ST-SPF & STMS: two new algorithms for path finding in robotic mobile fulfillment systems

Detalhes bibliográficos
Ano de defesa: 2021
Autor(a) principal: Barros, Ítalo Renan da Costa
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal da Paraíba
Brasil
Informática
Programa de Pós-Graduação em Informática
UFPB
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
RMFS
MAPF
Path planning
Sistemas multi-agentes
Warehouses robotizadas
Multti-agent systems
Robotized warehouses
CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
Link de acesso: https://repositorio.ufpb.br/jspui/handle/123456789/22655
Resumo: One of the main problems faced in Multi-Agent Path Finding (MAPF) applied to Robotic Mobile Fulfillment Systems (RMFS) is how to bring greater scalability as we increase the number of agents in the system. This work aims to propose two new offline algorithms, the Space-Time Swarm Path Finding (ST-SPF) a decentralized algorithm, and the Space-Time Multi-Start (STMS), an centralized algorithm. The algorithms were tested in a simulator developed in the PyGame framework, with up to 250 agents in three different types of warehouses instances) and two types of map representations: Grid-Based and Graph-Based. The results show that the ST-SPF is scalable in complex and populous maps, achieving up to 48% reduction in execution time when compared to the Conflict-based Search (CBS) art study algorithm, while the STMS presented an advantage to CBS since achieves more completeness in small and populous instances. Finally, it was also noted that the use of the Graph-Based representation has a high use of memory for complex instances (above 600 nodes), with the Grid-Based representation being the most efficient.
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spelling ST-SPF & STMS: two new algorithms for path finding in robotic mobile fulfillment systemsRMFSMAPFPath planningSistemas multi-agentesWarehouses robotizadasMultti-agent systemsRobotized warehousesCNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAOOne of the main problems faced in Multi-Agent Path Finding (MAPF) applied to Robotic Mobile Fulfillment Systems (RMFS) is how to bring greater scalability as we increase the number of agents in the system. This work aims to propose two new offline algorithms, the Space-Time Swarm Path Finding (ST-SPF) a decentralized algorithm, and the Space-Time Multi-Start (STMS), an centralized algorithm. The algorithms were tested in a simulator developed in the PyGame framework, with up to 250 agents in three different types of warehouses instances) and two types of map representations: Grid-Based and Graph-Based. The results show that the ST-SPF is scalable in complex and populous maps, achieving up to 48% reduction in execution time when compared to the Conflict-based Search (CBS) art study algorithm, while the STMS presented an advantage to CBS since achieves more completeness in small and populous instances. Finally, it was also noted that the use of the Graph-Based representation has a high use of memory for complex instances (above 600 nodes), with the Grid-Based representation being the most efficient.Conselho Nacional de Pesquisa e Desenvolvimento Científico e Tecnológico - CNPqUm dos principais problemas enfrentado no Multi-Agent Path Finding aplicado a Robotic Mobile Fulfillment Systems é como trazer uma maior escalabilidade ao sistema conforme aumentamos o número de agentes. Este trabalho tem como objetivo propor dois novos algoritmos offline, o algoritmo descentralizado Space-Time Swarm Path Finding (ST-SPF), e o algoritmo centralizado Space-Time Multi-Start (STMS). Os algoritmos foram testados em um simulador desenvolvido no framework PyGame, onde foram realizados experimentos com até 250 agentes em três tipos de warehouses (instâncias) diferentes, e com dois tipos representações do mapa: Grid-Based e Graph-Based. Os resultados demonstram que o ST-SPF é escalável em instâncias grandes e populosas, alcançando até 48% de redução do tempo de execução quando comparado com o algoritmo de estudo da arte Conflict-based Search (CBS), enquanto que o STMS apresentou uma vantagem ao CBS por ser mais completo (completeness) em instâncias pequenas e populosas. Por fim, também foi notado que a utilização da representação Graph-Based possui uma alta utilização de memória para instâncias complexas (acima de 600 nós), sendo a representação Grid-Based mais eficiente.Universidade Federal da ParaíbaBrasilInformáticaPrograma de Pós-Graduação em InformáticaUFPBNascimento, Tiago Pereira dohttp://lattes.cnpq.br/1641673656667170Costa, Luís Peliphe SilvaLattes não recuperado em 30/03/2022Barros, Ítalo Renan da Costa2022-04-06T15:10:06Z2021-10-232022-04-06T15:10:06Z2021-03-19info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesishttps://repositorio.ufpb.br/jspui/handle/123456789/22655porAttribution-NoDerivs 3.0 Brazilhttp://creativecommons.org/licenses/by-nd/3.0/br/info:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFPBinstname:Universidade Federal da Paraíba (UFPB)instacron:UFPB2022-04-07T16:39:23Zoai:repositorio.ufpb.br:123456789/22655Repositório InstitucionalPUBhttps://repositorio.ufpb.br/oai/requestdiretoria@ufpb.br||bdtd@biblioteca.ufpb.bropendoar:25462022-04-07T16:39:23Repositório Institucional da UFPB - Universidade Federal da Paraíba (UFPB)false
