Multi-Robot System Architecture Validation Using Disinfecting Robot Routine
Resumo
Coordinating multiple robots to achieve shared goals across diverse scenarios remains a key challenge in Multi-Robot Systems (MRS). The literature proposes solutions where robots must collaborate, share information, and have planning recovery mechanisms to ensure mission continuity. The challenges involved are closely related to Multi-Agent Systems (MAS) integrated with Automated Planning (AP), often evaluated in limited and controlled scenarios. But to support claims of applicability, broader testing across diverse scenarios is essential. This work evaluates an MRS solution that integrates AP into an MAS, using a disinfecting robot routine as an illustrative study.
Referências
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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.
Cashmore, M., Fox, M., Long, D., Magazzeni, D., Ridder, B., Carreraa, A., Palomeras, N., Hurtós, N., and Carrerasa, M. (2015). ROSPlan: Planning in the robot operating system. In Proc. of 35th Int. Conf. on Automated Planning and Scheduling (ICAPS), page 333–341.
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da Silva, C. J. T. and Ralha, C. G. (2024). Multi-agent system architectural aspects for continuous replanning. In Anais do XVIII Workshop-Escola de Sistemas de Agentes, seus Ambientes e Aplicações, pages 39–50, Porto Alegre, RS, Brasil. SBC.
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González, J. C., García-Olaya, A., and Fernández, F. (2020). Multi-layered multi-robot control architecture for the robocup logistics league. In Proc. of IEEE Int. Conf. on Autonomous Robot Systems and Competitions, pages 120–125.
Klavins, E. (2004). Communication Complexity of Multi-robot Systems, pages 275–291. Springer, Berlin, Heidelberg.
Komenda, A., Stolba, M., and Kovacs, D. L. (2016). The international competition of distributed and multiagent planners (CoDMAP). AI Magazine, 37(3):109–115.
Lesire, C., Bailon-Ruiz, R., Barbier, M., and Grand, C. (2022). A hierarchical deliberative architecture framework based on goal decomposition. In Proc. of IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), pages 9865–9870.
Martín, F., Clavero, J. G., Matellán, V., and Rodríguez, F. J. (2021). PlanSys2: A planning system framework for ROS2. In Proc. of IEEE Int. Conf. on Intelligent Robots and Systems (IROS), page 9742–9749.
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, pages 1272–1279.
Moreira, L. H. and Ralha, C. G. (2022). An efficient lightweight coordination model to multi-agent planning. Knowledge and Information Systems, 64:415–439.
OMG (2014). Business process model and notation specification version 2.0.2 (BPMN™). [link]. Accessed: 2025-08-03.
Rizk, Y., Awad, M., and Tunstel, E. W. (2019). Cooperative heterogeneous multi-robot systems: A survey. ACM Comput. Surv., 52(2).
Rodrigues, G., Caldas, R., Araujo, G., de Moraes, V., Rodrigues, G., and Pelliccione, P. (2022). An architecture for mission coordination of heterogeneous robots. Journal of Systems and Software, 191(111363).
Salzman, O. and Stern, R. (2020). Research challenges and opportunities in multi-agent path finding and multi-agent pickup and delivery problems. In Proc. of 19th Int. Conf. on Autonomous Agents and MultiAgent Systems (AAMAS), page 1711–1715.
Torreño, A., Onaindia, E., Komenda, A., and Štolba, M. (2017). Cooperative multi-agent planning: A survey. ACM Comput. Surv., 50(6).
Verma, J. K. and Ranga, V. (2021). Multi-robot coordination analysis, taxonomy, challenges and future scope. Journal of Intelligent & Robotic Systems, 102(1).
Weiss, G. (2016). Multiagent Systems. The MIT Press, 2nd edition.
Wooldridge, M. (2009). An introduction to multiagent systems. John Wiley & Sons.
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.
