{"title":"Modified histogramic technique for mobile robot indoor environment mapping based on uniform random distribution","authors":"Dinko Osmankovic, J. Velagić","doi":"10.1109/AMC.2012.6197140","DOIUrl":null,"url":null,"abstract":"In this paper we introduce a modification of histogramic in - motion mapping technique for mobile robots. This modification is based on the premise that precise sonar model is not required for accurate map building. We use uniform random distribution approach to replace the probabilistic model of sonar sensor. Problem of localization of the mobile robot is also discussed as it is very important for the precise mapping of the environment. For this purpose we used odometry measurements processed by Extended Kalman Filter for the robot localization. It is shown that this method gives precise maps of an environment in Player/Stage simulator, and also with real world scenarios.","PeriodicalId":6439,"journal":{"name":"2012 12th IEEE International Workshop on Advanced Motion Control (AMC)","volume":"31 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2012-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 12th IEEE International Workshop on Advanced Motion Control (AMC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AMC.2012.6197140","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In this paper we introduce a modification of histogramic in - motion mapping technique for mobile robots. This modification is based on the premise that precise sonar model is not required for accurate map building. We use uniform random distribution approach to replace the probabilistic model of sonar sensor. Problem of localization of the mobile robot is also discussed as it is very important for the precise mapping of the environment. For this purpose we used odometry measurements processed by Extended Kalman Filter for the robot localization. It is shown that this method gives precise maps of an environment in Player/Stage simulator, and also with real world scenarios.