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dc.contributor.author | Mahulea, C. | es_ES |
dc.contributor.author | González, R. | es_ES |
dc.contributor.author | Montijano, E. | es_ES |
dc.contributor.author | Silva, M. | es_ES |
dc.date.accessioned | 2021-02-02T13:43:06Z | |
dc.date.available | 2021-02-02T13:43:06Z | |
dc.date.issued | 2020-12-23 | |
dc.identifier.issn | 1697-7912 | |
dc.identifier.uri | http://hdl.handle.net/10251/160489 | |
dc.description.abstract | [EN] This paper presents a trajectory planning approach in multirobot systems based on Petri net models. This type of models is very useful for high-level specifications since, in this case, the classical planning methods (potential functions, RRT algorithms, RRT*) cannot be used being dicult to determine a priori the sequence of configurations for each robot. This work presents the formal definition of the Robot Motion Petri net t hat i s obtained from a partition of the environment in cells. Using the s tructure of the Petri net, in case of specifications defined as Boolean or Linear Temporal Logic (LTL) formulas, dierent optimization problems are presented that can be used to obtain trajectories for robots. The main advantage of models based on Petri nets is their scalability with respect to the number of robots. This makes it possible to reciently solve planning problems with a large number of robots. In the second part of the paper, some extensions and new results for distributed planning in unknown environments and with partial communications between robots are presented. | es_ES |
dc.description.abstract | [ES] Este trabajo presenta una estrategia de planificacón de trayectorias en equipos de robots moviles basada en el uso de modelos definidos con redes de Petri. Estos tipos de modelos son muy útiles para especificaciones de alto nivel ya que, en este caso, los métodos clásicos de planificación (funciones potenciales, algoritmos RRT, RRT*) no se pueden utilizar, siendo difícil determinar a priori la secuencia de configuraciones para cada robot. Este trabajo presenta la definición formal de la Red de Petri de Movimiento de Robots que se obtiene a partir de una partición del entorno en celdas. Utilizando la estructura de la red de Petri, en caso de especificaciones definidas como fórmulas Booleanas o fórmulas en lógica temporal lineal (LTL), se presentan diferentes problemas de optimización que se pueden utilizar para obtener trayectorias para los robots. La principal ventaja de los modelos basados en redes de Petri es su escalabilidad con respecto al número de robots. Ello permite resolver con eficiencia problemas de planificación de equipos con un número grande de robots. En la segunda parte del trabajo, se presentan algunas extensiones y resultados nuevos para la planificación distribuida en entornos desconocidos y con comunicaciones parciales entre los robots. | es_ES |
dc.description.sponsorship | Los resultados de esta línea de investigación son fruto de la participación de varios compañeros, investigadores de la Universidad de Zaragoza y de otras Universidades extranjeras. Queremos agradecer la participación de todos ellos, mencionando muy especialmente a Marius Kloetzer (profesor de la Universidad Técnica de Iasi, Rumanía). Este trabajo ha sido financiado parcialmente por los proyectos PGC2018-098719-B-I00 and PGC2018-098817-A-I00 (MCIU/AEI/FEDER, UE) y la ONR Global NICOP grant N62909-19-1-2027. | 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 - Compartir igual (by-nc-sa) | es_ES |
dc.subject | Path planning | es_ES |
dc.subject | Multirobot systems | es_ES |
dc.subject | Discrete event systems | es_ES |
dc.subject | Petri nets | es_ES |
dc.subject | Planificación de trayectorias | es_ES |
dc.subject | Sistemas multirobot | es_ES |
dc.subject | Sistemas de eventos discretos | es_ES |
