Enhanced Multi-Robot System Architecture with Distributed Planning
Resumo
Achieving shared goals across real scenarios with multiple robots remains a challenge in autonomous multi-robot systems. This challenge is closely related to Multi-Agent Systems (MAS) and automated planning. The literature presents solutions for robotic agents in navigation and interaction, but planning recovery mechanisms is vital to ensure mission continuity and deserves more investigation. The Belief-Desire-Intention (BDI) agents present full potential for autonomy, adaptability, reactivity, and cooperation in MAS. This work presents a multi-robot system architecture with BDI robots enhanced with distributed planning. The validation applies heterogeneous robots to a hospital disinfection mission with a runtime replanning strategy by the Coordinator and local robots, achieving a 100% mission success rate.Referências
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Macenski, S., Foote, T., Gerkey, B., Lalancette, C., and Woodall, W. (2022). Robot Operating System 2: Design, architecture, and uses in the wild. Science Robotics, 7(66).
Micheli, A., Bit-Monnot, A., Röger, G., Scala, E., Valentini, A., Framba, L., Rovetta, A., Trapasso, A., Bonassi, L., Gerevini, A. E., Iocchi, L., Ingrand, F., Köckemann, U., Patrizi, F., Saetti, A., Serina, I., and Stock, S. (2025). Unified Planning: Modeling, manipulating and solving AI planning problems in Python. SoftwareX, 29:102012.
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Moreira, L. H. and Ralha, C. G. (2022a). An efficient lightweight coordination model to multi-agent planning. Knowledge and Information Systems, 64:415–439.
Moreira, L. H. and Ralha, C. G. (2022b). Method for evaluating plan recovery strategies in dynamic multi-agent environments. Journal of Experimental & Theoretical Artificial Intelligence, pages 1–25.
Nau, D., Cao, Y., Lotem, A., and Munoz-Avila, H. (1999). Shop: simple hierarchical ordered planner. In Proc. of 16th Int. Joint Conf. on Artificial Intelligence (IJCAI), page 968–973, San Francisco, CA, USA. Morgan Kaufmann Publishers Inc.
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Rizk, Y., Awad, M., and Tunstel, E. W. (2019). Cooperative heterogeneous multi-robot systems: A survey. ACM Comput. Surv., 52(2).
Stolba, M., Komenda, A., and Kovacs, D. L. (2015). Competition of Distributed and Multiagent Planners (CoDMAP). Workshop on Distributed and Multi-Agent Planning (DMAP), 25th Int. Conf. on Automated Planning and Scheduling (ICAPS). Available at [link]. Accessed on: 2020-02-05.
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Trafton, A. (2020). Robot takes contact-free measurements of patients’ vital signs. MIT News Office. August 31, 2020.
Verma, J. K. and Ranga, V. (2021). Multi-robot coordination analysis, taxonomy, challenges and future scope. Journal of Intelligent & Robotic Systems, 102(1).
Wooldridge, M. (2009). An introduction to multiagent systems. John Wiley & Sons.
Wooldridge, M. (2020). Reasoning about Rational Agents. MIT Press. Intelligent Robotics and Autonomous Agents Series. ISBN: 9780262257237.
Askarpour, M., Tsigkanos, C., Menghi, C., Calinescu, R., Pelliccione, P., García, S., Caldas, R., von Oertzen, T. J., Wimmer, M., Berardinelli, L., Rossi, M., Bersani, M. M., and Rodrigues, G. S. (2021). RoboMAX: Robotic mission adaptation exemplars. In Proc. of Int. Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS), pages 245–251.
Aziz, H., Chan, H., Cseh, A., Li, B., Ramezani, F., and Wang, C. (2021). Multi-robot task allocation-complexity and approximation. In Proc. of 20th Int. Conf. on Autonomous Agents and MultiAgent Systems (AAMAS), page 133–141.
Bansod, Y., Patra, S., Nau, D., and Roberts, M. (2022). Htn replanning from the middle. In The International FLAIRS Conference Proceedings, volume 35.
Boissier, O., Bordini, R. H., Hübner, J., and Ricci, A. (2020). Multi-Agent Oriented Programming - Programming Multi-Agent Systems Using JaCaMo. MIT Press. Intelligent Robotics and Autonomous Agents Series. ISBN: 9780262044578.
