Ehab I. Al Khatib, M. Jaradat, M. Abdel-Hafez, Milad Roigari
{"title":"Multiple sensor fusion for mobile robot localization and navigation using the Extended Kalman Filter","authors":"Ehab I. Al Khatib, M. Jaradat, M. Abdel-Hafez, Milad Roigari","doi":"10.1109/ISMA.2015.7373480","DOIUrl":null,"url":null,"abstract":"Navigation is an important topic in mobile robots. In this paper, an Extended Kalman Filter (EKF) is used to localize a mobile robot equipped with an encoder, compass, IMU and GPS utilizing three different approaches. Subsequently, an input output state feedback linearization (I-O SFL) method is used to control the robot along the desired robot trajectory. The presented algorithms are verified when the robot was steered along two different track shapes. Additionally, the performance of the method is demonstrated when a fault was simulated on the sensors.","PeriodicalId":222454,"journal":{"name":"2015 10th International Symposium on Mechatronics and its Applications (ISMA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"25","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 10th International Symposium on Mechatronics and its Applications (ISMA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISMA.2015.7373480","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 25
Abstract
Navigation is an important topic in mobile robots. In this paper, an Extended Kalman Filter (EKF) is used to localize a mobile robot equipped with an encoder, compass, IMU and GPS utilizing three different approaches. Subsequently, an input output state feedback linearization (I-O SFL) method is used to control the robot along the desired robot trajectory. The presented algorithms are verified when the robot was steered along two different track shapes. Additionally, the performance of the method is demonstrated when a fault was simulated on the sensors.