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-60022018-01-14T23:53:25Z Cognitive map approach for mobility path optimization using multiple objectives genetic algorithm Krishnan, P.S. Paw, J.K.S. Kiong, T.S. 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. 2017-12-08T07:49:38Z 2017-12-08T07:49:38Z 2009 Conference Paper 10.1109/ICARA.2000.4803970 en_US ICARA 2009 - Proceedings of the 4th International Conference on Autonomous Robots and Agents 2009, Article number 4803970, Pages 267-272 |
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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. |
format |
Conference Paper |
author |
Krishnan, P.S. Paw, J.K.S. Kiong, T.S. |
spellingShingle |
Krishnan, P.S. Paw, J.K.S. Kiong, T.S. Cognitive map approach for mobility path optimization using multiple objectives genetic algorithm |
author_facet |
Krishnan, P.S. Paw, J.K.S. Kiong, T.S. |
author_sort |
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 |
2017 |
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1644493819794685952 |
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