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Una revisión de los sistemas multi-robot: desafíos actuales para los operadores y nuevos desarrollos de interfaces

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Una revisión de los sistemas multi-robot: desafíos actuales para los operadores y nuevos desarrollos de interfaces

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dc.contributor.author Roldan-Gómez, J. J. es_ES
dc.contributor.author de León Rivas, J. es_ES
dc.contributor.author Garcia-Aunon, P. es_ES
dc.contributor.author Barrientos, A. es_ES
dc.date.accessioned 2020-07-08T10:07:37Z
dc.date.available 2020-07-08T10:07:37Z
dc.date.issued 2020-07-01
dc.identifier.issn 1697-7912
dc.identifier.uri http://hdl.handle.net/10251/147659
dc.description.abstract [ES] Los sistemas multi-robot están experimentando un gran desarrollo en los últimos tiempos, ya que mejoran el rendimiento de las misiones actuales y permiten realizar nuevos tipos de misiones. Este artículo analiza el estado del arte de los sistemas multi-robot, abordando un conjunto de temas relevantes: misiones, flotas, operadores, interacción humano-sistema e interfaces. La revisión se centra en los retos relacionados con factores humanos como la carga de trabajo o la conciencia de la situación, así como en las propuestas de interfaces adaptativas e inmersivas para solucionarlos. es_ES
dc.description.abstract [EN] Multi-robot systems are experiencing great development in recent times, since they are improving the performance of current missions and allowing new types of missions. This article analyzes the state of the art of multi-robot systems, addressing a set of relevant topics: missions, fleets, operators, human-system interaction and interfaces. The review focuses on the challenges related to human factors such as workload and situational awareness, as well as the proposals of adaptive and immersive interfaces to solve them. es_ES
dc.description.sponsorship Esta investigación ha recibido fondos de los proyectos SAVIER (Situational Awareness VIrtual EnviRonment) de Airbus; RoboCity2030-DIH-CM, Madrid Robotics Digital Innovation Hub, S2018/ NMT-4331, financiado por los Programas de Actividades I+D de la Comunidad de Madrid y confinanciado por los Fondos Estructurales de la UE; y DPI2014-56985-R (Protección Robotizada de Infraestructuras Críticas) financiado por el ministerio de Economía y Competitividad del Gobierno de España. es_ES
dc.language Español es_ES
dc.publisher Universitat Politècnica de València es_ES
dc.relation.ispartof Revista Iberoamericana de Automática e Informática industrial es_ES
dc.rights Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) es_ES
dc.subject Robotics es_ES
dc.subject Robots es_ES
dc.subject Operators es_ES
dc.subject Interfaces es_ES
dc.subject Man-Machine Interaction es_ES
dc.subject Robótica es_ES
dc.subject Operadores es_ES
dc.subject Interacción Humano-Máquina es_ES
dc.title Una revisión de los sistemas multi-robot: desafíos actuales para los operadores y nuevos desarrollos de interfaces es_ES
dc.title.alternative A review on multi-robot systems: current challenges for operators and new developments of interfaces es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.4995/riai.2020.13100
dc.relation.projectID info:eu-repo/grantAgreement/CAM//S2018%2FNMT-4331/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//DPI2014-56985-R/ES/PROTECCION ROBOTIZADA DE INFRAESTRUCTURAS CRITICAS/ es_ES
dc.rights.accessRights Abierto es_ES
dc.description.bibliographicCitation Roldan-Gómez, JJ.; De León Rivas, J.; Garcia-Aunon, P.; Barrientos, A. (2020). Una revisión de los sistemas multi-robot: desafíos actuales para los operadores y nuevos desarrollos de interfaces. Revista Iberoamericana de Automática e Informática industrial. 17(3). https://doi.org/10.4995/riai.2020.13100 es_ES
dc.description.accrualMethod OJS es_ES
dc.relation.publisherversion https://doi.org/10.4995/riai.2020.13100 es_ES
dc.description.upvformatpfin 305 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 17 es_ES
dc.description.issue 3 es_ES
dc.identifier.eissn 1697-7920
dc.relation.pasarela OJS\13100 es_ES
dc.contributor.funder Airbus Defense and Space es_ES
dc.contributor.funder Comunidad de Madrid es_ES
dc.contributor.funder European Commission es_ES
dc.contributor.funder Ministerio de Economía y Competitividad es_ES
dc.description.references Abbadi, A. and Prenosil., 2015. Safe path planning using cell decomposition approximation. Distance Learning, Simulation and Communication, 8. es_ES
dc.description.references Adams, B. and Suykens, F., 2013 Astute: Increased Situational Awareness through proactive decision support and adaptive map-centric user interfaces. 2013 IEEE European Intelligence and Security Informatics Conference (EISIC), 289-293. https://doi.org/10.1109/EISIC.2013.74 es_ES
