{"title":"Blanche: Position Estimation For An Autonomous Robot Vehicle","authors":"I. Cox","doi":"10.1109/IROS.1989.637941","DOIUrl":null,"url":null,"abstract":"This paper describes the position estimation system for an autonomous robot vehicle called Blanche, which is designed for use in structured office or factory environments. Blanche is intended to be low cost, depending on only two sensors, an optical rangefinder and odometry. Briefly, the position estimation system consists of odometry supplemented with a fast, robust matching algorithm which determines the congruence between the range data and a 2D map of its environment. This is used to correct any errors existing in the odometry estimate. The integration of odometry with fast, robust matching allows for accurate estimates of the robot’s position and accurate estimates of the robot’s position allow for fast, robust matching. That is, the system is self sustaining.","PeriodicalId":332317,"journal":{"name":"Proceedings. IEEE/RSJ International Workshop on Intelligent Robots and Systems '. (IROS '89) 'The Autonomous Mobile Robots and Its Applications","volume":"99 3","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1989-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"128","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. IEEE/RSJ International Workshop on Intelligent Robots and Systems '. (IROS '89) 'The Autonomous Mobile Robots and Its Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IROS.1989.637941","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 128
Abstract
This paper describes the position estimation system for an autonomous robot vehicle called Blanche, which is designed for use in structured office or factory environments. Blanche is intended to be low cost, depending on only two sensors, an optical rangefinder and odometry. Briefly, the position estimation system consists of odometry supplemented with a fast, robust matching algorithm which determines the congruence between the range data and a 2D map of its environment. This is used to correct any errors existing in the odometry estimate. The integration of odometry with fast, robust matching allows for accurate estimates of the robot’s position and accurate estimates of the robot’s position allow for fast, robust matching. That is, the system is self sustaining.