КФУ. Карточка публикации. Towards robot fall detection and management for russian humanoid AR-601

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TOWARDS ROBOT FALL DETECTION AND MANAGEMENT FOR RUSSIAN HUMANOID AR-601

Форма представления

Статьи в зарубежных журналах и сборниках

Год публикации

2018

Язык

английский

Авторы, сотрудники КФУ

Магид Евгений Аркадьевич, автор

Сагитов Артур Газизович, автор

Авторы, аспиранты КФУ

Сагитов Артур Газизович, автор

Библиографическое описание на языке оригинала

Magid E. Towards Robot Fall Detection and Management for Russian Humanoid AR-601 / Sagitov A. // Smart Innovation, Systems and Technologies. - 2017. - №74. - p. 200-209.

Аннотация

While interacting in a human environment, a fall is the main threat to safety and successful operation of humanoid robots, and thus it is critical to explore ways to detect and manage an unavoidable fall of humanoid robots. Even assuming perfect bipedal walking strategies and algorithms, there exist several unexpected factors, which can threaten existing balance of a humanoid robot. These include such issues as power failure, robot component failures, communication disruptions and failures, sudden forces applied to the robot externally as well as internally generated exceed torques etc. As progress in a humanoid robotics continues, robots attain more autonomy and enter realistic human environments, they will inevitably encounter such factors more frequently. Undesirable fall might cause serious physical damage to a human user, to a robot and to surrounding environment. In this paper, we present a brief review of strategies that include algorithms for fall prediction, avoidance, and dam

Ключевые слова

AR-601, Fall prediction, Humanoid robot fall, Humanoid robots, Robot control, Safe fall, Safety

Название журнала

Smart Innovation, Systems and Technologies

URL

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85020412784&doi=10.1007%2f978-3-319-59394-4_20&partnerID=40&md5=20682768671b334f49563ac5620a2844

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https://repository.kpfu.ru/?p_id=161698

Файлы ресурса

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2017_Towards_robot_fall_detection_and_management_for_russian_humanoid_AR_601.pdf	0,62	pdf	посмотреть / скачать

Полная запись метаданных

Поле DC	Значение	Язык
dc.contributor.author	Магид Евгений Аркадьевич	ru_RU
dc.contributor.author	Сагитов Артур Газизович	ru_RU
dc.contributor.author	Сагитов Артур Газизович	ru_RU
dc.date.accessioned	2018-01-01T00:00:00Z	ru_RU
dc.date.available	2018-01-01T00:00:00Z	ru_RU
dc.date.issued	2018	ru_RU
dc.identifier.citation	Magid E. Towards Robot Fall Detection and Management for Russian Humanoid AR-601 / Sagitov A. // Smart Innovation, Systems and Technologies. - 2017. - №74. - p. 200-209.	ru_RU
dc.identifier.uri	https://repository.kpfu.ru/?p_id=161698	ru_RU
dc.description.abstract	Smart Innovation, Systems and Technologies	ru_RU
dc.description.abstract	While interacting in a human environment, a fall is the main threat to safety and successful operation of humanoid robots, and thus it is critical to explore ways to detect and manage an unavoidable fall of humanoid robots. Even assuming perfect bipedal walking strategies and algorithms, there exist several unexpected factors, which can threaten existing balance of a humanoid robot. These include such issues as power failure, robot component failures, communication disruptions and failures, sudden forces applied to the robot externally as well as internally generated exceed torques etc. As progress in a humanoid robotics continues, robots attain more autonomy and enter realistic human environments, they will inevitably encounter such factors more frequently. Undesirable fall might cause serious physical damage to a human user, to a robot and to surrounding environment. In this paper, we present a brief review of strategies that include algorithms for fall prediction, avoidance, and dam	ru_RU
dc.language.iso	ru	ru_RU
dc.subject	AR-601	ru_RU
dc.subject	Fall prediction	ru_RU
dc.subject	Humanoid robot fall	ru_RU
dc.subject	Humanoid robots	ru_RU
dc.subject	Robot control	ru_RU
dc.subject	Safe fall	ru_RU
dc.subject	Safety	ru_RU
dc.title	Towards robot fall detection and management for russian humanoid AR-601	ru_RU
dc.type	Статьи в зарубежных журналах и сборниках	ru_RU