dc.description.references Almeida, L., Menezes, P. and Dias, J., 2017. Improving robot teleoperation experience via immersive interfaces. In 2017 4th IEEE Experiment@ International Conference (exp. at'17), 87-92. https://doi.org/10.1109/EXPAT.2017.7984414 es_ES
dc.description.references Arnold, K. P., 2016. The UAV Ground Control Station: Types, Components, Safety, Redundancy, and Future Applications. International Journal of Unmanned Systems Engineering., 4(1), 37. es_ES
dc.description.references Ayaz, H., Shewokis, P. A., Bunce, S., Izzetoglu, K., Willems, B. and Onaral, B., 2012. Optical brain monitoring for operator training and mental workload assessment. Neuroimage, 59(1), 36-47. https://doi.org/10.1016/j.neuroimage.2011.06.023 es_ES
dc.description.references Beer, J., Fisk, A. D. and Rogers, W. A., 2014. Toward a framework for levels of robot autonomy in human-robot interactions. Journal of Human-Robot Interaction, 3(2), 74. https://doi.org/10.5898/JHRI.3.2.Beer es_ES
dc.description.references Bourguet, M. L., 2003. Designing and Prototyping Multimodal Commands. Interact, 3, 717-720. es_ES
dc.description.references Brutschy, A., Pini, G., Pinciroli, C., Birattari, M. and Dorigo, M., 2014. Self-organized task allocation to sequentially interdependent tasks in swarm robotics. Autonomous agents and multi-agent systems, 28(1), 101-125. https://doi.org/10.1007/s10458-012-9212-y es_ES
dc.description.references Cantelli, L., Mangiameli, M., Melita, C. D. and Muscato, G., 2013. UAV/UGV cooperation for surveying operations in humanitarian demining. 2013 IEEE international symposium on safety, security, and rescue robotics (SSRR),1-6). https://doi.org/10.1109/SSRR.2013.6719363 es_ES
dc.description.references Chang, H. and Jin, T., 2013. Command fusion based fuzzy controller design for moving obstacle avoidance of mobile robot. Future information communication technology and applications, Springer, 905-913. https://doi.org/10.1007/978-94-007-6516-0_99 es_ES
dc.description.references Chen, J. Y. C., Haas, E. C. and Barnes, M. J., 2007. Human performance issues and user interface design for teleoperated robots. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 37(6), 1231-1245. https://doi.org/10.1109/TSMCC.2007.905819 es_ES
dc.description.references Chen, J. Y. C., Barnes, M. J. and Harper-Sciarini, M., 2011. Supervisory control of multiple robots: Human-performance issues and user-interface design. IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications an Reviews), 41(4), 435-454. https://doi.org/10.1109/TSMCC.2010.2056682 es_ES
dc.description.references Clark, C. M., 2005. Probabilistic road map sampling strategies for multi-robot motion planning. Robotics and Autonomous Systems, 53(3), 244-264. https://doi.org/10.1016/j.robot.2005.09.002 es_ES
dc.description.references Cummings, M. L., Bruni, S., Mercier, S. and Mitchell, P. J., 2007. Automation architecture for single operator, multiple UAV command and control. Tech. Rep DTIC Document. es_ES
dc.description.references Cummings, M. L. and Mitchell P. J., 2008. Predicting controller capacity in supervisory control of multiple UAVs. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, 38(2), 451-460. https://doi.org/10.1109/TSMCA.2007.914757 es_ES
dc.description.references Cummings, M. L., Mastracchio, C., Thornburg, K. M. and Mkrtchyan, A., 2013. Boredom and distraction in multiple unmanned vehicle supervisory control. Interacting with computers, 25(1), 34-47. https://doi.org/10.1093/iwc/iws011 es_ES
dc.description.references De Cubber, G., Doroftei, D., Serrano, D., Chintamani, K., Sabino, R. and Ourevitch, S., 2013. The EU-ICARUS project: developing assistive robotic tools for search and rescue operations. 2013 IEEE international symposium on safety, security, and rescue robotics (SSRR), 1-4. https://doi.org/10.1109/SSRR.2013.6719323 es_ES
dc.description.references De Greeff, J., Hindriks, K., Neerincx, M. A. and Kruijff-Korbayova, I., 2015. Human-robot teamwork in USAR environments: the TRADR project. Proceedings of the Tenth Annual ACM/IEEE International Conference on Human-Robot Interaction Extended Abstracts, pp. 151-152. https://doi.org/10.1145/2701973.2702031 es_ES
dc.description.references Dezfoulian, S. H., Wu, D. and Ahmad, I. S., 2013. A generalized neural network approach to mobile robot navigation and obstacle avoidance. Intelligent Autonomous Systems, Springer, 12, 25-52. https://doi.org/10.1007/978-3-642-33926-4_3 es_ES
dc.description.references Di, B., Zhou, R. and Duan, H., 2015. Potential field based receding horizon motion planning for centrality-aware multiple UAV cooperative surveillance. Aerospace Science and Technology, 46, 386-397. https://doi.org/10.1016/j.ast.2015.08.006 es_ES
dc.description.references Dixon, S. R., Wickens, C. D. and Chang, D, 2005. Mission control of multiple unmanned aerial vehicles: A workload analysis. Human Factors: The Journal of the Human Factors and Ergonomics Society 47(3), 479-487. https://doi.org/10.1518/001872005774860005 es_ES
