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dc.contributor.authorVeiga Almagro, Carloses_ES
dc.contributor.authorCastro, Mario Dies_ES
dc.contributor.authorLunghi, Giacomoes_ES
dc.contributor.authorMarín Prades, Raúles_ES
dc.contributor.authorSanz Valero, Pedro Josées_ES
dc.contributor.authorFerre Pérez, Manueles_ES
dc.contributor.authorMasi, Alessandroes_ES
dc.date.accessioned2020-08-12T15:41:42Z-
dc.date.available2020-08-12T15:41:42Z-
dc.date.issued2019-07-22-
dc.identifier.citationSensors 19 (14): 3220 (2019)es_ES
dc.identifier.issn1424-8220-
dc.identifier.urifile:///C:/Users/macr_/Downloads/sensors-19-03220.pdf-
dc.identifier.urihttp://hdl.handle.net/10261/217859-
dc.description.abstractRobotic interventions in hazardous scenarios need to pay special attention to safety, as in most cases it is necessary to have an expert operator in the loop. Moreover, the use of a multi-modal Human-Robot Interface allows the user to interact with the robot using manual control in critical steps, as well as semi-autonomous behaviours in more secure scenarios, by using, for example, object tracking and recognition techniques. This paper describes a novel vision system to track and estimate the depth of metallic targets for robotic interventions. The system has been designed for on-hand monocular cameras, focusing on solving lack of visibility and partial occlusions. This solution has been validated during real interventions at the Centre for Nuclear Research (CERN) accelerator facilities, achieving 95% success in autonomous mode and 100% in a supervised manner. The system increases the safety and efficiency of the robotic operations, reducing the cognitive fatigue of the operator during non-critical mission phases. The integration of such an assistance system is especially important when facing complex (or repetitive) tasks, in order to reduce the work load and accumulated stress of the operator, enhancing the performance and safety of the mission.es_ES
dc.description.sponsorshipThis work has been funded by CERN, Engineering Department, Mechatronics, Robotics and Operations Section.es_ES
dc.language.isoenges_ES
dc.publisherMolecular Diversity Preservation Internationales_ES
dc.relation.isversionofPublisher's versiones_ES
dc.rightsopenAccesses_ES
dc.subjectVisiones_ES
dc.subjectRobotic interventionses_ES
dc.subjectEye-in-handes_ES
dc.subjectTrackinges_ES
dc.subjectHazardous environmentses_ES
dc.subjectRadioactive scenarioses_ES
dc.titleMonocular Robust Depth Estimation Vision System for Robotic Tasks Interventions in Metallic Targetses_ES
dc.typeartículoes_ES
dc.identifier.doihttp://dx.doi.org/10.3390/s19143220-
dc.description.peerreviewedPeer reviewedes_ES
dc.relation.publisherversionhttps://doi.org/10.3390/s19143220es_ES
dc.rights.licensehttp://creativecommons.org/licenses/by/4.0/es_ES
dc.contributor.funderEuropean Organization for Nuclear Researches_ES
dc.relation.csices_ES
oprm.item.hasRevisionno ko 0 false*
dc.contributor.orcidVeiga Almagro, Carlos [0000-0002-5599-1476]es_ES
dc.contributor.orcidCastro, Mario Di [0000-0002-2513-967X]es_ES
dc.contributor.orcidLunghi, Giacomo [0000-0003-2395-2496]es_ES
dc.contributor.orcidMarín Prades, Raúl [0000-0002-2340-4126]es_ES
dc.contributor.orcidSanz Valero, Pedro José [0000-0003-3382-1553]es_ES
dc.contributor.orcidFerre Pérez, Manuel [0000-0003-0030-1551]es_ES
dc.contributor.orcidMasi, Alessandro [0000-0002-9237-3140]es_ES
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