Please use this identifier to cite or link to this item: http://dspace2020.uniten.edu.my:8080/handle/123456789/6002
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dc.contributor.authorKrishnan, P.S.en_US
dc.contributor.authorPaw, J.K.S.en_US
dc.contributor.authorKiong, T.S.en_US
dc.date.accessioned2017-12-08T07:49:38Z-
dc.date.available2017-12-08T07:49:38Z-
dc.date.issued2009-
dc.description.abstractThis 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.en_US
dc.language.isoen_USen_US
dc.relation.ispartofICARA 2009 - Proceedings of the 4th International Conference on Autonomous Robots and Agents 2009, Article number 4803970, Pages 267-272en_US
dc.titleCognitive map approach for mobility path optimization using multiple objectives genetic algorithmen_US
dc.typeConference Paperen_US
dc.identifier.doi10.1109/ICARA.2000.4803970-
item.cerifentitytypePublications-
item.languageiso639-1en_US-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextnone-
item.openairetypeConference Paper-
Appears in Collections:COE Scholarly Publication
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