dc.description.references Donmez, B., Nehme, C. and Cummings, M.L., 2010. Modeling workload impact in multiple unmanned vehicle supervisory control. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, 40(6), 1180-1190. https://doi.org/10.1109/TSMCA.2010.2046731 es_ES
dc.description.references Drury, J. L., Scholtz, J. and Yanco, H.A., 2003. Awareness in human-robot interactions. IEEE International Conference on Systems, Man and Cybernetics, 1, 912-918. es_ES
dc.description.references Drury, J. L., Riek, L. and Rackliffe, N., 2006A. A decomposition of UAV-related situation awareness. Proceedings of the 1st ACM SIGCHI/SIGART conference on Human-robot interaction, 88-94. https://doi.org/10.1145/1121241.1121258 es_ES
dc.description.references Drury, J. L., Richer, J., Rackliffe, N. and Goodrich, M. A., 2006B. Comparing situation awareness for two unmanned aerial vehicle human interfaces approaches. Technical rpeort, Mitre Corp Bedford MA. es_ES
dc.description.references Endsley, M. R., 1988A. Design and evaluation for situation awareness enhancement. Proceedings of the human factors and ergonomics society annual meeting, SAGE Publications, 32(2), 97-101. https://doi.org/10.1177/154193128803200221 es_ES
dc.description.references Endsley, M. R., 1988B. Situation awareness global assessment technique (SAGAT). Proceedings of the IEEE 1988 National Aerospace and Electronics Conference (NAECON), 789-795. es_ES
dc.description.references Endsley, M. R. and Garland, D. J., 2000. Situation awareness analysis and measurement. CRC Press. https://doi.org/10.1201/b12461 es_ES
dc.description.references Endsley M. R., 1999. Level of automation effects on performance, situation awareness and workload in a dynamic control task. Ergonomics, 42(3), 462-492. https://doi.org/10.1080/001401399185595 es_ES
dc.description.references Flushing, E. F., Gambardella, L. and Di Caro, G. A., 2012. Gis-based mission support system for wilderness search and rescue with heterogeneous agents. Proc 2nd Workshop on robots and sensors integration in future rescue INformation system (ROSIN), IEEE/RSJ Int Conference on Intelligent Robots and Systems (IROS). es_ES
dc.description.references Foit, K., 2014. Mixed reality as a tool supporting programming of the robot. Advanced Materials Research, Trans Tech Publications, 1036, 737-742. https://doi.org/10.4028/www.scientific.net/AMR.1036.737 es_ES
dc.description.references Frische, F. and Lüdtke, A., 2013. SA-tracer: A tool for assessment of UAV swarm operator SA during mission execution. 2013 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA), 203-211. https://doi.org/10.1109/CogSIMA.2013.6523849 es_ES
dc.description.references Fuchs, C., Borst, C., de Croon, G. C., Van Paassen, M. M. and Mulder, M., 2014. An ecological approach to the supervisory control of UAV swarms. International Journal of Micro Air Vehicles, 6(4), 211-229. https://doi.org/10.1260/1756-8293.6.4.211 es_ES
dc.description.references Galceran, E. and Carreras, M., 2013. A survey on coverage path planning for robotics. Robotics and Autonomous Systems, 61(12), 1258-1276. https://doi.org/10.1016/j.robot.2013.09.004 es_ES
dc.description.references García, J. C., Patrão, B., Pérez, J., Seabra, J., Menezes, P., Dias, J. and Sanz, P.J., 2015. Towards an immersive and natural gesture controlled interface for intervention underwater robots. IEEE OCEANS 2015-Genova, 1-5. https://doi.org/10.1109/OCEANS-Genova.2015.7271501 es_ES
dc.description.references García, S. E., Slawiñski, E., Mut, V., and Penizzotto, F., 2018. Collision avoidance method for multi-operator multi-robot teleoperation system. Robotica, 36(1), 78-95. https://doi.org/10.1017/S0263574717000169 es_ES
dc.description.references Garzón, M., Valente, J., Zapata, D. and Barrientos, A., 2013. An aerial-ground robotic system for navigation and obstacle mapping in large outdoor areas. Sensors, 13(1), 1247-1267. https://doi.org/10.3390/s130101247 es_ES
dc.description.references Garzón, M., Valente, J., Roldán, J. J., Cancar, L., Barrientos, A. and Del Cerro, J., 2016. A multirobot system for distributed area coverage and signal searching in large outdoor scenarios. Journal of Field Robotics, 33(8), 1087-1106. https://doi.org/10.1002/rob.21636 es_ES
dc.description.references Garzón, M., Valente, J., Roldán, J. J., Garzón-Ramos, D., de León, J., Barrientos, A. and del Cerro, J., 2017. Using ros in multi-robot systems: Experiences and lessons learned from real-world field tests. In Robot Operating System (ROS), Springer, Cham, 449-483. https://doi.org/10.1007/978-3-319-54927-9_14 es_ES
dc.description.references Goerzen, C., Kong, Z. and Mettler, B., 2009. A survey of motion planning algorithms from the perspective of autonomous UAV guidance. Selected papers from the 2nd International Symposium on UAVs, Reno, Nevada, USA, Springer, 64-100. https://doi.org/10.1007/978-90-481-8764-5_5 es_ES
