Decisão Consensual em Sistemas Multirrobôs
Resumo
Essa tese tem como objetivo gerar soluções para gerenciar o comportamento coletivo de sistemas multirrobôs em fábricas inteligentes para obtenção de resiliência à falha. Assim, um mecanismo resiliente à falha, baseado em consenso, denominado Consensual Fault-Resilient Behaviour (CFRB) é apresentado. O CFRB é metodizado em três planos hierárquicos: imposição, negociação e consensual. A restauração de falhas é consequência do comportamento coletivo administrado por meio da decisão ternária nestes planos. A abordagem contribui para melhorias de produção em fábricas inteligentes, onde multirrobôs autônomos são empregados para melhorar a confiabilidade e robustez na ocorrência de falhas. Experimentos foram conduzidos para mostrar os benefícios das soluções propostas, bem como uma análise quantitativa. Além disso, o CFRB foi comparado com outras abordagens atuais e os resultados são apresentados, demonstrando sua eficiência.
Palavras-chave:
Sistemas multirrobôs, Resiliência à falha, Consenso, Fábricas inteligentes
Referências
Das, G. P., Mcginnity, T. M., Coleman, S. A., and Behera, L. (2015). A Distributed Task Allocation Algorithm for a Multi-Robot System in Healthcare Facilities. Journal of Intelligent and Robotic Systems, 80(1):33-58.
Gerkey, B. P. and Mataric, M. J. (2004). A formal analysis and taxonomy of task allocation in multi-robot systems. The International Journal of Robotics Research, 23(9):939-954.
Hoenig, W., Kiesel, S., Tinka, A., Durham, J., and Ayanian, N. (2018). Conflict-based search with optimal task assignment. Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems.
Kalempa, V. C., Piardi, L., Limeira, M., and De Oliveira, A. S. (2020a). Fault-resilient collective ternary-hierarchical behavior to smart factories. IEEE Access, 8:176905-176915.
Kalempa, V. C., Piardi, L., Limeira, M., and de Oliveira, A. S. (2021a). Multi-robot preemptive task scheduling with fault recovery: A novel approach to automatic logistics of smart factories. Sensors, 21(19).
Kalempa, V. C., Simões Teixeira, M. A., de Oliveira, A. S., and Fabro, J. A. (2021b). Agile Experimentation of Robot Swarms in Large Scale, pages 77-123. Springer International Publishing, Cham.
Kalempa, V. C., Teixeira, M. A. S., and de Oliveira, A. S. (2020b). Versatile and massive experimentation of robot swarms in industrial scenarios. In Silva, M. F., Luís Lima, J., Reis, L. P., Sanfeliu, A., and Tardioli, D., editors, Robot 2019: Fourth Iberian Robotics Conference, pages 279-290, Cham. Springer International Publishing.
Kalempa, V. C., Teixeira, M. A. S., de Oliveira, A. S., and Fabro, J. A. (2018). Intelligent dynamic formation of the multi-robot systems to cleaning tasks in unstructured environments and with a single perception system. In 2018 Latin American Robotic Symposium, 2018 Brazilian Symposium on Robotics (SBR) and 2018 Workshop on Robotics in Education (WRE), pages 71-76, Joao Pessoa, Brazil. IEEE.
Khamis, A., Hussein, A., and Elmogy, A. (2015). Multi-robot Task Allocation: A Review of the State-of-the-Art, pages 31-51. Springer International Publishing, Cham.
Limeira, M., Piardi, L., Cremer Kalempa, V., Schneider, A., and Leitão, P. (2020). Augmented reality system for multi-robot experimentation in warehouse logistics. In Silva, M. F., Luís Lima, J., Reis, L. P., Sanfeliu, A., and Tardioli, D., editors, Robot 2019: Fourth Iberian Robotics Conference, pages 319-330, Cham. Springer International Publishing.
Limeira, M., Piardi, L., Kalempa, V. C., de Oliveira, A. S., and Leitão, P. (2019). Wsbot: A tiny, low-cost swarm robot for experimentation on industry 4.0. Robotics Symposium and Latin American Robotics Symposium (SBR-LARS), 2019 Brazil.
Limeira, M., Piardi, L., Kalempa, V. C., Leitão, P., and de Oliveira, A. S. (2021). Depthlidar: Active segmentation of environment depth map into mobile sensors. IEEE Sensors Journal, 21(17):19047-19057.
Ongaro, D. and Ousterhout, J. (2014). In search of an understandable consensus algorithm. In 2014 USENIX Annual Technical Conference USENIX ATC' 14, pages 305-319.
Passino, K. M., Yurkovich, S., and Reinfrank, M. (1998). Fuzzy control, volume 42. Addison-wesley Reading, Boston.
