Multi-robot interfaces and operator situational awareness: Study of the impact of immersion and prediction

Multi-robot missions are a challenge for operators in terms of workload and situational awareness. These operators have to receive data from the robots, extract information, understand the situation properly, make decisions, generate the adequate commands, and send them to the robots. The consequenc...

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Detalles Bibliográficos
Autores: Roldán Gómez, Juan J., Peña-Tapia, Elena, Martín-Barrio, Andrés, Olivares Méndez, Miguel A., Cerro, Jaime del, Barrientos, Antonio
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2017
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/170685
Acceso en línea:http://hdl.handle.net/10261/170685
Access Level:acceso abierto
Palabra clave:Multi-robot
Machine learning
virtual reality
Prediction
immersion
Situational awareness
operator interface
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spelling Multi-robot interfaces and operator situational awareness: Study of the impact of immersion and predictionRoldán Gómez, Juan J.Peña-Tapia, ElenaMartín-Barrio, AndrésOlivares Méndez, Miguel A.Cerro, Jaime delBarrientos, AntonioMulti-robotMachine learningvirtual realityPredictionimmersionSituational awarenessoperator interfaceMulti-robot missions are a challenge for operators in terms of workload and situational awareness. These operators have to receive data from the robots, extract information, understand the situation properly, make decisions, generate the adequate commands, and send them to the robots. The consequences of excessive workload and lack of awareness can vary from inefficiencies to accidents. This work focuses on the study of future operator interfaces of multi-robot systems, taking into account relevant issues such as multimodal interactions, immersive devices, predictive capabilities and adaptive displays. Specifically, four interfaces have been designed and developed: a conventional, a predictive conventional, a virtual reality and a predictive virtual reality interface. The four interfaces have been validated by the performance of twenty-four operators that supervised eight multi-robot missions of fire surveillance and extinguishing. The results of the workload and situational awareness tests show that virtual reality improves the situational awareness without increasing the workload of operators, whereas the effects of predictive components are not significant and depend on their implementation.This work is framed on SAVIER (Situational Awareness Virtual EnviRonment) Project, which is both supported and funded by Airbus Defence & Space. The research leading to these results has received funding from the RoboCity2030-III-CM project (Robótica aplicada a la mejora de la calidad de vida de los ciudadanos. Fase III; S2013/MIT-2748), funded by Programas de Actividades I+D en la Comunidad de Madrid and cofunded by Structural Funds of the EU, and from the DPI2014-56985-R project (Protección robotizada de infraestructuras críticas) funded by the Ministerio de Economía y Competitividad of Gobierno de España. We would like to thank to the students of Technical University of Madrid that took part in the experiments and provided us valuable information.Peer ReviewedMolecular Diversity Preservation InternationalComunidad de MadridConsejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]2018201820172018info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Publisher's versioninfo:eu-repo/semantics/publishedVersionhttp://hdl.handle.net/10261/170685reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Inglés#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#S2013/MIT-2748/RoboCity2030-IIIinfo:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/DPI2014-56985-RSíinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/1706852026-05-22T06:33:51Z
dc.title.none.fl_str_mv Multi-robot interfaces and operator situational awareness: Study of the impact of immersion and prediction
title Multi-robot interfaces and operator situational awareness: Study of the impact of immersion and prediction
spellingShingle Multi-robot interfaces and operator situational awareness: Study of the impact of immersion and prediction
Roldán Gómez, Juan J.
Multi-robot
Machine learning
virtual reality
Prediction
immersion
Situational awareness
operator interface
title_short Multi-robot interfaces and operator situational awareness: Study of the impact of immersion and prediction
title_full Multi-robot interfaces and operator situational awareness: Study of the impact of immersion and prediction
title_fullStr Multi-robot interfaces and operator situational awareness: Study of the impact of immersion and prediction
title_full_unstemmed Multi-robot interfaces and operator situational awareness: Study of the impact of immersion and prediction
title_sort Multi-robot interfaces and operator situational awareness: Study of the impact of immersion and prediction
dc.creator.none.fl_str_mv Roldán Gómez, Juan J.
Peña-Tapia, Elena
Martín-Barrio, Andrés
Olivares Méndez, Miguel A.
Cerro, Jaime del
Barrientos, Antonio
author Roldán Gómez, Juan J.
author_facet Roldán Gómez, Juan J.
Peña-Tapia, Elena
Martín-Barrio, Andrés
Olivares Méndez, Miguel A.
Cerro, Jaime del
Barrientos, Antonio
author_role author
author2 Peña-Tapia, Elena
Martín-Barrio, Andrés
Olivares Méndez, Miguel A.
Cerro, Jaime del
Barrientos, Antonio
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Comunidad de Madrid
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Multi-robot
Machine learning
virtual reality
Prediction
immersion
Situational awareness
operator interface
topic Multi-robot
Machine learning
virtual reality
Prediction
immersion
Situational awareness
operator interface
description Multi-robot missions are a challenge for operators in terms of workload and situational awareness. These operators have to receive data from the robots, extract information, understand the situation properly, make decisions, generate the adequate commands, and send them to the robots. The consequences of excessive workload and lack of awareness can vary from inefficiencies to accidents. This work focuses on the study of future operator interfaces of multi-robot systems, taking into account relevant issues such as multimodal interactions, immersive devices, predictive capabilities and adaptive displays. Specifically, four interfaces have been designed and developed: a conventional, a predictive conventional, a virtual reality and a predictive virtual reality interface. The four interfaces have been validated by the performance of twenty-four operators that supervised eight multi-robot missions of fire surveillance and extinguishing. The results of the workload and situational awareness tests show that virtual reality improves the situational awareness without increasing the workload of operators, whereas the effects of predictive components are not significant and depend on their implementation.
publishDate 2017
dc.date.none.fl_str_mv 2017
2018
2018
2018
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Publisher's version
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/170685
url http://hdl.handle.net/10261/170685
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv #PLACEHOLDER_PARENT_METADATA_VALUE#
#PLACEHOLDER_PARENT_METADATA_VALUE#
S2013/MIT-2748/RoboCity2030-III
info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/DPI2014-56985-R
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Molecular Diversity Preservation International
publisher.none.fl_str_mv Molecular Diversity Preservation International
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
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score 15.811543

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