dc.description.references Goodrich, M. A. and Schultz, A. C., 2007. Human-robot interaction: a survey. Foundations and trends in human-computer interaction, 1(3), 203-275. https://doi.org/10.1561/1100000005 es_ES
dc.description.references Gregory, J., Fink, J., Stump, E., Twigg, J., Rogers, J., Baran, D., Fung, N. and Young, S., 2016. Application of multi-robot systems to disaster-relief scenarios with limited communication. In Field and Service Robotics, Springer, Cham, 639-653. https://doi.org/10.1007/978-3-319-27702-8_42 es_ES
dc.description.references Haas, E. C., Pillalamarri, K., Stachowiak, C. C. and Fields, M., 2011. Multimodal controls for soldier/swarm interaction. IEEE RO-MAN, 223-228. https://doi.org/10.1109/ROMAN.2011.6005227 es_ES
dc.description.references Hagiwara, Y., 2015. Cloud based VR system with immersive interfaces to collect multimodal data in human-robot interaction. 2015 IEEE 4th Global Conference on Consumer Electronics (GCCE), 256-259. https://doi.org/10.1109/GCCE.2015.7398709 es_ES
dc.description.references Hart, S. G. and Staveland E.L., 1988. Development of NASA-TLX (Task Load Index): Results of empirical and theoretical research. Advances in psychology, 52, 139-183. https://doi.org/10.1016/S0166-4115(08)62386-9 es_ES
dc.description.references Hart, S. G., 2006. NASA-task load index (NASA-TLX); 20 years later. Proceedings of the human factors and ergonomics society annual meeting, Sage Publications Sage CA, Los Angeles, CA, 50(9), 904-908. https://doi.org/10.1177/154193120605000909 es_ES
dc.description.references Hobbs, A. and Herwitz, S. R., 2014. Human factors in the maintenance of unmanned aerial vehicle (UAV) swarm management. Applied Ergonomics, 58, 66-80. https://doi.org/10.1016/j.apergo.2016.05.011 es_ES
dc.description.references Hocraffer, A. and Nam, C. S. A meta-analysis of human-system interfaces in unmanned aerial vehicle (UAV) swarm management. Applied Ergonomics, 58, 66-80. https://doi.org/10.1016/j.apergo.2016.05.011 es_ES
dc.description.references Hong, A., 2016. Human-Robot Interactions for Single Robots and Multi-Robot Teams. PhD thesis, Department of Mechanical and Industrial Engineering, University of Toronto. es_ES
dc.description.references Janchiv, A., Batsaikhan, D., hwan Kim, G. and Lee, S. G., 2011. Complete coverage path planning for multi-robots based on. 2011 11th IEEE International Conference on Control, Automation and Systems, 824-827. es_ES
dc.description.references Jasper, P., Sibley, C. and Coyne, J. Using Heart Rate Variability to Assess Operator Mental Workload in a Command and Control Simulation of Multiple Unmanned Aerial Vehicles. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, SAGE Publications Sage CA, Los Angeles, CA, 60(1), 1125-1129. https://doi.org/10.1177/1541931213601264 es_ES
dc.description.references Jia, X. and Meng, M. Q. H., 2013. A survey and analysis of task allocation algorithms in multi-robot systems. 2013 IEEE International Conference on Robotics and biomimetics (ROBIO), 2280-2285. https://doi.org/10.1109/ROBIO.2013.6739809 es_ES
dc.description.references Jiang, Y., 2016. A survey of task allocation and load balancing in distributed systems. IEEE Transactions on Parallel and Distributed Systems, 27(2), 585-599. https://doi.org/10.1109/TPDS.2015.2407900 es_ES
dc.description.references Johannsmeier, L. and Haddadin, S., 2016. A hierarchical human-robot interaction-planning framework for task allocation in collaborative industrial assembly processes. IEEE Robotics and Automation Letters, 2(1), 41-48. https://doi.org/10.1109/LRA.2016.2535907 es_ES
dc.description.references Kapoutsis, A. C., Chatzichristofis, S. A., Doitsidis, L., de Sousa, J. B., Pinto, J., Braga, J. and Kosmatopoulos, E. B., 2016. Real-time adaptive multi-robot exploration with application to underwater map construction. Autonomous robots, 40(6), 987-1015. https://doi.org/10.1007/s10514-015-9510-8 es_ES
dc.description.references Kavitha, S., Veena, S. and Kumaraswamy, R., 2015. Development of automatic speech recognition system for voice activated Ground Control system. 2015 IEEE International Conference on Trends in Automation, Communications and Computing Technology (I-TACT-15), pp. 1-5. https://doi.org/10.1109/ITACT.2015.7492684 es_ES
dc.description.references Khaleghi, A. M., Xu, D., Minaeian, S., Li, M., Yuan, Y., Liu, J., Son, Y. J., Vo, C., Mousavian, A. and Lien, J. M., 2014. A comparative study of control architectures in UAV/UGV-based surveillance system. Proceedings of the IIE Annual Conference, Institute of Industrial and Systems Engineers (IISE), 3455. es_ES
dc.description.references Khamis, A., Hussein, A. and Elmogy, A., 2015. Multi-robot Task Allocation: A Review of the State-of-the-Art. Cooperative Robots and Sensor Networks, Springer, 31-51. https://doi.org/10.1007/978-3-319-18299-5_2 es_ES