Bordini, R. H., Hübner, J. F., and Wooldridge, M. (2007). Programming Multi-Agent Systems in AgentSpeak using Jason. John Wiley & Sons. ISBN: 9780470029008.
Bratman, M. (1987). Intention, Plans, and Practical Reason. Cambridge, MA: Harvard University Press, Cambridge.
Cardoso, R. C., Ferrando, A., Dennis, L. A., and Fisher, M. (2020). An interface for programming verifiable autonomous agents in ROS. In International Conference on Agreement Technologies (ICAT), pages 191–205.
da Silva, C. J. T., Santos, R. M., Cardoso, R. C., and Ralha, C. G. (2026). A Multi-Robot Architecture for Continuous Planning and Execution using BDI Agents. In Proc. of 25nd Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS), page 422–430, Richland, SC. IFAAMAS.
Klavins, E. (2004). Communication Complexity of Multi-robot Systems, pages 275–291. Springer, Berlin, Heidelberg.
Macenski, S., Foote, T., Gerkey, B., Lalancette, C., and Woodall, W. (2022). Robot Operating System 2: Design, architecture, and uses in the wild. Science Robotics, 7(66).
Micheli, A., Bit-Monnot, A., Röger, G., Scala, E., Valentini, A., Framba, L., Rovetta, A., Trapasso, A., Bonassi, L., Gerevini, A. E., Iocchi, L., Ingrand, F., Köckemann, U., Patrizi, F., Saetti, A., Serina, I., and Stock, S. (2025). Unified Planning: Modeling, manipulating and solving AI planning problems in Python. SoftwareX, 29:102012.
Moreira, L. H. and Ralha, C. G. (2021). Evaluation of decision-making strategies for robots in intralogistics problems using multi-agent planning. In Proc. of IEEE Congress on Evolutionary Computation (CEC), pages 1272–1279.
Moreira, L. H. and Ralha, C. G. (2022a). An efficient lightweight coordination model to multi-agent planning. Knowledge and Information Systems, 64:415–439.
Moreira, L. H. and Ralha, C. G. (2022b). Method for evaluating plan recovery strategies in dynamic multi-agent environments. Journal of Experimental & Theoretical Artificial Intelligence, pages 1–25.
Nau, D., Cao, Y., Lotem, A., and Munoz-Avila, H. (1999). Shop: simple hierarchical ordered planner. In Proc. of 16th Int. Joint Conf. on Artificial Intelligence (IJCAI), page 968–973, San Francisco, CA, USA. Morgan Kaufmann Publishers Inc.
OMG (2014). Business process model and notation specification version 2.0.2 (BPMN™).
Rizk, Y., Awad, M., and Tunstel, E. W. (2019). Cooperative heterogeneous multi-robot systems: A survey. ACM Comput. Surv., 52(2).
Stolba, M., Komenda, A., and Kovacs, D. L. (2015). Competition of Distributed and Multiagent Planners (CoDMAP). Workshop on Distributed and Multi-Agent Planning (DMAP), 25th Int. Conf. on Automated Planning and Scheduling (ICAPS). Available at [link]. Accessed on: 2020-02-05.
Torreño, A., Onaindia, E., Komenda, A., and Štolba, M. (2017). Cooperative multi-agent planning: A survey. ACM Comput. Surv., 50(6).
Trafton, A. (2020). Robot takes contact-free measurements of patients’ vital signs. MIT News Office. August 31, 2020.
Verma, J. K. and Ranga, V. (2021). Multi-robot coordination analysis, taxonomy, challenges and future scope. Journal of Intelligent & Robotic Systems, 102(1).
Wooldridge, M. (2009). An introduction to multiagent systems. John Wiley & Sons.
Wooldridge, M. (2020). Reasoning about Rational Agents. MIT Press. Intelligent Robotics and Autonomous Agents Series. ISBN: 9780262257237.
Publicado
19/10/2026
Como Citar
SANTOS, Rafael Melo; TAVARES, Carlos Joel; RALHA, Célia Ghedini.
Enhanced Multi-Robot System Architecture with Distributed Planning. In: ENCONTRO NACIONAL DE INTELIGÊNCIA ARTIFICIAL E COMPUTACIONAL (ENIAC), 23. , 2026, Cuiabá/MT.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2026
.
p. 2667-2678.
ISSN 2763-9061.
DOI: https://doi.org/10.5753/eniac.2026.30088.
