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Architecting centralized coordination of soccer robots based on principle solution

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Architecting centralized coordination of soccer robots based on principle solution

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dc.contributor.author Guarnizo Marín, José Guillermo es_ES
dc.contributor.author Mellado Arteche, Martín es_ES
dc.contributor.author Low, Cheng Yee es_ES
dc.contributor.author Blanes Noguera, Francisco es_ES
dc.date.accessioned 2016-05-27T10:48:19Z
dc.date.available 2016-05-27T10:48:19Z
dc.date.issued 2015-04
dc.identifier.issn 0169-1864
dc.identifier.uri http://hdl.handle.net/10251/64845
dc.description This is an Accepted Manuscript of an article published by Taylor & Francis in Advanced Robotics on 2015, available online:http://www.tandfonline.com/10.1080/01691864.2015.1017534 es_ES
dc.description.abstract Coordination strategy is a relevant topic in multi-robot systems, and robot soccer offers a suitable domain to conduct research in multi-robot coordination. Team strategy collects and uses environmental information to derive optimal team reactions, through cooperation among individual soccer robots. This paper presents a diagrammatic approach to architecting the coordination strategy of robot soccer teams by means of a principle solution. The proposed model focuses on robot soccer leagues that possess a central decision-making system, involving the dynamic selection of the roles and behaviors of the robot soccer players. The work sets out from the conceptual design phase, facilitating cross-domain development efforts, where different layers must be interconnected and coordinated to perform multiple tasks. The principle solution allows for intuitive design and the modeling of team strategies in a highly complex robot soccer environment with changing game conditions. Furthermore, such an approach enables systematic realization of collaborative behaviors among the teammates. es_ES
dc.description.sponsorship This work was partially supported by the Spanish Ministry of Economy and Competitiveness (MINECO) under the CICYT project Mission Based Control (COBAMI): DPI2011-28507-C02-01/02. Jose G. Guarnizo was supported by a scholarship from the Administrative Department of Science, Technology and Innovation COLCIENCIAS, Colombia. en_EN
dc.language Inglés es_ES
dc.publisher Taylor and Francis es_ES
dc.relation.ispartof Advanced Robotics es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Multi-robot systems es_ES
dc.subject Robot soccer es_ES
dc.subject Strategy es_ES
dc.subject Principle solution es_ES
dc.subject Architecture es_ES
dc.subject.classification INGENIERIA DE SISTEMAS Y AUTOMATICA es_ES
dc.subject.classification ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES es_ES
dc.title Architecting centralized coordination of soccer robots based on principle solution es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1080/01691864.2015.1017534
dc.relation.projectID info:eu-repo/grantAgreement/MICINN//DPI2011-28507-C02-02/ES/SOPORTE DE EJECUCION FIABLE DE SISTEMAS DE CONTROL BASADOS EN MISIONES/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MICINN//DPI2011-28507-C02-01/ES/DESARROLLO DE CONTROLADORES BASADOS EN MISIONES/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Informática de Sistemas y Computadores - Departament d'Informàtica de Sistemes i Computadors es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería de Sistemas y Automática - Departament d'Enginyeria de Sistemes i Automàtica es_ES
dc.description.bibliographicCitation Guarnizo Marín, JG.; Mellado Arteche, M.; Low, CY.; Blanes Noguera, F. (2015). Architecting centralized coordination of soccer robots based on principle solution. Advanced Robotics. 29(15):989-1004. https://doi.org/10.1080/01691864.2015.1017534 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://dx.doi.org/10.1080/01691864.2015.1017534 es_ES
