{"title":"Robot navigation in unknown environment using fuzzy logic","authors":"N. Kumar, M. Takács, Z. Vámossy","doi":"10.1109/SAMI.2017.7880317","DOIUrl":null,"url":null,"abstract":"In this paper, a Simulink model for the robot navigation in unknown environment is presented. The robot navigation is handled by two controllers: pure pursuit and fuzzy logic controller. The pure pursuit controller computes a direct path from start to goal position without considering the obstacles in the path. For obstacle avoidance in robot navigation, the fuzzy logic controller is taken. This fuzzy logic controller takes the input from the laser sensor of the robot and gives the change in the angular velocity as output to the robot to avoid the obstacle. The navigation paths resulting from the proposed Simulink model, with and without obstacles in the paths, are shown in figures.","PeriodicalId":105599,"journal":{"name":"2017 IEEE 15th International Symposium on Applied Machine Intelligence and Informatics (SAMI)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE 15th International Symposium on Applied Machine Intelligence and Informatics (SAMI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAMI.2017.7880317","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 18
Abstract
In this paper, a Simulink model for the robot navigation in unknown environment is presented. The robot navigation is handled by two controllers: pure pursuit and fuzzy logic controller. The pure pursuit controller computes a direct path from start to goal position without considering the obstacles in the path. For obstacle avoidance in robot navigation, the fuzzy logic controller is taken. This fuzzy logic controller takes the input from the laser sensor of the robot and gives the change in the angular velocity as output to the robot to avoid the obstacle. The navigation paths resulting from the proposed Simulink model, with and without obstacles in the paths, are shown in figures.