ORB-ODOM: Stereo and odometer sensor fusion for simultaneous localization and mapping

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.creatorCaldato, Brenno A. C.-
Autor(es): dc.creatorFilho, Ricardo Achilles-
Autor(es): dc.creatorCastanho, José Eduardo C.-
Data de aceite: dc.date.accessioned2021-03-11T00:36:00Z-
Data de disponibilização: dc.date.available2021-03-11T00:36:00Z-
Data de envio: dc.date.issued2018-12-11-
Data de envio: dc.date.issued2018-12-11-
Data de envio: dc.date.issued2017-12-15-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1109/SBR-LARS-R.2017.8215301-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/171104-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/171104-
Descrição: dc.descriptionFinanciadora de Estudos e Projetos-
Descrição: dc.descriptionORB-SLAM2 is one of the better-known open source SLAM implementations available. However, the dependence of visual features causes it to fail in featureless environments. With the present work, we propose a new technique to improve visual odometry results given by ORB-SLAM2 using a tightly Sensor Fusion approach to integrate camera and odometer data. In this work, we use odometer readings to improve the tracking results by adding graph constraints between frames and introduce a new method for preventing the tracking loss. We test our method using three different datasets, and show an improvement in the estimated trajectory, allowing a continuous tracking without losses.-
Formato: dc.format1-5-
Idioma: dc.languageen-
Relação: dc.relationProceedings - 2017 LARS 14th Latin American Robotics Symposium and 2017 5th SBR Brazilian Symposium on Robotics, LARS-SBR 2017 - Part of the Robotics Conference 2017-
Direitos: dc.rightsopenAccess-
Título: dc.titleORB-ODOM: Stereo and odometer sensor fusion for simultaneous localization and mapping-
Aparece nas coleções:Repositório Institucional - Unesp

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