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

J. J. Roldan-Gómez, J. de León Rivas, P. Garcia-Aunon, A. Barrientos

Resumen

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.


Palabras clave

Robótica; Robots; Operadores; Interfaces; Interacción Humano-Máquina

Clasificación por materias

Robótica y sistemas robotizados; Interfaces; Interacción Persona-Máquina

Texto completo:

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Referencias

Abbadi, A. and Prenosil., 2015. Safe path planning using cell decomposition approximation. Distance Learning, Simulation and Communication, 8.

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

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

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.

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

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

Bourguet, M. L., 2003. Designing and Prototyping Multimodal Commands. Interact, 3, 717-720.

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

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

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

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

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

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

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.

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

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

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

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

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

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

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

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

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.

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

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.

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

Endsley, M. R., 1988B. Situation awareness global assessment technique (SAGAT). Proceedings of the IEEE 1988 National Aerospace and Electronics Conference (NAECON), 789-795.

Endsley, M. R. and Garland, D. J., 2000. Situation awareness analysis and measurement. CRC Press. https://doi.org/10.1201/b12461

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

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).

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Hong, A., 2016. Human-Robot Interactions for Single Robots and Multi-Robot Teams. PhD thesis, Department of Mechanical and Industrial Engineering, University of Toronto.

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.

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

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

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

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

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

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

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.

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

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

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

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.

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

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

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

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

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

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

Lysaght, R. J., 1989. Operator workload: Comprehensive review and evaluation of operator workload methodologies. Tech. Rep. DTIC Document. https://doi.org/10.21236/ADA212879

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

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

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

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

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

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

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.

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

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

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

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

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.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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.

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

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

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.

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

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

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

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

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.

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

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

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

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

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

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

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

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

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

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

Sheridan, 2002. Humans and automation: System design and research issues. John Wiley & Sons.

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

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.

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

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

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.

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

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

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

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

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

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

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

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

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

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