M. Carratù, S. D. Iacono, A. Pietrosanto, V. Paciello
{"title":"Self-alignment procedure for IMU in automotive context","authors":"M. Carratù, S. D. Iacono, A. Pietrosanto, V. Paciello","doi":"10.1109/INDIN41052.2019.8972211","DOIUrl":null,"url":null,"abstract":"In this paper a method for IMU and MARG alignment in two wheeled vehicles suspension control system is presented. Nowadays, the initial alignment of the device with respect to the vehicle frame is obtained thanks to algorithms available in literature based on the estimation of the attitude and simple geometrical rules to determine. However, these classical procedures do not allow to obtain a precise measurement of the initial device attitude. The proposed method aims to fuse data between classical methods results and GPS/GNSS signals to improve the existing methodologies. The algorithm has been implemented on a low cost platform to demonstrate its feasibility and it has been tested on a motorcycle during real ride conditions. The performed experiments have demonstrated the repeatability of the procedures and its high accuracy.","PeriodicalId":260220,"journal":{"name":"2019 IEEE 17th International Conference on Industrial Informatics (INDIN)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 17th International Conference on Industrial Informatics (INDIN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INDIN41052.2019.8972211","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
In this paper a method for IMU and MARG alignment in two wheeled vehicles suspension control system is presented. Nowadays, the initial alignment of the device with respect to the vehicle frame is obtained thanks to algorithms available in literature based on the estimation of the attitude and simple geometrical rules to determine. However, these classical procedures do not allow to obtain a precise measurement of the initial device attitude. The proposed method aims to fuse data between classical methods results and GPS/GNSS signals to improve the existing methodologies. The algorithm has been implemented on a low cost platform to demonstrate its feasibility and it has been tested on a motorcycle during real ride conditions. The performed experiments have demonstrated the repeatability of the procedures and its high accuracy.
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