{"title":"An extended virtual force field based behavioral fusion with neural networks and evolutionary programming for mobile robot navigation","authors":"K. Im, Se-Young Oh","doi":"10.1109/CEC.2000.870792","DOIUrl":null,"url":null,"abstract":"A local navigation algorithm for mobile robots is proposed, based on the new extended virtual force field (EVFF) concept, neural network-based fusion for the three primitive behaviors generated by the EVFF, and the evolutionary programming-based optimization of the neural network weights. Furthermore, a multi-network version of the above neurally-combined EVFF has been proposed that lends itself not only to an efficient architecture but also to a greatly enhanced generalization capability. These techniques have been verified through both simulation and real experiments under a collection of complex environments.","PeriodicalId":218136,"journal":{"name":"Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CEC.2000.870792","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 16
Abstract
A local navigation algorithm for mobile robots is proposed, based on the new extended virtual force field (EVFF) concept, neural network-based fusion for the three primitive behaviors generated by the EVFF, and the evolutionary programming-based optimization of the neural network weights. Furthermore, a multi-network version of the above neurally-combined EVFF has been proposed that lends itself not only to an efficient architecture but also to a greatly enhanced generalization capability. These techniques have been verified through both simulation and real experiments under a collection of complex environments.