A Real-Time meta-heuristic-based safe navigation approach for mobile robots in unknown environments

Autonomous navigation in mobile robots is a complex challenge, particularly in unknown and dynamic environments where obstacle avoidance and real-time trajectory optimization are crucial. This work introduces the MetaHeuristic Real-Time Safe Navigation (MHRTSN) strategy, which integrates potential f...

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Detalles Bibliográficos
Autor: Balza, Micael
Tipo de recurso: tesis de maestría
Estado:Versión publicada
Fecha de publicación:2025
País:Brasil
Institución:Universidade Federal do Rio Grande do Norte (UFRN)
Repositorio:Repositório Institucional da UFRN
Idioma:inglés
OAI Identifier:oai:repositorio.ufrn.br:123456789/63578
Acceso en línea:https://repositorio.ufrn.br/handle/123456789/63578
Access Level:acceso abierto
Palabra clave:Autonomous navigation
Metaheuristic
Mobile robots
Path planning
Unknown environment
ENGENHARIAS::ENGENHARIA ELETRICA
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network_acronym_str BR
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repository_id_str
spelling A Real-Time meta-heuristic-based safe navigation approach for mobile robots in unknown environmentsAutonomous navigationMetaheuristicMobile robotsPath planningUnknown environmentENGENHARIAS::ENGENHARIA ELETRICAAutonomous navigation in mobile robots is a complex challenge, particularly in unknown and dynamic environments where obstacle avoidance and real-time trajectory optimization are crucial. This work introduces the MetaHeuristic Real-Time Safe Navigation (MHRTSN) strategy, which integrates potential fields with population-based metaheuristics to enhance trajectory planning and navigation efficiency. The proposed strategy was evaluated through a series of simulations in different static and dynamic scenarios, comparing the performance of two versions: MetaHeuristic Real-Time Safe Navigation with Genetic Algorithm (MHRTSN-GA) and MetaHeuristic Real-Time Safe Navigation with Particle Swarm Optimization (MHRTSN-PSO). The evaluation considered key metrics such as displacement, distance traveled, CPU time, and clock time. The results indicate that both versions provide sub-optimal solutions, with MHRTSN-PSO demonstrating superior performance in terms of computational efficiency and convergence when using a small population size. Comparisons with existing approaches in the literature revealed that MHRTSN generated paths of similar length while maintaining a safer distance from obstacles. Thus, the proposed approach offers an efficient and safe solution for autonomous navigation in mobile robots, contributing to advancements in real-world robotic applications.Universidade Federal do Rio Grande do NorteBRUFRNPROGRAMA DE PÓS-GRADUAÇÃO EM ENGENHARIA ELÉTRICA E DE COMPUTAÇÃOFernandes, Marcelo Augusto Costahttps://orcid.org/0000-0001-7536-2506http://lattes.cnpq.br/3475337353676349Silva, Sérgio NatanPedrosa, Diogo Pinheiro FernandesOliveira, Fábio Fonseca de2025-05-15T22:06:59Z2025-05-15T22:06:59Z2025-02-19info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfBALZA, Micael. A Real-Time meta-heuristic-based safe navigation approach for mobile robots in unknown environments. Orientador: Dr. Marcelo Augusto Costa Fernandes. 2025. 73f. Dissertação (Mestrado em Engenharia Elétrica e de Computação) - Centro de Tecnologia, Universidade Federal do Rio Grande do Norte, Natal, 2025.https://repositorio.ufrn.br/handle/123456789/63578ark:/41046/001300000gffjinfo:eu-repo/semantics/openAccessengreponame:Repositório Institucional da UFRNinstname:Universidade Federal do Rio Grande do Norte (UFRN)instacron:UFRNBalza, Micael2025-05-15T22:07:47Zoai:repositorio.ufrn.br:123456789/63578Repositório InstitucionalPUBhttp://repositorio.ufrn.br/oai/repositorio@bczm.ufrn.bropendoar:2025-05-15T22:07:47Repositório Institucional da UFRN - Universidade Federal do Rio Grande do Norte (UFRN)false
dc.title.none.fl_str_mv A Real-Time meta-heuristic-based safe navigation approach for mobile robots in unknown environments
title A Real-Time meta-heuristic-based safe navigation approach for mobile robots in unknown environments
spellingShingle A Real-Time meta-heuristic-based safe navigation approach for mobile robots in unknown environments
Balza, Micael
Autonomous navigation
Metaheuristic
Mobile robots
Path planning
Unknown environment
ENGENHARIAS::ENGENHARIA ELETRICA
