KFU. Card publication. Towards robot fall detection and management for russian humanoid AR-601

KAZAN
FEDERAL UNIVERSITY

- RUS
- 中文
- ES

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

Form of presentation

Articles in international journals and collections

Year of publication

2018

Язык

английский

Authors, employees of KFU

Magid Evgeniy Arkadevich, author

Sagitov Artur Gazizovich, author

Authors, postgraduates KFU

Sagitov Artur Gazizovich, postgraduate kfu

Bibliographic description in the original language

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.

Annotation

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

Keywords

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

The name of the journal

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

Please use this ID to quote from or refer to the card

https://repository.kpfu.ru/eng/?p_id=161698&p_lang=2

Resource files

File name	Size (MB)	Format
2017_Towards_robot_fall_detection_and_management_for_russian_humanoid_AR_601.pdf	0,62	pdf	show / download

Full metadata record

Field DC	Value	Language
dc.contributor.author	Magid Evgeniy Arkadevich	ru_RU
dc.contributor.author	Sagitov Artur Gazizovich	ru_RU
dc.contributor.author	Sagitov Artur Gazizovich	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/eng/?p_id=161698&p_lang=2	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	Articles in international journals and collections	ru_RU