Piardi, L., Kalempa, V. C., Limeira, M., de Oliveira, A. S., and Leitão, P. (2019). Arena augmented reality to enhanced experimentation in smart warehouses. Sensors, 19(19).
Yogeswaran, M. and Ponnambalam, S. G. (2010). Swarm robotics: An extensive research review. Advanced Knowledge Application in Practice, Igor Fuerstner (Ed.), InTech.
Gerkey, B. P. and Mataric, M. J. (2004). A formal analysis and taxonomy of task allocation in multi-robot systems. The International Journal of Robotics Research, 23(9):939-954.
Hoenig, W., Kiesel, S., Tinka, A., Durham, J., and Ayanian, N. (2018). Conflict-based search with optimal task assignment. Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems.
Kalempa, V. C., Piardi, L., Limeira, M., and De Oliveira, A. S. (2020a). Fault-resilient collective ternary-hierarchical behavior to smart factories. IEEE Access, 8:176905-176915.
Kalempa, V. C., Piardi, L., Limeira, M., and de Oliveira, A. S. (2021a). Multi-robot preemptive task scheduling with fault recovery: A novel approach to automatic logistics of smart factories. Sensors, 21(19).
Kalempa, V. C., Simões Teixeira, M. A., de Oliveira, A. S., and Fabro, J. A. (2021b). Agile Experimentation of Robot Swarms in Large Scale, pages 77-123. Springer International Publishing, Cham.
Kalempa, V. C., Teixeira, M. A. S., and de Oliveira, A. S. (2020b). Versatile and massive experimentation of robot swarms in industrial scenarios. In Silva, M. F., Luís Lima, J., Reis, L. P., Sanfeliu, A., and Tardioli, D., editors, Robot 2019: Fourth Iberian Robotics Conference, pages 279-290, Cham. Springer International Publishing.
Kalempa, V. C., Teixeira, M. A. S., de Oliveira, A. S., and Fabro, J. A. (2018). Intelligent dynamic formation of the multi-robot systems to cleaning tasks in unstructured environments and with a single perception system. In 2018 Latin American Robotic Symposium, 2018 Brazilian Symposium on Robotics (SBR) and 2018 Workshop on Robotics in Education (WRE), pages 71-76, Joao Pessoa, Brazil. IEEE.
Khamis, A., Hussein, A., and Elmogy, A. (2015). Multi-robot Task Allocation: A Review of the State-of-the-Art, pages 31-51. Springer International Publishing, Cham.
Limeira, M., Piardi, L., Cremer Kalempa, V., Schneider, A., and Leitão, P. (2020). Augmented reality system for multi-robot experimentation in warehouse logistics. In Silva, M. F., Luís Lima, J., Reis, L. P., Sanfeliu, A., and Tardioli, D., editors, Robot 2019: Fourth Iberian Robotics Conference, pages 319-330, Cham. Springer International Publishing.
Limeira, M., Piardi, L., Kalempa, V. C., de Oliveira, A. S., and Leitão, P. (2019). Wsbot: A tiny, low-cost swarm robot for experimentation on industry 4.0. Robotics Symposium and Latin American Robotics Symposium (SBR-LARS), 2019 Brazil.
Limeira, M., Piardi, L., Kalempa, V. C., Leitão, P., and de Oliveira, A. S. (2021). Depthlidar: Active segmentation of environment depth map into mobile sensors. IEEE Sensors Journal, 21(17):19047-19057.
Ongaro, D. and Ousterhout, J. (2014). In search of an understandable consensus algorithm. In 2014 USENIX Annual Technical Conference USENIX ATC' 14, pages 305-319.
Passino, K. M., Yurkovich, S., and Reinfrank, M. (1998). Fuzzy control, volume 42. Addison-wesley Reading, Boston.
Piardi, L., Kalempa, V. C., Limeira, M., de Oliveira, A. S., and Leitão, P. (2019). Arena augmented reality to enhanced experimentation in smart warehouses. Sensors, 19(19).
Yogeswaran, M. and Ponnambalam, S. G. (2010). Swarm robotics: An extensive research review. Advanced Knowledge Application in Practice, Igor Fuerstner (Ed.), InTech.
Publicado
18/10/2022
Como Citar
KALEMPA, Vivian Cremer; OLIVEIRA, André Schneider de.
Decisão Consensual em Sistemas Multirrobôs. In: CONCURSO DE TESES E DISSERTAÇÕES EM ROBÓTICA - CTDR (DOUTORADO) - SIMPÓSIO BRASILEIRO DE ROBÓTICA E SIMPÓSIO LATINO-AMERICANO DE ROBÓTICA (SBR/LARS), 14. , 2022, São Bernardo do Campo/SP.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2022
.
p. 85-96.
DOI: https://doi.org/10.5753/wtdr_ctdr.2022.226552.