dc.description.references Kirchner, E. A., Kim, S. K., Tabie, M., Wöhrle, H., Maurus, M. and Kirchner, F., 2016. An intelligent man-machine interface - Multi-robot control adapted for task engagement based on single-trial detectability of P300. Frontiers in human neuroscience, 10, 291. https://doi.org/10.3389/fnhum.2016.00291 es_ES
dc.description.references Kolling, A., Nunnally, S. and Lewis, M., 2012. Towards human control of robot swarms. Proceedings of the seventh annual ACM/IEEE international conference on human-robot interaction, 89-96. https://doi.org/10.1145/2157689.2157704 es_ES
dc.description.references Kothari, M., Postlethwaite, I. and Gu, D. W. Multi-UAV path planning in obstacle rich environment using rapidly-exploring random trees. Proceedings of the 48 IEEE Conference on Decision and Control, 3069-3074. es_ES
dc.description.references Kruijff-Korbayová, I., Colas, F., Gianni, M., Pirri, F., de Greeff, J., Hindriks, K., Neerincx, M., Ögren, P., Svoboda, T. and Worst, R., 2015. Tradr project: Long-term human-robot teaming for robot assisted disaster response. KI-Künstliche Intelligenz, 29(2), 193-201. https://doi.org/10.1007/s13218-015-0352-5 es_ES
dc.description.references Kurniawan, H., Maslov, A. V. and Pechenizkiy, M., 2013. Stress detection from speech and galvanic skin response signals. IEEE 26th International Symposium on Computer-Based Medical Systems (CBMS), 209-214. https://doi.org/10.1109/CBMS.2013.6627790 es_ES
dc.description.references Lang, R. G., da Silva, I. N., Romero, R. A. F., 2014. Development of distributed control architecture for multi-robot systems. IEEE 2014 Joint Conference on Robotics: SBR-LARS Robotics Symposium and Robocontrol, 163-168. https://doi.org/10.1109/SBR.LARS.Robocontrol.2014.49 es_ES
dc.description.references Larochelle, B., Kruijff, G. J. M., Smets, N., Mioch, T. and Groenewegen, P., 2011. Establishing human situation awareness using a multi-modal operator control unit in an urban search & rescue human-robot team, IEEE, 229-234. https://doi.org/10.1109/ROMAN.2011.6005237 es_ES
dc.description.references Lesire, C., Infantes, G., Gateau, T. and Barbier, M., 2016. A distributed architecture for supervision of autonomous multi-robot missions. Autonomous Robots, 40(7), 1343-1362. https://doi.org/10.1007/s10514-016-9603-z es_ES
dc.description.references Lindemuth, M., Murphy, R., Steimle, E., Armitage, W., Dreger, K., Elliot, T., Hall, M., Kalyadin, D., Kramer, J., Palankar, M. and Pratt, K., 2011. Sea robot-assisted inspection. IEEE robotics & automation magazine, 18(2), 96-107. https://doi.org/10.1109/MRA.2011.940994 es_ES
dc.description.references Lysaght, R. J., 1989. Operator workload: Comprehensive review and evaluation of operator workload methodologies. Tech. Rep. DTIC Document. https://doi.org/10.21236/ADA212879 es_ES
dc.description.references Mantecón, T., del Blanco, C. R., Jaureguizar, F. and García, N., 2014. New generation of human machine interfaces for controlling UAV through depth-based gesture recognition. Unmanned Systems Technology XVI, International Society for Optics and Photonics, 9084. https://doi.org/10.1117/12.2053244 es_ES
dc.description.references Marino, A., Parker, L. E., Antonelli, G. and Caccavale, F., 2013. A decentralized architecture for multi-robot systems based on the null-space-behavioral control with application to multi-robot border patrolling. Journal of Intelligent & Robotic Systems, 71(3-4), 423-444. https://doi.org/10.1007/s10846-012-9783-5 es_ES
dc.description.references Martín-Barrio, A., Terrile, S., Barrientos, A. and del Cerro, J., 2018. Hyper-Redundant Robots: Classification, State-of-the-Art and Issues. Revista Iberoamericana de Automática e Informática Industrial, 15(4), 351-362. https://doi.org/10.4995/riai.2018.9207 es_ES
dc.description.references Martín-Barrio, A., Roldán, J. J., Terrile, S., del Cerro, J. and Barrientos, A., 2019. Application of Immersive Technologies and Natural Language to Hyper-Redundant Robot Teleoperation. Virtual Reality, 1-15. https://doi.org/10.1007/s10055-019-00414-9 es_ES
dc.description.references Martins, H., Oakley, I. and Ventura, R., 2015. Design and evaluation of a head-mounted display for immersive 3D teleoperation of field robots. Robotica, 33(10), 2166-2185. https://doi.org/10.1017/S026357471400126X es_ES
dc.description.references Matellán, V. and Borrajo, D., 2001. ABC2 an agenda based multi-agent model for robots control and cooperation. Journal of Intelligent & Robotic Systems, 32(1), 93-114. https://doi.org/10.1023/A:1012009429991 es_ES
dc.description.references McCarley, J.S. and Wickens, C. D., 2005. Human factors implications of UAVs in the national airspace. University of Illinois at Urbana-Champaign, Aviation Human Factors Division. es_ES
dc.description.references McDuff, D., Gontarek, S. and Picard, R., 2014. Remote measurement of cognitive stress via heart rate variability. 36th Annual International Conference on the IEEE Engineering in Medicine and Biology Society (EMBC), 2957-2960. https://doi.org/10.1109/EMBC.2014.6944243 es_ES
