{"title":"Behavior control of a mobile robot based on Fuzzy logic and Neuro Fuzzy approaches for monitoring wall","authors":"Hanene Rouabah, C. Abdelmoula, M. Masmoudi","doi":"10.1109/DTIS.2012.6232944","DOIUrl":null,"url":null,"abstract":"This work describes the design and development of controllers based on artificial intelligence tried on a newly design of a mobile robot type-vehicle to control behavior for monitoring wall. Two approaches have been optimized and developed to control the robot: The first one is based on Fuzzy logic. This control algorithm combines the different sensory information and provides a suitable control command allowing the mobile robot to follow the wall deviations. The second approach consists of applying a hybrid-type Neuro-Fuzzy ANFIS controller for the same task. This controller combines the advantages of Fuzzy logic and Neural Networks. Simulations results are presented and implemented with VHDL using ANFIS architecture.","PeriodicalId":114829,"journal":{"name":"7th International Conference on Design & Technology of Integrated Systems in Nanoscale Era","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"7th International Conference on Design & Technology of Integrated Systems in Nanoscale Era","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DTIS.2012.6232944","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
This work describes the design and development of controllers based on artificial intelligence tried on a newly design of a mobile robot type-vehicle to control behavior for monitoring wall. Two approaches have been optimized and developed to control the robot: The first one is based on Fuzzy logic. This control algorithm combines the different sensory information and provides a suitable control command allowing the mobile robot to follow the wall deviations. The second approach consists of applying a hybrid-type Neuro-Fuzzy ANFIS controller for the same task. This controller combines the advantages of Fuzzy logic and Neural Networks. Simulations results are presented and implemented with VHDL using ANFIS architecture.