title_short A Real-Time meta-heuristic-based safe navigation approach for mobile robots in unknown environments
title_full A Real-Time meta-heuristic-based safe navigation approach for mobile robots in unknown environments
title_fullStr A Real-Time meta-heuristic-based safe navigation approach for mobile robots in unknown environments
title_full_unstemmed A Real-Time meta-heuristic-based safe navigation approach for mobile robots in unknown environments
title_sort A Real-Time meta-heuristic-based safe navigation approach for mobile robots in unknown environments
dc.creator.none.fl_str_mv Balza, Micael
author Balza, Micael
author_facet Balza, Micael
author_role author
dc.contributor.none.fl_str_mv Fernandes, Marcelo Augusto Costa
https://orcid.org/0000-0001-7536-2506
http://lattes.cnpq.br/3475337353676349
Silva, Sérgio Natan
Pedrosa, Diogo Pinheiro Fernandes
Oliveira, Fábio Fonseca de
dc.subject.por.fl_str_mv Autonomous navigation
Metaheuristic
Mobile robots
Path planning
Unknown environment
ENGENHARIAS::ENGENHARIA ELETRICA
topic Autonomous navigation
Metaheuristic
Mobile robots
Path planning
Unknown environment
ENGENHARIAS::ENGENHARIA ELETRICA
description Autonomous navigation in mobile robots is a complex challenge, particularly in unknown and dynamic environments where obstacle avoidance and real-time trajectory optimization are crucial. This work introduces the MetaHeuristic Real-Time Safe Navigation (MHRTSN) strategy, which integrates potential fields with population-based metaheuristics to enhance trajectory planning and navigation efficiency. The proposed strategy was evaluated through a series of simulations in different static and dynamic scenarios, comparing the performance of two versions: MetaHeuristic Real-Time Safe Navigation with Genetic Algorithm (MHRTSN-GA) and MetaHeuristic Real-Time Safe Navigation with Particle Swarm Optimization (MHRTSN-PSO). The evaluation considered key metrics such as displacement, distance traveled, CPU time, and clock time. The results indicate that both versions provide sub-optimal solutions, with MHRTSN-PSO demonstrating superior performance in terms of computational efficiency and convergence when using a small population size. Comparisons with existing approaches in the literature revealed that MHRTSN generated paths of similar length while maintaining a safer distance from obstacles. Thus, the proposed approach offers an efficient and safe solution for autonomous navigation in mobile robots, contributing to advancements in real-world robotic applications.
publishDate 2025
dc.date.none.fl_str_mv 2025-05-15T22:06:59Z
2025-05-15T22:06:59Z
2025-02-19
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 BALZA, Micael. A Real-Time meta-heuristic-based safe navigation approach for mobile robots in unknown environments. Orientador: Dr. Marcelo Augusto Costa Fernandes. 2025. 73f. Dissertação (Mestrado em Engenharia Elétrica e de Computação) - Centro de Tecnologia, Universidade Federal do Rio Grande do Norte, Natal, 2025.
https://repositorio.ufrn.br/handle/123456789/63578
dc.identifier.dark.fl_str_mv ark:/41046/001300000gffj
identifier_str_mv BALZA, Micael. A Real-Time meta-heuristic-based safe navigation approach for mobile robots in unknown environments. Orientador: Dr. Marcelo Augusto Costa Fernandes. 2025. 73f. Dissertação (Mestrado em Engenharia Elétrica e de Computação) - Centro de Tecnologia, Universidade Federal do Rio Grande do Norte, Natal, 2025.
ark:/41046/001300000gffj
url https://repositorio.ufrn.br/handle/123456789/63578
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal do Rio Grande do Norte
BR
UFRN
PROGRAMA DE PÓS-GRADUAÇÃO EM ENGENHARIA ELÉTRICA E DE COMPUTAÇÃO
publisher.none.fl_str_mv Universidade Federal do Rio Grande do Norte
BR
UFRN
PROGRAMA DE PÓS-GRADUAÇÃO EM ENGENHARIA ELÉTRICA E DE COMPUTAÇÃO
dc.source.none.fl_str_mv reponame:Repositório Institucional da UFRN
instname:Universidade Federal do Rio Grande do Norte (UFRN)
instacron:UFRN
instname_str Universidade Federal do Rio Grande do Norte (UFRN)
instacron_str UFRN
institution UFRN
reponame_str Repositório Institucional da UFRN
collection Repositório Institucional da UFRN
repository.name.fl_str_mv Repositório Institucional da UFRN - Universidade Federal do Rio Grande do Norte (UFRN)
repository.mail.fl_str_mv repositorio@bczm.ufrn.br
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score 15.300719

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