A Real-Time Safe Navigation Proposal for Mobile Robots in Unknown Environments Using Meta-Heuristics
Autonomous navigation in mobile robots represents a significant challenge in unknown and dynamic environments, where the need to avoid obstacles and find safe trajectories in real-time requires efficient solutions. This work presents the MetaHeuristic Real-Time Safe Navigation (MHRTSN) strategy, whi...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10857271/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1823859644584427520 |
|---|---|
| author | Micael Balza Mateus A. Goldbarg Sergio N. Silva Lucileide M. D. Silva Marcelo A. C. Fernandes |
| author_facet | Micael Balza Mateus A. Goldbarg Sergio N. Silva Lucileide M. D. Silva Marcelo A. C. Fernandes |
| author_sort | Micael Balza |
| collection | DOAJ |
| description | Autonomous navigation in mobile robots represents a significant challenge in unknown and dynamic environments, where the need to avoid obstacles and find safe trajectories in real-time requires efficient solutions. This work presents the MetaHeuristic Real-Time Safe Navigation (MHRTSN) strategy, which combines potential fields with population-based meta-heuristics to optimize trajectory planning and navigation in such environments. The MHRTSN strategy was tested through a series of simulations using different static and dynamic scenarios, comparing the performance of MHRTSN-GA and MHRTSN-PSO versions in terms of displacement, distance traveled, and CPU and clock times. The results demonstrate that both versions provide sub-optimal solutions, with MHRTSN-PSO showing superior performance in terms of required processing time and better convergence compared to MHRTSN-GA when using a small number of individuals. Comparisons with other approaches in the literature showed that MHRTSN generated paths of equivalent length to those of the literature, but in a safer manner. Thus, the proposed approach offers an efficient and safe solution for autonomous navigation in mobile robots, contributing to the advancement of this field in real-world applications. Future work may explore the application of the strategy in physical robotic systems and more complex environments. |
| format | Article |
| id | doaj-art-ceb2c615aaf344538c3c4d92b0c1ffc0 |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-ceb2c615aaf344538c3c4d92b0c1ffc02025-02-11T00:01:15ZengIEEEIEEE Access2169-35362025-01-0113239872401310.1109/ACCESS.2025.353608110857271A Real-Time Safe Navigation Proposal for Mobile Robots in Unknown Environments Using Meta-HeuristicsMicael Balza0https://orcid.org/0000-0001-9315-9683Mateus A. Goldbarg1https://orcid.org/0009-0003-2176-793XSergio N. Silva2https://orcid.org/0000-0002-6958-6754Lucileide M. D. Silva3https://orcid.org/0000-0001-6282-9744Marcelo A. C. Fernandes4https://orcid.org/0000-0001-7536-2506InovAI Laboratory, nPITI/IMD, Federal University of Rio Grande do Norte (UFRN), Natal, BrazilInovAI Laboratory, nPITI/IMD, Federal University of Rio Grande do Norte (UFRN), Natal, BrazilInovAI Laboratory, nPITI/IMD, Federal University of Rio Grande do Norte (UFRN), Natal, BrazilInovAI Laboratory, nPITI/IMD, Federal University of Rio Grande do Norte (UFRN), Natal, BrazilInovAI Laboratory, nPITI/IMD, Federal University of Rio Grande do Norte (UFRN), Natal, BrazilAutonomous navigation in mobile robots represents a significant challenge in unknown and dynamic environments, where the need to avoid obstacles and find safe trajectories in real-time requires efficient solutions. This work presents the MetaHeuristic Real-Time Safe Navigation (MHRTSN) strategy, which combines potential fields with population-based meta-heuristics to optimize trajectory planning and navigation in such environments. The MHRTSN strategy was tested through a series of simulations using different static and dynamic scenarios, comparing the performance of MHRTSN-GA and MHRTSN-PSO versions in terms of displacement, distance traveled, and CPU and clock times. The results demonstrate that both versions provide sub-optimal solutions, with MHRTSN-PSO showing superior performance in terms of required processing time and better convergence compared to MHRTSN-GA when using a small number of individuals. Comparisons with other approaches in the literature showed that MHRTSN generated paths of equivalent length to those of the literature, but in a safer manner. Thus, the proposed approach offers an efficient and safe solution for autonomous navigation in mobile robots, contributing to the advancement of this field in real-world applications. Future work may explore the application of the strategy in physical robotic systems and more complex environments.https://ieeexplore.ieee.org/document/10857271/Autonomous navigationmetaheuristicmobile robotspath planningunknown environment |
| spellingShingle | Micael Balza Mateus A. Goldbarg Sergio N. Silva Lucileide M. D. Silva Marcelo A. C. Fernandes A Real-Time Safe Navigation Proposal for Mobile Robots in Unknown Environments Using Meta-Heuristics IEEE Access Autonomous navigation metaheuristic mobile robots path planning unknown environment |
| title | A Real-Time Safe Navigation Proposal for Mobile Robots in Unknown Environments Using Meta-Heuristics |
| title_full | A Real-Time Safe Navigation Proposal for Mobile Robots in Unknown Environments Using Meta-Heuristics |
| title_fullStr | A Real-Time Safe Navigation Proposal for Mobile Robots in Unknown Environments Using Meta-Heuristics |
| title_full_unstemmed | A Real-Time Safe Navigation Proposal for Mobile Robots in Unknown Environments Using Meta-Heuristics |
| title_short | A Real-Time Safe Navigation Proposal for Mobile Robots in Unknown Environments Using Meta-Heuristics |
| title_sort | real time safe navigation proposal for mobile robots in unknown environments using meta heuristics |
| topic | Autonomous navigation metaheuristic mobile robots path planning unknown environment |
| url | https://ieeexplore.ieee.org/document/10857271/ |
| work_keys_str_mv | AT micaelbalza arealtimesafenavigationproposalformobilerobotsinunknownenvironmentsusingmetaheuristics AT mateusagoldbarg arealtimesafenavigationproposalformobilerobotsinunknownenvironmentsusingmetaheuristics AT sergionsilva arealtimesafenavigationproposalformobilerobotsinunknownenvironmentsusingmetaheuristics AT lucileidemdsilva arealtimesafenavigationproposalformobilerobotsinunknownenvironmentsusingmetaheuristics AT marceloacfernandes arealtimesafenavigationproposalformobilerobotsinunknownenvironmentsusingmetaheuristics AT micaelbalza realtimesafenavigationproposalformobilerobotsinunknownenvironmentsusingmetaheuristics AT mateusagoldbarg realtimesafenavigationproposalformobilerobotsinunknownenvironmentsusingmetaheuristics AT sergionsilva realtimesafenavigationproposalformobilerobotsinunknownenvironmentsusingmetaheuristics AT lucileidemdsilva realtimesafenavigationproposalformobilerobotsinunknownenvironmentsusingmetaheuristics AT marceloacfernandes realtimesafenavigationproposalformobilerobotsinunknownenvironmentsusingmetaheuristics |