{"title":"基于自适应无气味卡尔曼滤波的鲁棒姿态估计","authors":"C. Antonio, O. Bruno, A. Guilherme","doi":"10.1109/ICRA.2019.8793714","DOIUrl":null,"url":null,"abstract":"This paper presents the robust Adaptive unscented Kalman filter (RAUKF) for attitude estimation. Since the proposed algorithm represents attitude as a unit quaternion, all basic tools used, including the standard UKF, are adapted to the unit quaternion algebra. Additionally, the algorithm adopts an outlier detector algorithm to identify abrupt changes in the UKF innovation and an adaptive strategy based on covariance matching to tune the measurement covariance matrix online. Adaptation and outlier detection make the proposed algorithm robust to fast and slow perturbations such as magnetic field interference and linear accelerations. Experimental results with a manipulator robot suggest that our method overcomes other algorithms found in the literature.","PeriodicalId":73286,"journal":{"name":"IEEE International Conference on Robotics and Automation : ICRA : [proceedings]. IEEE International Conference on Robotics and Automation","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Robust attitude estimation using an adaptive unscented Kalman filter\",\"authors\":\"C. Antonio, O. Bruno, A. Guilherme\",\"doi\":\"10.1109/ICRA.2019.8793714\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents the robust Adaptive unscented Kalman filter (RAUKF) for attitude estimation. Since the proposed algorithm represents attitude as a unit quaternion, all basic tools used, including the standard UKF, are adapted to the unit quaternion algebra. Additionally, the algorithm adopts an outlier detector algorithm to identify abrupt changes in the UKF innovation and an adaptive strategy based on covariance matching to tune the measurement covariance matrix online. Adaptation and outlier detection make the proposed algorithm robust to fast and slow perturbations such as magnetic field interference and linear accelerations. Experimental results with a manipulator robot suggest that our method overcomes other algorithms found in the literature.\",\"PeriodicalId\":73286,\"journal\":{\"name\":\"IEEE International Conference on Robotics and Automation : ICRA : [proceedings]. IEEE International Conference on Robotics and Automation\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-05-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE International Conference on Robotics and Automation : ICRA : [proceedings]. IEEE International Conference on Robotics and Automation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICRA.2019.8793714\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE International Conference on Robotics and Automation : ICRA : [proceedings]. IEEE International Conference on Robotics and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRA.2019.8793714","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Robust attitude estimation using an adaptive unscented Kalman filter
This paper presents the robust Adaptive unscented Kalman filter (RAUKF) for attitude estimation. Since the proposed algorithm represents attitude as a unit quaternion, all basic tools used, including the standard UKF, are adapted to the unit quaternion algebra. Additionally, the algorithm adopts an outlier detector algorithm to identify abrupt changes in the UKF innovation and an adaptive strategy based on covariance matching to tune the measurement covariance matrix online. Adaptation and outlier detection make the proposed algorithm robust to fast and slow perturbations such as magnetic field interference and linear accelerations. Experimental results with a manipulator robot suggest that our method overcomes other algorithms found in the literature.