Cashmore, M., Fox, M., Long, D., Magazzeni, D., Ridder, B., Carreraa, A., Palomeras, N., Hurtós, N., and Carrerasa, M. (2015). ROSPlan: Planning in the robot operating system. In Proc. of 35th Int. Conf. on Automated Planning and Scheduling (ICAPS), page 333–341.
da Silva, C. J. T. (2024). A Multi-robot System Architecture with Multi-agent Planning. Master’s thesis, Computer Science Department, University of Brasília, Brazil.
da Silva, C. J. T. and Ralha, C. G. (2023). Multi-robot system architecture focusing on plan recovery for dynamic environments. In 2023 IEEE Symposium Series on Computational Intelligence (SSCI), pages 1668–1673.
da Silva, C. J. T. and Ralha, C. G. (2024). Multi-agent system architectural aspects for continuous replanning. In Anais do XVIII Workshop-Escola de Sistemas de Agentes, seus Ambientes e Aplicações, pages 39–50, Porto Alegre, RS, Brasil. SBC.
Erol, K., Hendler, J., and Nau, D. (1996). Complexity results for HTN planning. Annals of Mathematics and Artificial Intelligence, 18:69–93.
Erol, K., Hendler, J., and Nau, D. S. (1994). HTN planning: complexity and expressivity. In Proceedings of the Twelfth AAAI National Conference on Artificial Intelligence, AAAI’94, page 1123–1128. AAAI Press.
González, J. C., García-Olaya, A., and Fernández, F. (2020). Multi-layered multi-robot control architecture for the robocup logistics league. In Proc. of IEEE Int. Conf. on Autonomous Robot Systems and Competitions, pages 120–125.
Klavins, E. (2004). Communication Complexity of Multi-robot Systems, pages 275–291. Springer, Berlin, Heidelberg.
Komenda, A., Stolba, M., and Kovacs, D. L. (2016). The international competition of distributed and multiagent planners (CoDMAP). AI Magazine, 37(3):109–115.
Lesire, C., Bailon-Ruiz, R., Barbier, M., and Grand, C. (2022). A hierarchical deliberative architecture framework based on goal decomposition. In Proc. of IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), pages 9865–9870.
Martín, F., Clavero, J. G., Matellán, V., and Rodríguez, F. J. (2021). PlanSys2: A planning system framework for ROS2. In Proc. of IEEE Int. Conf. on Intelligent Robots and Systems (IROS), page 9742–9749.
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, pages 1272–1279.
Moreira, L. H. and Ralha, C. G. (2022). An efficient lightweight coordination model to multi-agent planning. Knowledge and Information Systems, 64:415–439.
OMG (2014). Business process model and notation specification version 2.0.2 (BPMN™). [link]. Accessed: 2025-08-03.
Rizk, Y., Awad, M., and Tunstel, E. W. (2019). Cooperative heterogeneous multi-robot systems: A survey. ACM Comput. Surv., 52(2).
Rodrigues, G., Caldas, R., Araujo, G., de Moraes, V., Rodrigues, G., and Pelliccione, P. (2022). An architecture for mission coordination of heterogeneous robots. Journal of Systems and Software, 191(111363).
Salzman, O. and Stern, R. (2020). Research challenges and opportunities in multi-agent path finding and multi-agent pickup and delivery problems. In Proc. of 19th Int. Conf. on Autonomous Agents and MultiAgent Systems (AAMAS), page 1711–1715.
Torreño, A., Onaindia, E., Komenda, A., and Štolba, M. (2017). Cooperative multi-agent planning: A survey. ACM Comput. Surv., 50(6).
Verma, J. K. and Ranga, V. (2021). Multi-robot coordination analysis, taxonomy, challenges and future scope. Journal of Intelligent & Robotic Systems, 102(1).
Weiss, G. (2016). Multiagent Systems. The MIT Press, 2nd edition.
Wooldridge, M. (2009). An introduction to multiagent systems. John Wiley & Sons.
Publicado
29/09/2025
Como Citar
SANTOS, Rafael Melo; TAVARES, Carlos Joel; RALHA, Célia Ghedini.
Multi-Robot System Architecture Validation Using Disinfecting Robot Routine. In: WORKSHOP-ESCOLA DE SISTEMAS DE AGENTES, SEUS AMBIENTES E APLICAÇÕES (WESAAC), 19. , 2025, Fortaleza/CE.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 101-112.
ISSN 2326-5434.
DOI: https://doi.org/10.5753/wesaac.2025.37529.