dc.subject | Redes de Petri | es_ES |
dc.title | Planificación de trayectorias en sistemas multirobot utilizando redes de Petri. Resultados y problemas abiertos | es_ES |
dc.title.alternative | Path planning of multirobot systems using Petri net models. Results and open problems | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.4995/riai.2020.13785 | |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PGC2018-098719-B-I00/ES/SISTEMAS FLEXIBLES MULTIROBOT PARA COBERTURA Y TRANSPORTE/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PGC2018-098817-A-I00/ES/ANALISIS MULTIMODAL DE ESCENAS PARA APLICACIONES DE MONITORIZACION/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/ONR//N62909-19-1-2027/US/ONRG-NICOP: DISTRIBUTED HIGH-LEVEL SCENE REASONING WITH TEAMS OF HETEROGENEOUS ROBOTS/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.description.bibliographicCitation | Mahulea, C.; González, R.; Montijano, E.; Silva, M. (2020). Planificación de trayectorias en sistemas multirobot utilizando redes de Petri. Resultados y problemas abiertos. Revista Iberoamericana de Automática e Informática industrial. 18(1):19-31. https://doi.org/10.4995/riai.2020.13785 | es_ES |
dc.description.accrualMethod | OJS | es_ES |
dc.relation.publisherversion | https://doi.org/10.4995/riai.2020.13785 | es_ES |
dc.description.upvformatpinicio | 19 | es_ES |
dc.description.upvformatpfin | 31 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 18 | es_ES |
dc.description.issue | 1 | es_ES |
dc.identifier.eissn | 1697-7920 | |
dc.relation.pasarela | OJS\13785 | es_ES |
dc.contributor.funder | European Regional Development Fund | es_ES |
dc.contributor.funder | Office of Naval Research | es_ES |
dc.contributor.funder | Agencia Estatal de Investigación | es_ES |
dc.description.references | Baier, C., Katoen, J.P., 2008. Principles of model checking. MIT Press. | es_ES |
dc.description.references | Belta, C., Bicchi, A., Egerstedt, M., Frazzoli, E., Klavins, E., Pappas, G.-J., 2007. Symbolic planning and control of robot motion. IEEE Robotics and Automation Magazine 14 (1), 61-71. https://doi.org/10.1109/MRA.2007.339624 | es_ES |
dc.description.references | Belta, C., Habets, L., 2006. Controlling a class of nonlinear systems on rectangles. IEEE Transactions on Automatic Control 51 (11), 1749-1759. https://doi.org/10.1109/TAC.2006.884957 | es_ES |
dc.description.references | Brown, F., 2012. Boolean Reasoning: The Logic of Boolean Equations, 2nd Edition. Dover Publications. | es_ES |
dc.description.references | Castellanos, J. G., Cervantes, M. V., Santana, J. S., Martínez, S. R., 2014. Seguimiento de trayectorias de un robot movil (3,0) mediante control acotado. Rev. Iberoamericana de Automatica e Informática industrial 11 (4), 426-434. https://doi.org/10.1016/j.riai.2014.09.005 | es_ES |
dc.description.references | Choset, H., Lynch, K. M., Hutchinson, S., Kantor, G., Burgard, W., Kavraki, L. E., Thrun, S., 2005. Principles of Robot Motion: Theory, Algorithms, and Implementations. MIT Press, Boston. | es_ES |
dc.description.references | Clarke, E.-M.-M., Peled, D., Grumberg, O., 1999. Model checking. MIT Press. | es_ES |
dc.description.references | DeCastro, J., Ehlers, R., Runggers, M., Balkan, A., Kress-Gazit, H., 2016. Automated generation of dynamics-based runtime certificates for high-level control. Discrete Event Dynamic Systems 27 (2), 371-405. https://doi.org/10.1007/s10626-016-0232-7 | es_ES |
dc.description.references | Ding, X., Smith, S.-L., Belta, C., Rus, D., 2014. Optimal control of Markov decision processes with linear temporal logic constraints. IEEE Transactions on Automatic Control 59 (5), 1244-1257. https://doi.org/10.1109/TAC.2014.2298143 | es_ES |
