Change detection using weighted features for image-based localization

dc.affiliation.dptoUC3M. Departamento de Ingeniería de Sistemas y Automáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Laboratorio de Robótica (Robotics Lab)es
dc.contributor.authorDernera, Erik
dc.contributor.authorGómez Blázquez, Clara
dc.contributor.authorHernández Silva, Alejandra Carolina
dc.contributor.authorBarber Castaño, Ramón Ignacio
dc.contributor.authorBabuska, Robert
dc.contributor.funderComunidad de Madrides
dc.contributor.funderMinisterio de Economía y Competitividad (España)es
dc.description.abstractAutonomous mobile robots are becoming increasingly important in many industrial and domestic environments. Dealing with unforeseen situations is a difficult problem that must be tackled to achieve long-term robot autonomy. In vision-based localization and navigation methods, one of the major issues is the scene dynamics. The autonomous operation of the robot may become unreliable if the changes occurring in dynamic environments are not detected and managed. Moving chairs, opening and closing doors or windows, replacing objects and other changes make many conventional methods fail. To deal with these challenges, we present a novel method for change detection based on weighted local visual features. The core idea of the algorithm is to distinguish the valuable information in stable regions of the scene from the potentially misleading information in the regions that are changing. We evaluate the change detection algorithm in a visual localization framework based on feature matching by performing a series of long-term localization experiments in various real-world environments. The results show that the change detection method yields an improvement in the localization accuracy, compared to the baseline method without change detection. In addition, an experimental evaluation on a public long-term localization data set with more than 10 000 images reveals that the proposed method outperforms two alternative localization methods on images recorded several months after the initial mapping.en
dc.description.sponsorshipThis work was supported by the European Regional Development Fund under the project Robotics for Industry 4.0 (reg. no. CZ.02.1.01/0.0/0.0/15_003/0000470) and by the Grant Agency of the Czech Technical University in Prague, grant no.SGS19/174/OHK3/3T/13. This research has also received funding from HEROITEA: Heterogeneous Intelligent Multi-Robot Team for Assistance of Elderly People (RTI2018-095599-B-C21), funded by Spanish Ministerio de Economia y Competitividad, and the RoboCity2030 - DIH-CM project (S2018/NMT-4331, RoboCity2030 - Madrid Robotics Digital Innovation Hub, Spain).en
dc.identifier.bibliographicCitationDerner, E., Gomez, C., Hernandez, A. C., Barber, R. & Babuška, R. (2021). Change detection using weighted features for image-based localization. Robotics and Autonomous Systems, 135, 103676.en
dc.identifier.publicationtitleRobotics and Autonomous Systemsen
dc.relation.projectIDComunidad de Madrid. S2018/NMT-4331es
dc.relation.projectIDGobierno de España. RTI2018-095599-B-C21es
dc.rights© 2020 Elsevier B.V. All rights reserved.en
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.rights.accessRightsopen accessen
dc.subject.ecienciaRobótica e Informática Industriales
dc.subject.otherChange detectionen
dc.subject.otherImage-based localizationen
dc.subject.otherLong-term autonomyen
dc.subject.otherMobile roboticsen
dc.titleChange detection using weighted features for image-based localizationen
dc.typeresearch article*
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