dc.title.none.fl_str_mv ST-SPF & STMS: two new algorithms for path finding in robotic mobile fulfillment systems
title ST-SPF & STMS: two new algorithms for path finding in robotic mobile fulfillment systems
spellingShingle ST-SPF & STMS: two new algorithms for path finding in robotic mobile fulfillment systems
Barros, Ítalo Renan da Costa
RMFS
MAPF
Path planning
Sistemas multi-agentes
Warehouses robotizadas
Multti-agent systems
Robotized warehouses
CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
title_short ST-SPF & STMS: two new algorithms for path finding in robotic mobile fulfillment systems
title_full ST-SPF & STMS: two new algorithms for path finding in robotic mobile fulfillment systems
title_fullStr ST-SPF & STMS: two new algorithms for path finding in robotic mobile fulfillment systems
title_full_unstemmed ST-SPF & STMS: two new algorithms for path finding in robotic mobile fulfillment systems
title_sort ST-SPF & STMS: two new algorithms for path finding in robotic mobile fulfillment systems
author Barros, Ítalo Renan da Costa
author_facet Barros, Ítalo Renan da Costa
author_role author
dc.contributor.none.fl_str_mv Nascimento, Tiago Pereira do
http://lattes.cnpq.br/1641673656667170
Costa, Luís Peliphe Silva
Lattes não recuperado em 30/03/2022
dc.contributor.author.fl_str_mv Barros, Ítalo Renan da Costa
dc.subject.por.fl_str_mv RMFS
MAPF
Path planning
Sistemas multi-agentes
Warehouses robotizadas
Multti-agent systems
Robotized warehouses
CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
topic RMFS
MAPF
Path planning
Sistemas multi-agentes
Warehouses robotizadas
Multti-agent systems
Robotized warehouses
CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
description One of the main problems faced in Multi-Agent Path Finding (MAPF) applied to Robotic Mobile Fulfillment Systems (RMFS) is how to bring greater scalability as we increase the number of agents in the system. This work aims to propose two new offline algorithms, the Space-Time Swarm Path Finding (ST-SPF) a decentralized algorithm, and the Space-Time Multi-Start (STMS), an centralized algorithm. The algorithms were tested in a simulator developed in the PyGame framework, with up to 250 agents in three different types of warehouses instances) and two types of map representations: Grid-Based and Graph-Based. The results show that the ST-SPF is scalable in complex and populous maps, achieving up to 48% reduction in execution time when compared to the Conflict-based Search (CBS) art study algorithm, while the STMS presented an advantage to CBS since achieves more completeness in small and populous instances. Finally, it was also noted that the use of the Graph-Based representation has a high use of memory for complex instances (above 600 nodes), with the Grid-Based representation being the most efficient.
publishDate 2021
dc.date.none.fl_str_mv 2021-10-23
2021-03-19
2022-04-06T15:10:06Z
2022-04-06T15:10:06Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://repositorio.ufpb.br/jspui/handle/123456789/22655
url https://repositorio.ufpb.br/jspui/handle/123456789/22655
dc.language.iso.fl_str_mv por
language por
dc.rights.driver.fl_str_mv Attribution-NoDerivs 3.0 Brazil
http://creativecommons.org/licenses/by-nd/3.0/br/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Attribution-NoDerivs 3.0 Brazil
http://creativecommons.org/licenses/by-nd/3.0/br/
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Universidade Federal da Paraíba
Brasil
Informática
Programa de Pós-Graduação em Informática
UFPB
publisher.none.fl_str_mv Universidade Federal da Paraíba
Brasil
Informática
Programa de Pós-Graduação em Informática
UFPB
dc.source.none.fl_str_mv reponame:Repositório Institucional da UFPB
instname:Universidade Federal da Paraíba (UFPB)
instacron:UFPB
instname_str Universidade Federal da Paraíba (UFPB)
instacron_str UFPB
institution UFPB
reponame_str Repositório Institucional da UFPB
collection Repositório Institucional da UFPB
repository.name.fl_str_mv Repositório Institucional da UFPB - Universidade Federal da Paraíba (UFPB)
repository.mail.fl_str_mv diretoria@ufpb.br||bdtd@biblioteca.ufpb.br
_version_ 1863379044828971008

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