dc.description.references | Duret-Lutz, A., Lewkowicz, A., Fauchille, A., Michaud, T., Renault, E., Xu, L., 2016. Spot 2.0 - a framework for ltl and ω-automata manipulation. In: Proc. of ATVA'16. pp. 122-129. https://doi.org/10.1007/978-3-319-46520-3_8 | es_ES |
dc.description.references | Fainekos, G. E., Girard, A., Kress-Gazit, H., Pappas, G. J., 2009. Temporal logic motion planning for dynamic robots. Automatica 45 (2), 343-352. https://doi.org/10.1016/j.automatica.2008.08.008 | es_ES |
dc.description.references | Garrido, S., Moreno, L., Gomez, J.-V., Lima, P.-U., 2013. International Journal ' of Advanced Robotic Systems 10 (1), 64. https://doi.org/10.5772/53999 | es_ES |
dc.description.references | Gastin, P., Oddoux, D., 2001. Fast ltl to buchi automata translation. In: Proc. of the 13th Conference on Computer Aided Verification (CAV). pp. 53-65. https://doi.org/10.1007/3-540-44585-4_6 | es_ES |
dc.description.references | Gonzalez, R., Mahulea, C., Kloetzer, M., 2015. A Matlab-Based Interactive Simulator for Mobile Robotics. In: IEEE CASE'2015: Int. Conf. on Autom. Science and Engineering. Gothenburg, Sweden, pp. 310-315. https://doi.org/10.1109/CoASE.2015.7294097 | es_ES |
dc.description.references | Gonzalez, R., Rodriguez, F., Guzman, J. L., 2014. Autonomous Tracked Robots in Planar Off-Road Conditions. Modelling, Localization and Motion Control. Series: Studies in Systems, Decision and Control. Springer. https://doi.org/10.1007/978-3-319-06038-5 | es_ES |
dc.description.references | Guo, M., Dimarogonas, D.-V., 2015. Multi-agent plan reconfiguration under local LTL specifications. Int. Journal of Robotics Research 34 (2), 218-235. https://doi.org/10.1177/0278364914546174 | es_ES |
dc.description.references | Habets, L. C. G. J. M., Collins, P. J., van Schuppen, J. H., 2006. Reachability and control synthesis for piecewise-affine hybrid systems on simplices. IEEE Transactions on Automatic Control 51, 938-948. https://doi.org/10.1109/TAC.2006.876952 | es_ES |
dc.description.references | Julian, B.-J., Angermann, M., Schwager, M., Rus, D., 2012. Distributed robotic sensor networks: An information-theoretic approach. The International Journal of Robotics Research 31 (10), 1134-1154. https://doi.org/10.1177/0278364912452675 | es_ES |
dc.description.references | Kloetzer, M., Mahulea, C., 2014. A Petri net based approach for multi-robot path planning. Discrete Event Dynamic Systems: Theory and Applications 24 (4), 417-445. https://doi.org/10.1007/s10626-013-0162-6 | es_ES |
dc.description.references | Kloetzer, M., Mahulea, C., 2014. An assembly problem with mobile robots. In: ETFA'2014: IEEE Emerging Technology and Factory Automation. pp. 1-7. https://doi.org/10.1109/ETFA.2014.7005116 | es_ES |
dc.description.references | Kloetzer, M., Mahulea, C., 2015. LTL-based planning in environments with probabilistic observations. IEEE Transactions on Automation Science and Engineering 12 (4), 1407-1420. https://doi.org/10.1109/TASE.2015.2454299 | es_ES |
dc.description.references | Kloetzer, M., Mahulea, C., 2020. Path planning for robotic teams based on LTL specifications and Petri net models. Discrete Event Dynamic Systems: Theory and Applications 30 (1), 55-79. https://doi.org/10.1007/s10626-019-00300-1 | es_ES |
dc.description.references | Lacerda, B., Lima, P. U., 2019. Petri net based multi-robot task coordination from temporal logic specifications. Robotics and Autonomous Systems 122, 343-352. https://doi.org/10.1016/j.robot.2019.103289 | es_ES |
dc.description.references | LaValle, S. M., 2006. Planning Algorithms. Cambridge, available at http://planning.cs.uiuc.edu. https://doi.org/10.1017/CBO9780511546877 | es_ES |
dc.description.references | Leahy, K., Cristofalo, E., Vasile, C.-I., Jones, A., Montijano, E., Schwager, M., Belta, C., 2019. Control in belief space with temporal logic specifications using vision-based localization. The International Journal of Robotics Research 38 (6), 702-722. https://doi.org/10.1177/0278364919846340 | es_ES |
