Monocular Robust Depth Estimation Vision System for Robotic Tasks Interventions in Metallic Targets
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Otros documentos de la autoría: Veiga Almagro, Carlos; Di Castro, Mario; Lunghi, Giacomo; Marin, Raul; Sanz, Pedro J; Ferre, Manuel; Masi, Alessandro
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INVESTIGACIONMetadatos
Título
Monocular Robust Depth Estimation Vision System for Robotic Tasks Interventions in Metallic TargetsAutoría
Fecha de publicación
2019Editor
MDPIISSN
1424-8220Cita bibliográfica
VEIGA ALMAGRO, Carlos, et al. Monocular Robust Depth Estimation Vision System for Robotic Tasks Interventions in Metallic Targets. Sensors, 2019, vol. 19, núm. 14, p. 3220Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
https://www.mdpi.com/1424-8220/19/14/3220Versión
info:eu-repo/semantics/publishedVersionPalabras clave / Materias
Resumen
Robotic 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 ... [+]
Robotic 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. [-]
Publicado en
Sensors, 2019, vol. 19, núm. 14, p. 3220Proyecto de investigación
This work has been funded by CERN, Engineering Department, Mechatronics, Robotics and Operations Section.Derechos de acceso
info:eu-repo/semantics/openAccess
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