dc.description.upvformatpinicio 989 es_ES
dc.description.upvformatpfin 1004 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 29 es_ES
dc.description.issue 15 es_ES
dc.relation.senia 303304 es_ES
dc.identifier.eissn 1568-5535
dc.contributor.funder Ministerio de Ciencia e Innovación es_ES
dc.contributor.funder Departamento Administrativo de Ciencia, Tecnología e Innovación, Colombia es_ES
dc.description.references Farinelli, A., Iocchi, L., & Nardi, D. (2004). Multirobot Systems: A Classification Focused on Coordination. IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), 34(5), 2015-2028. doi:10.1109/tsmcb.2004.832155 es_ES
dc.description.references Tews, A., & Wyeth, G. (2000). MAPS: a system for multi-agent coordination. Advanced Robotics, 14(1), 37-50. doi:10.1163/156855300741429 es_ES
dc.description.references Stulp, F., Utz, H., Isik, M., & Mayer, G. (2010). Implicit Coordination with Shared Belief: A Heterogeneous Robot Soccer Team Case Study. Advanced Robotics, 24(7), 1017-1036. doi:10.1163/016918610x496964 es_ES
dc.description.references Guarnizo, J. G., Mellado, M., Low, C. Y., & Aziz, N. (2013). Strategy Model for Multi-Robot Coordination in Robotic Soccer. Applied Mechanics and Materials, 393, 592-597. doi:10.4028/www.scientific.net/amm.393.592 es_ES
dc.description.references Riley, P., & Veloso, M. (2002). Recognizing Probabilistic Opponent Movement Models. Lecture Notes in Computer Science, 453-458. doi:10.1007/3-540-45603-1_59 es_ES
dc.description.references Ros, R., Arcos, J. L., Lopez de Mantaras, R., & Veloso, M. (2009). A case-based approach for coordinated action selection in robot soccer. Artificial Intelligence, 173(9-10), 1014-1039. doi:10.1016/j.artint.2009.02.004 es_ES
dc.description.references Atkinson, J., & Rojas, D. (2009). On-the-fly generation of multi-robot team formation strategies based on game conditions. Expert Systems with Applications, 36(3), 6082-6090. doi:10.1016/j.eswa.2008.07.039 es_ES
dc.description.references Costelha, H., & Lima, P. (2012). Robot task plan representation by Petri nets: modelling, identification, analysis and execution. Autonomous Robots, 33(4), 337-360. doi:10.1007/s10514-012-9288-x es_ES
dc.description.references Abreu, P. H., Silva, D. C., Almeida, F., & Mendes-Moreira, J. (2014). Improving a simulated soccer team’s performance through a Memory-Based Collaborative Filtering approach. Applied Soft Computing, 23, 180-193. doi:10.1016/j.asoc.2014.06.021 es_ES
dc.description.references Duan, Y., Liu, Q., & Xu, X. (2007). Application of reinforcement learning in robot soccer. Engineering Applications of Artificial Intelligence, 20(7), 936-950. doi:10.1016/j.engappai.2007.01.003 es_ES
dc.description.references Hwang, K.-S., Jiang, W.-C., Yu, H.-H., & Li, S.-Y. (2011). Cooperative Reinforcement Learning Based on Zero-Sum Games. Mobile Robots - Control Architectures, Bio-Interfacing, Navigation, Multi Robot Motion Planning and Operator Training. doi:10.5772/26620 es_ES
dc.description.references Gausemeier, J., Dumitrescu, R., Kahl, S., & Nordsiek, D. (2011). Integrative development of product and production system for mechatronic products. Robotics and Computer-Integrated Manufacturing, 27(4), 772-778. doi:10.1016/j.rcim.2011.02.005 es_ES
dc.description.references Klančar, G., Zupančič, B., & Karba, R. (2007). Modelling and simulation of a group of mobile robots. Simulation Modelling Practice and Theory, 15(6), 647-658. doi:10.1016/j.simpat.2007.02.002 es_ES
dc.description.references Gausemeier, J., Frank, U., Donoth, J., & Kahl, S. (2009). Specification technique for the description of self-optimizing mechatronic systems. Research in Engineering Design, 20(4), 201-223. doi:10.1007/s00163-008-0058-x es_ES


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