{"title":"Optimization based algorithm for correction of systematic odometry errors of mobile robot","authors":"Senka Krivic, Aida Mrzic, J. Velagić, N. Osmic","doi":"10.1109/ASCC.2013.6606226","DOIUrl":null,"url":null,"abstract":"This paper deals with measuring and reduction of odometry errors of a differential-drive mobile robot. For this purpose an algorithm for reducing systematic odometry errors caused by uncertainty of an effective wheelbase and unequal wheel diameters is proposed. The algorithm calculates three calibration coefficients using an optimization based on Levenberg-Marquardt algorithm. These coefficients compensate the effects of unknown values of wheel radius and unknown value of the wheelbase. The mobile robot location during a motion is determined based on visual system measurements. For evaluating the proposed algorithm three different tests are considered: straight line experiment, turn in place experiments, unidirectional square path experiment. Simulation and experimental results demonstrate the effectiveness of the proposed algorithm in reducing the systematic odometry errors.","PeriodicalId":6304,"journal":{"name":"2013 9th Asian Control Conference (ASCC)","volume":"3 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 9th Asian Control Conference (ASCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASCC.2013.6606226","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
This paper deals with measuring and reduction of odometry errors of a differential-drive mobile robot. For this purpose an algorithm for reducing systematic odometry errors caused by uncertainty of an effective wheelbase and unequal wheel diameters is proposed. The algorithm calculates three calibration coefficients using an optimization based on Levenberg-Marquardt algorithm. These coefficients compensate the effects of unknown values of wheel radius and unknown value of the wheelbase. The mobile robot location during a motion is determined based on visual system measurements. For evaluating the proposed algorithm three different tests are considered: straight line experiment, turn in place experiments, unidirectional square path experiment. Simulation and experimental results demonstrate the effectiveness of the proposed algorithm in reducing the systematic odometry errors.