Modelling mobile robot navigation in 3D environments: camera-based stairs recognition in Gazebo

Meshheryakov Roman Valerevich; Mustafin Maxim Andreevich; Martinez-Garsia Edgar A.; Tsoy Tatyana Grigorevna; Magid Evgeni Arkadevich

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dc.contributor	Казанский федеральный университет
dc.contributor.author	Mustafin Maxim Andreevich
dc.contributor.author	Tsoy Tatyana Grigorevna
dc.contributor.author	Martinez-Garsia Edgar A.
dc.contributor.author	Meshheryakov Roman Valerevich
dc.contributor.author	Magid Evgeni Arkadevich
dc.date.accessioned	2023-09-21T08:38:57Z
dc.date.available	2023-09-21T08:38:57Z
dc.date.issued	2022
dc.identifier.citation	Modelling mobile robot navigation in 3D environments: camera-based stairs recognition in Gazebo / M. Mustafin, T. Tsoy, E.A. Martınez-Garcıa [et al.] // 2022 Moscow Workshop on Electronic and Networking Technologies (MWENT). Moscow, 2022. - P. 1-6.
dc.identifier.uri	https://dspace.kpfu.ru/xmlui/handle/net/176906
dc.description.abstract	The task of sensory-based autonomous navigation of mobile robots requires data fusion from multiple sources in order to properly detect and recognize environmental obstacles. One of important issues mobile robots deal in a typical multilevel indoor environment is a stair well detection and negotiation. This paper presents ROS-based stairs detection implementation using onboard cameras of the Russian mobile crawler robot Servosila Engineer. Virtual experiments were performed in Gazebo environment with a single camera and a stereo camera
dc.language.iso	en
dc.relation.ispartofseries	Moscow Workshop on Electronic and Networking Technologies (MWENT-2022)
dc.rights	открытый доступ
dc.subject	Computer vision
dc.subject	Object recognition
dc.subject	ROS
dc.subject	Gazebo
dc.subject	Mobile crawler robot
dc.title	Modelling mobile robot navigation in 3D environments: camera-based stairs recognition in Gazebo
dc.type	Article
dc.contributor.org	Институт информационных технологий и интеллектуальных систем
dc.description.pages	1-6
dc.pub-id	268021
dc.identifier.doi	10.1109/MWENT55238.2022.9802368