dc.description.references Menda, J., Hing, J. T., Ayaz, H., Shewokis, P. A., Izzetoglu, K., Onaral, B. and Oh, P., 2011. Optical brain imaging to enhance UAV operator training, evaluation, and interface development. Journal of intelligent & robotic systems, 61(1-4), 423-443. https://doi.org/10.1007/s10846-010-9507-7 es_ES
dc.description.references Monajjemi, V. M., Pourmehr, S., Sadat, S. A., Zhan, F., Wawerla, J., Mori, G. and Vaughan, R., 2014. Integrating multi-modal interfaces to command UAVs. Proceedings of the 2014 ACM/IEEE international conference on Human-robot interaction, 106-106. https://doi.org/10.1145/2559636.2559646 es_ES
dc.description.references Moore, J., Wolfe, K. C., Johannes, M. S., Katyal, K. D., Para, M. P., Murphy, R. J., Hatch, J., Taylor, C. J., Bamberger, R. J. and Tunstel, E., 2016. Nested marsupial robotic system for search and sampling in increasingly constrained environments. 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2279-2286 https://doi.org/10.1109/SMC.2016.7844578 es_ES
dc.description.references Mosteo, A. R. and Montano, L., 2010. A survey of multi-robot task allocation. Technical Report No. AMI-009-10-TEC, Instituto de Investigación en Ingeniería de Aragón, University of Zaragoza, Zaragoza, Spain. es_ES
dc.description.references Murphy, R. R., 2004. Human-robot interaction in rescue robotics. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 34(2), 138-153. https://doi.org/10.1109/TSMCC.2004.826267 es_ES
dc.description.references Nagi, J., Giusti, A., Di Caro, G. A. and Gambardella, L. M., 2014. Human control of UAVs using face pose estimates and hand gestures. 2014 9th ACM/IEEE International Conference on Human-Robot Interaction (HRI), 1-2. https://doi.org/10.1145/2559636.2559644 es_ES
dc.description.references Nam, C. S., Johnson, S., Li, Y. and Seong, Y., 2009. Evaluation of human-agent user interfaces in multi-agent systems. International Journal of Industrial Ergonomics, 39(1), 192-201. https://doi.org/10.1016/j.ergon.2008.08.008 es_ES
dc.description.references Nestmeyer, T., Giordano, P. R., Bülthoff, H. H. and Franchi, A., 2017. Decentralized simultaneous multi-target exploration using a connected network of multiple robots. Autonomous Robots, 41(4), 989-1011. https://doi.org/10.1007/s10514-016-9578-9 es_ES
dc.description.references Oleiwi, B. K., Al-Jarrah, R., Roth, H. and Kazem, B. I., 2014. Multi objective optimization of trajectory planning of non-holonomic mobile robot in dynamic environment using enhanced GA by fuzzy motion control and A*. International Conference on Neural Networks and Artificial Intelligence, Springer, Cham, 34-49. https://doi.org/10.1007/978-3-319-08201-1_5 es_ES
dc.description.references Olson, W. A. and Sarter, N. B., 2000. Automation management strategies: Pilot preferences and operational experiences. The International Journal of Aviation Psychology, 10(4), 327-341. https://doi.org/10.1207/S15327108IJAP1004_2 es_ES
dc.description.references Parasuraman, R., Sheridan, T. B. and Wickens, C. D., 2000. A model for types and levels of human interaction with automation. IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans, 30(3), 286-297. https://doi.org/10.1109/3468.844354 es_ES
dc.description.references Pedrotti, M., Mirzaei, M. A., Tedesco, A., Chardonnet, J. R., Mérienne, F., Benedetto, S. and Baccino, T., 2014. Automatic stress classification with pupil diameter analysis. International Journal of Human-Computer Interaction, 30(3), 220-236. https://doi.org/10.1080/10447318.2013.848320 es_ES
dc.description.references Peppoloni, L., Brizzi, F., Avizzano, C. A. and Ruffaldi, E., 2015. Immersive ROS-integrated framework for robot teleoperation. 2015 IEEE Symposium on 3D Interfaces (3DUI), 177-178. https://doi.org/10.1109/3DUI.2015.7131758 es_ES
dc.description.references Ramirez-Atencia, C., Bello-Orgaz, G., R-Moreno, M. D. and Camacho, D., 2015. Performance evaluation of multi-uav cooperative mission planning models. Computational Collective Intelligence, Springer, Cham, 203-212. https://doi.org/10.1007/978-3-319-24306-1_20 es_ES
dc.description.references Ramirez-Atencia, C., Bello-Orgaz, G., R-Moreno, M. D. and Camacho, D., 2017. Solving complex multi-UAV mission planning problems using multi-objective genetic algorithms. Soft Computing, 21(17), 4883-4900. https://doi.org/10.1007/s00500-016-2376-7 es_ES
dc.description.references Recchiuto, C. T., Sgorbissa, A. and Zaccaria, R., 2016. Visual feedback with multiple cameras in a UAVs Human-Swarm Interface. Robotics and Autonomous Systems, 80, 43-54. https://doi.org/10.1016/j.robot.2016.03.006 es_ES
dc.description.references Rodríguez-Fernández, V., Menéndez, H. D. and Camacho, D., 2016. Automatic profile generation for uav operators using a simulation-based training environment. Progress in Artificial Intelligence, 5(1), 37-46. https://doi.org/10.1007/s13748-015-0072-y es_ES
