Detection and tracking of dynamic objects by using a multirobot system: Application to critical infrastructures surveillance

The detection and tracking of mobile objects (DATMO) is progressively gaining importance for security and surveillance applications. This article proposes a set of new algorithms and procedures for detecting and tracking mobile objects by robots that work collaboratively as part of a multirobot syst...

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Detalles Bibliográficos
Autores: Rodríguez-Canosa, Gonzalo R., Cerro, Jaime del, Barrientos, Antonio
Tipo de recurso: artículo
Fecha de publicación:2014
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/102625
Acceso en línea:http://hdl.handle.net/10261/102625
Access Level:acceso abierto
Palabra clave:Camera
Information
Robot
Laser scanner
Vehicle detection
DATMO
Multirobot
Critical infrastructure surveillance
Moving-Objects
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oai_identifier_str oai:digital.csic.es:10261/102625
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repository_id_str
spelling Detection and tracking of dynamic objects by using a multirobot system: Application to critical infrastructures surveillanceRodríguez-Canosa, Gonzalo R.Cerro, Jaime delBarrientos, AntonioCameraInformationRobotLaser scannerVehicle detectionDATMOMultirobotCritical infrastructure surveillanceMoving-ObjectsThe detection and tracking of mobile objects (DATMO) is progressively gaining importance for security and surveillance applications. This article proposes a set of new algorithms and procedures for detecting and tracking mobile objects by robots that work collaboratively as part of a multirobot system. These surveillance algorithms are conceived of to work with data provided by long distance range sensors and are intended for highly reliable object detection in wide outdoor environments. Contrary to most common approaches, in which detection and tracking are done by an integrated procedure, the approach proposed here relies on a modular structure, in which detection and tracking are carried out independently, and the latter might accept input data from different detection algorithms. Two movement detection algorithms have been developed for the detection of dynamic objects by using both static and/or mobile robots. The solution to the overall problem is based on the use of a Kalman filter to predict the next state of each tracked object. Additionally, new tracking algorithms capable of combining dynamic objects lists coming from either one or various sources complete the solution. The complementary performance of the separated modular structure for detection and identification is evaluated and, finally, a selection of test examples discussed. © 2014 by the authors; licensee MDPI, Basel, Switzerland.ROTOS: Multi-robot system for outdoor infrastructuresprotection, sponsored by the Spanish Ministry of Education and Science. DPI2010-17998; ROBOCITY2030, sponsored by the Community of Madrid. S-0505/DPI/000235Peer ReviewedMultidisciplinary Digital Publishing Institute2014201420142014info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501http://hdl.handle.net/10261/102625reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Inglésinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/1026252026-05-22T06:33:51Z
dc.title.none.fl_str_mv Detection and tracking of dynamic objects by using a multirobot system: Application to critical infrastructures surveillance
title Detection and tracking of dynamic objects by using a multirobot system: Application to critical infrastructures surveillance
spellingShingle Detection and tracking of dynamic objects by using a multirobot system: Application to critical infrastructures surveillance
Rodríguez-Canosa, Gonzalo R.
Camera
Information
Robot
Laser scanner
Vehicle detection
DATMO
Multirobot
Critical infrastructure surveillance
Moving-Objects
title_short Detection and tracking of dynamic objects by using a multirobot system: Application to critical infrastructures surveillance
title_full Detection and tracking of dynamic objects by using a multirobot system: Application to critical infrastructures surveillance
title_fullStr Detection and tracking of dynamic objects by using a multirobot system: Application to critical infrastructures surveillance
title_full_unstemmed Detection and tracking of dynamic objects by using a multirobot system: Application to critical infrastructures surveillance
title_sort Detection and tracking of dynamic objects by using a multirobot system: Application to critical infrastructures surveillance
dc.creator.none.fl_str_mv Rodríguez-Canosa, Gonzalo R.
Cerro, Jaime del
Barrientos, Antonio
author Rodríguez-Canosa, Gonzalo R.
author_facet Rodríguez-Canosa, Gonzalo R.
Cerro, Jaime del
Barrientos, Antonio
author_role author
author2 Cerro, Jaime del
Barrientos, Antonio
author2_role author
author
dc.subject.none.fl_str_mv Camera
Information
Robot
Laser scanner
Vehicle detection
DATMO
Multirobot
Critical infrastructure surveillance
Moving-Objects
topic Camera
Information
Robot
Laser scanner
Vehicle detection
DATMO
Multirobot
Critical infrastructure surveillance
Moving-Objects
description The detection and tracking of mobile objects (DATMO) is progressively gaining importance for security and surveillance applications. This article proposes a set of new algorithms and procedures for detecting and tracking mobile objects by robots that work collaboratively as part of a multirobot system. These surveillance algorithms are conceived of to work with data provided by long distance range sensors and are intended for highly reliable object detection in wide outdoor environments. Contrary to most common approaches, in which detection and tracking are done by an integrated procedure, the approach proposed here relies on a modular structure, in which detection and tracking are carried out independently, and the latter might accept input data from different detection algorithms. Two movement detection algorithms have been developed for the detection of dynamic objects by using both static and/or mobile robots. The solution to the overall problem is based on the use of a Kalman filter to predict the next state of each tracked object. Additionally, new tracking algorithms capable of combining dynamic objects lists coming from either one or various sources complete the solution. The complementary performance of the separated modular structure for detection and identification is evaluated and, finally, a selection of test examples discussed. © 2014 by the authors; licensee MDPI, Basel, Switzerland.
publishDate 2014
dc.date.none.fl_str_mv 2014
2014
2014
2014
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/102625
url http://hdl.handle.net/10261/102625
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute
publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869406840597512192
score 15,81155

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