dc.description.references | Mahulea, C., Kloetzer, M., 2018. Robot Planning based on Boolean Specifications using Petri Net Models. IEEE Trans. on Automatic Control 63 (7), 2218-2225. https://doi.org/10.1109/TAC.2017.2760249 | es_ES |
dc.description.references | Mahulea, C., Kloetzer, M., Gonzalez, R., 2020a. Path Planning of Cooperative ' Mobile Robots Using Discrete Event Models. IEEE Wiley. https://doi.org/10.1002/9781119486305 | es_ES |
dc.description.references | Mahulea, C., Kloetzer, M., Lesage, J.-J., 2020b. Multi-robot path planning with boolean specifications and collision avoidance. In: WODES'2020: 15th Workshop on Discrete Event Systems. | es_ES |
dc.description.references | Mahulea, C., Montijano, E., Kloetzer, M., 2020c. Distributed Multirobot Path Planning in Unknown Maps Using Petri Net Models. IFACPapersOnLine21th IFAC World Congress. | es_ES |
dc.description.references | Mesbahi, M., Egerstedt, M., 2010. Graph theoretic methods in multiagent networks. Princeton University Press. https://doi.org/10.1515/9781400835355 | es_ES |
dc.description.references | Montijano, E., Montijano, J.-I., Sagues, C., Feb 2013. Chebyshev polynomials in distributed consensus applications. IEEE Transactions on Signal Processing 61 (3), 693-706. https://doi.org/10.1109/TSP.2012.2226173 | es_ES |
dc.description.references | Montijano, E., Sagües, C., 2015. Distributed consensus with visual perception ' in multi-robot systems. Springer. https://doi.org/10.1007/978-3-319-15699-6 | es_ES |
dc.description.references | Parrilla, L., Mahulea, C., Kloetzer, M., 2017. RMTool: Recent Enhancements. IFAC-PapersOnLine 50 (1), 5824 - 5830, 20th IFAC World Congress. https://doi.org/10.1016/j.ifacol.2017.08.539 | es_ES |
dc.description.references | Schillinger, P., Burger, M., Dimarogonas, D., 2018. Simultaneous task allocation and planning for temporal logic goals in heterogeneous multi-robot systems. The International Journal of Robotics Research 37 (7), 818-838. https://doi.org/10.1177/0278364918774135 | es_ES |
dc.description.references | Siegwart, R., Nourbakhsh, I., 2004. Introduction to Autonomous Mobile Robots, First Edition. A Bradford book. The MIT Press, USA. Silva, M., 1985. Las Redes de Petri : en la Automatica y la Informática; 1a ed. Editorial AC Madrid. | es_ES |
dc.description.references | Silva, M., Colom, J.-M., 1988. On the Computation of Structural Synchronic Invariants in P/T Nets. Advances in Petri Nets'87 340, 386-417. https://doi.org/10.1007/3-540-50580-6_39 | es_ES |
dc.description.references | Silva, M., Teruel, E., Colom, J.-M., 1998. Linear Algebraic and Linear Programming Techniques for the Analysis of P/T Net Systems. Lecture on Petri Nets I: Basic Models 1491, 309-373. https://doi.org/10.1007/3-540-65306-6_19 | es_ES |
dc.description.references | Tumova, J., Dimarogonas, D., 2016. Multi-agent planning under local LTL specifications and event-based synchronization. Automatica 70, 239-248. https://doi.org/10.1016/j.automatica.2016.04.006 | es_ES |
dc.description.references | Ulusoy, A., Smith, S., Ding, X., Belta, C., 2012. Robust multi-robot optimal path planning with temporal logic constraints. In: ICRA 2012: IEEE Conference on Robotics and Automation. pp. 4693-4698. https://doi.org/10.1109/ICRA.2012.6224792 | es_ES |
dc.description.references | Wolper, P., Vardi, M., Sistla, A., 1983. Reasoning about infinite computation paths. In: Proc. of the 24th IEEE Symposium on Foundations of Computer Science. pp. 185-194. https://doi.org/10.1109/SFCS.1983.51 | es_ES |
dc.description.references | Yen, J.-Y., 1971. Finding the k shortest loopless paths in a network. Management Science 17 (11), 712-716. https://doi.org/10.1287/mnsc.17.11.712 | es_ES |