dc.description.references Roldán, J. J., Garcia-Aunon, P., Garzón, M., de León, J., del Cerro, J. and Barrientos, A., 2016A. Heterogeneous multi-robot system for mapping environmental variables of greenhouses. Sensors, 16(7), 1018. https://doi.org/10.3390/s16071018 es_ES
dc.description.references Roldán, J. J., Lansac, B., del Cerro, J. and Barrientos, A., 2016B. A proposal of multi-UAV mission coordination and control architecture. Robot 2015: Second Iberian robotics conference, Springer, Cham, 597-608. https://doi.org/10.1007/978-3-319-27146-0_46 es_ES
dc.description.references Roldán, J. J., del Cerro, J. D. and Barrientos, A., 2016C. Multiple Robots, Single Operator: Considerations About Information and Commanding, RoboCity16: Open Conference on Future Trends in Robotics, 259-266. es_ES
dc.description.references Roldán, J. J., Peña-Tapia, E., Martín-Barrio, A., Olivares-Méndez, M. A., del Cerro, J. and Barrientos, A., 2017. Multi-robot interfaces and operator situational awareness: Study of the impact of immersion and prediction. Sensors, 17(8), 1720. https://doi.org/10.3390/s17081720 es_ES
dc.description.references Roldán, J. J., Olivares-Méndez, M. A., del Cerro, J. and Barrientos, A., 2018A. Analyzing and improving multi-robot missions by using process mining. Autonomous Robots, 42(6), 1187-1205. https://doi.org/10.1007/s10514-017-9686-1 es_ES
dc.description.references Roldán, J. J., Del Cerro, J. and Barrientos, A., 2018B. Should We Compete or Should We Cooperate? Applying Game Theory to Task Allocation in Drone Swarms. 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 5366-5371. es_ES
dc.description.references Roldán, J. J., Peña-Tapia, E., Garzón-Ramos, D., de León, J., Garzón, M., del Cerro, J. and Barrientos, A., 2019A. Multi-robot Systems, Virtual Reality and ROS: Developing a New Generation of Operator Interfaces. Robot Operating System (ROS), Springer, Cham, 29-64. https://doi.org/10.1007/978-3-319-91590-6_2 es_ES
dc.description.references Roldán, J. J., Peña-Tapia, E., García-Aunon, P., del Cerro, J. and Barrientos, A., 2019B. Bringing Adaptive and Immersive Interfaces to Real-World Multi-Robot Scenarios: Application to Surveillance and Intervention in Infrastructures. IEEE Access, 7, 86319-86335. https://doi.org/10.1109/ACCESS.2019.2924938 es_ES
dc.description.references Roldán, J. J., Díaz-Maroto, V., Real, J., Palafox, P. R., Valente, J., Garzón, M. and Barrientos, A., 2019C. Press Start to Play: Classifying Multi-Robot Operators and Predicting Their Strategies through a Videogame. Robotics, 8(3), 53. https://doi.org/10.3390/robotics8030053 es_ES
dc.description.references Román-Ibáñez, V., Pujol-López, F. A., Mora-Mora, H., Pertegal-Felices, M. L. and Jimeno-Morenilla, A., 2018. A low-cost immersive virtual reality system for teaching robotic manipulators programming. Sustainability, 10(4), 1102. https://doi.org/10.3390/su10041102 es_ES
dc.description.references Rosen, E., Whitney, D., Phillips, E., Ullman, D. and Tellex, S., 2018. Testing robot teleoperation using a virtual reality interface with ROS reality. Proceedings of the 1st International Workshop on Virtual, Augmented, and Mixed Reality for HRI (VAM-HRI), 1-4. es_ES
dc.description.references Ruano, S., Cuevas, C., Gallego, G. and García, N., 2017. Augmented reality tool for the situational awareness improvement of UAV operators. Sensors, 17(2), 297. https://doi.org/10.3390/s17020297 es_ES
dc.description.references Ruiz, J. J., Viguria, A., Martinez-de-Dios, J. R. and Ollero, A. Immersive displays for building spatial knowledge in multi-UAV operations. 2015 IEEE International Conference on Unmanned Aircraft Systems (ICUAS), 1043-1048. https://doi.org/10.1109/ICUAS.2015.7152395 es_ES
dc.description.references Ruff, H. A., Narayanan, S. and Draper, M. H., 2002. Human interaction with levels of automation and decision-aid fidelity in the supervisory control of multiple simulated unmanned air vehicles. Presence: Teleoper Virtual Environ., 11(4), 335-351. https://doi.org/10.1162/105474602760204264 es_ES
dc.description.references Sampedro, C., Bavle, H., Sanchez-Lopez, J. L., Fernández, R. A. S., Rodríguez-Ramos, A., Molina, M. and Campoy, P., 2016. A flexible and dynamic mission planning architecture for uav swarm coordination. 2016 IEEE International Conference on Unmanned Aircraft Systems (ICUAS), 355-363. https://doi.org/10.1109/ICUAS.2016.7502669 es_ES
dc.description.references Scheggi, S., Aggravi, M., Morbidi, F. and Prattichizzo, D., 2014. Cooperative human-robot haptic navigation. 2014 IEEE International Conference on Robotics and Automation (ICRA), 2693-2698. https://doi.org/10.1109/ICRA.2014.6907245 es_ES
