Cognitive map approach for mobility path optimization using multiple objectives genetic algorithm
This paper describes the evolutionary planning strategies for mobile robot to move along the streamlined collision-free paths in a known static environment. The Cognitive Map method is combined with genetic algorithm to derive the mobile robot optimal moving path towards its goal functions. In this...
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my.uniten.dspace-308412024-04-18T10:39:09Z Cognitive map approach for mobility path optimization using multiple objectives genetic algorithm Krishnan P.S. Paw J.K.S. Kiong T.S. 36053261400 22951210700 15128307800 Cognitive map approach Mobile robots Multiple objective genetic algorithm Path optimization Autonomous agents Conformal mapping Function evaluation Genetic algorithms Mobile robots Optimization Cognitive map approach Cognitive maps Collision-free paths Fitness functions Goal functions Hybrid method Key parameters Moving obstacles Moving path Multi objective Multiple objective genetic algorithm Multiple objectives Path optimization Path optimizations Planning strategies Simulation result Static environment Stationary obstacles Navigation This paper describes the evolutionary planning strategies for mobile robot to move along the streamlined collision-free paths in a known static environment. The Cognitive Map method is combined with genetic algorithm to derive the mobile robot optimal moving path towards its goal functions. In this study, multi-objectives genetic algorithm (MOGA) is utilized due to there are more than one objective need to be achieved while planning for the robot moving path. Goal-factor and obstacle-factor are the key parameters incorporated in the MOGA fitness functions. The simulation results showed that the hybrid Cognitive Map approach with MOGA is capable of navigating a robot situated among non-moving obstacles. The proposed hybrid method demonstrates good performance in planning and optimizing mobile robot moving path with stationary obstacles and goal. �2009 IEEE. Final 2023-12-29T07:54:23Z 2023-12-29T07:54:23Z 2009 Conference Paper 10.1109/ICARA.2000.4803970 2-s2.0-66149171613 https://www.scopus.com/inward/record.uri?eid=2-s2.0-66149171613&doi=10.1109%2fICARA.2000.4803970&partnerID=40&md5=dc78b03732e526c0dd57a6f2f38321ba https://irepository.uniten.edu.my/handle/123456789/30841 4803970 267 272 Scopus |
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Cognitive map approach Mobile robots Multiple objective genetic algorithm Path optimization Autonomous agents Conformal mapping Function evaluation Genetic algorithms Mobile robots Optimization Cognitive map approach Cognitive maps Collision-free paths Fitness functions Goal functions Hybrid method Key parameters Moving obstacles Moving path Multi objective Multiple objective genetic algorithm Multiple objectives Path optimization Path optimizations Planning strategies Simulation result Static environment Stationary obstacles Navigation |
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Cognitive map approach Mobile robots Multiple objective genetic algorithm Path optimization Autonomous agents Conformal mapping Function evaluation Genetic algorithms Mobile robots Optimization Cognitive map approach Cognitive maps Collision-free paths Fitness functions Goal functions Hybrid method Key parameters Moving obstacles Moving path Multi objective Multiple objective genetic algorithm Multiple objectives Path optimization Path optimizations Planning strategies Simulation result Static environment Stationary obstacles Navigation Krishnan P.S. Paw J.K.S. Kiong T.S. Cognitive map approach for mobility path optimization using multiple objectives genetic algorithm |
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This paper describes the evolutionary planning strategies for mobile robot to move along the streamlined collision-free paths in a known static environment. The Cognitive Map method is combined with genetic algorithm to derive the mobile robot optimal moving path towards its goal functions. In this study, multi-objectives genetic algorithm (MOGA) is utilized due to there are more than one objective need to be achieved while planning for the robot moving path. Goal-factor and obstacle-factor are the key parameters incorporated in the MOGA fitness functions. The simulation results showed that the hybrid Cognitive Map approach with MOGA is capable of navigating a robot situated among non-moving obstacles. The proposed hybrid method demonstrates good performance in planning and optimizing mobile robot moving path with stationary obstacles and goal. �2009 IEEE. |
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36053261400 |
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36053261400 Krishnan P.S. Paw J.K.S. Kiong T.S. |
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Conference Paper |
author |
Krishnan P.S. Paw J.K.S. Kiong T.S. |
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Krishnan P.S. |
title |
Cognitive map approach for mobility path optimization using multiple objectives genetic algorithm |
title_short |
Cognitive map approach for mobility path optimization using multiple objectives genetic algorithm |
title_full |
Cognitive map approach for mobility path optimization using multiple objectives genetic algorithm |
title_fullStr |
Cognitive map approach for mobility path optimization using multiple objectives genetic algorithm |
title_full_unstemmed |
Cognitive map approach for mobility path optimization using multiple objectives genetic algorithm |
title_sort |
cognitive map approach for mobility path optimization using multiple objectives genetic algorithm |
publishDate |
2023 |
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1806426374023413760 |
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13.214268 |