjective reality. © Published under licence by IOP Publishing Ltd.
URI: http://elar.urfu.ru/handle/10995/118271
Условия доступа: info:eu-repo/semantics/openAccess
Конференция/семинар: 15th International Conference on Industrial Manufacturing and Metallurgy, ICIMM 2020
Дата конференции/семинара: 18 June 2020 through 19 June 2020
Идентификатор SCOPUS: 85097087542
Идентификатор PURE: 20235535
ISSN: 17578981
DOI: 10.1088/1757-899X/966/1/012084
Располагается в коллекциях:Научные публикации ученых УрФУ, проиндексированные в SCOPUS и WoS CC

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