dc.description.references Schneider, E., Sklar, E. I., Parsons, S. and Özgelen, A. T., 2015. Auction-based task allocation for multi-robot teams in dynamic environments. Conference Towards Autonomous Robotic Systems, Springer, Cham, 246-257. https://doi.org/10.1007/978-3-319-22416-9_29 es_ES
dc.description.references Scholtz, J., 2003. Theory and evaluation of human robot interactions. Proceedings of the 36th Annual Hawaii International Conference on System Sciences, IEEE, 10. https://doi.org/10.1109/HICSS.2003.1174284 es_ES
dc.description.references Scholtz, J., Young, J., Drury, J. L. and Yanco, H. A., 2004. Evaluation of human-robot interaction awareness in search and rescue. Proceedings of the IEEE International Conference on Robotics and Automation 2004 (ICRA'04), 3, 2327-2332. https://doi.org/10.1109/ROBOT.2004.1307409 es_ES
dc.description.references Schultze-Kraft, M., Dähne, S., Gugler, M., Curio, G. and Blankertz, B., 2016. Unsupervised classification of operator workload from brain signals. Journal of neural engineering, 13(3), 036008. https://doi.org/10.1088/1741-2560/13/3/036008 es_ES
dc.description.references Sheridan, T. B. and Verplank, W. L., 1978. Human and computer control of undersea teleoperators. Tech. rep. DTIC Document. https://doi.org/10.21236/ADA057655 es_ES
dc.description.references Sheridan, 2002. Humans and automation: System design and research issues. John Wiley & Sons. es_ES
dc.description.references Shimizu, M. and Takahashi, T., 2013. Training platform for rescue robot operation and pair operations of multi-robots. Advanced Robotics, 27(5), 385-391. https://doi.org/10.1080/01691864.2013.763744 es_ES
dc.description.references Simpson, B. D., Bolia, R. S. and Draper, M. H., 2013. Spatial audio display concepts supporting situation awareness for operators of unmanned aerial vehicles. Human Performance, Situation Awareness, and Automation: Current Research and Trends HPSAA II, Volumes I and II, 2, 61. es_ES
dc.description.references Slawinski, E., Mut, V. A., Fiorini, P. and Salinas, L. R., 2011. Quantitative absolute transparency for bilateral teleoperation of mobile robots. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, 42(2), 430-442. https://doi.org/10.1109/TSMCA.2011.2159588 es_ES
dc.description.references Soares, J., Vale, A. and Ventura, R., 2015. A multi-purpose rescue vehicle and a human-robot interface architecture for remote assistance in ITER. Fusion Engineering and Design, 98, 1656-1659. https://doi.org/10.1016/j.fusengdes.2015.06.148 es_ES
dc.description.references Teichteil-Königsbuch, F. and Fabiani, P., 2007. A multi-thread decisional architecture for real-time planning under uncertainty. 3rd ICAPS'07 Workshop on Planning and Plan Execution for Real-World Systems. es_ES
dc.description.references Tsokas, N. A. and Kyriakopoulos, K. J., 2012. Multi-robot multiple hypothesis tracking for pedestrian tracking. Autonomous Robots, 32(1), 63-79. https://doi.org/10.1007/s10514-011-9259-7 es_ES
dc.description.references Tully, S., Kantor, G. and Choset, H., 2010. Leap-frog path design for multi-robot cooperative localization. Field and service robotics, 307-317. https://doi.org/10.1007/978-3-642-13408-1_28 es_ES
dc.description.references Ulam, P., Endo, Y., Wagner, A. and Arkin, R., 2006. Integrated mission specification and task allocation for robot teams-part 2: Testing and evaluation. GEORGIA INST OF TECH ATLANTA COLL OF COMPUTING. https://doi.org/10.21236/ADA457295 es_ES
dc.description.references Valente, J., Sanz, D., Barrientos, A., Cerro, J. D., Ribeiro, Á. and Rossi, C., 2011. An air-ground wireless sensor network for crop monitoring. Sensors, 11(6), 6088-6108. https://doi.org/10.3390/s110606088 es_ES
dc.description.references Yan, Z., Jouandeau, N. and Cherif, A. A., 2013. A survey and analysis of multi-robot coordination. International Journal of Advanced Robotics Systems, 10(12), 399. https://doi.org/10.5772/57313 es_ES
dc.description.references Yang, L., Qi, J., Song, D., Xiao, J., Han, J. and Xia, Y., 2016A. Survey of robot 3D path planning algorithms. Journal of Control Science and Engineering, 5. https://doi.org/10.1155/2016/7426913 es_ES
dc.description.references Yang, X. J., Wickens, C. D. and Hölttä-Otto, K., 2016. How users adjust trust in automation: Contrast effect and hindsight bias. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, SAGE Publications Sage CA, Los Angeles, CA, 60(1), 196-200. https://doi.org/10.1177/1541931213601044 es_ES
dc.description.references Yew, A. W. W., Ong, S. K. and Nee A. Y. C., 2017. Immersive augmented reality for the teleoperation of maintenance robots. Procedia CIRP, 61, 305-310. https://doi.org/10.1016/j.procir.2016.11.183 es_ES
dc.description.references Zhang, Y., Gong, D. W. and Zhang, J. H., 2013. Robot path planning in uncertain environment using multi-objective particle swarm optimization. Neurocomputing, 103, 172-185. https://doi.org/10.1016/j.neucom.2012.09.019 es_ES


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