Mohammad Ali Zaiter, R. Lherbier, G. Faour, O. Bazzi, J. Noyer
{"title":"3D LiDAR Extrinsic Calibration Method using Ground Plane Model Estimation","authors":"Mohammad Ali Zaiter, R. Lherbier, G. Faour, O. Bazzi, J. Noyer","doi":"10.1109/ICCVE45908.2019.8964949","DOIUrl":null,"url":null,"abstract":"In the context of road defects detection, especially potholes detection, using a 3D LiDAR mounted on a vehicle seems to be an interesting way to provide location and geometric information about the defects. In this paper, an extrinsic calibration method is proposed, to merge all the LiDAR frames in a common reference frame and to define the positioning of the sensor. This method depends mainly on the geometrical ground impact model in order to estimate the LiDAR extrinsic parameters by successive steps algorithm: fitting plane, Euler's angles estimation of rotation, height estimation and parameters optimization. Results are presented in terms of precision and robustness against the LiDAR range accuracy proving the performance of this calibration method.","PeriodicalId":384049,"journal":{"name":"2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCVE45908.2019.8964949","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
In the context of road defects detection, especially potholes detection, using a 3D LiDAR mounted on a vehicle seems to be an interesting way to provide location and geometric information about the defects. In this paper, an extrinsic calibration method is proposed, to merge all the LiDAR frames in a common reference frame and to define the positioning of the sensor. This method depends mainly on the geometrical ground impact model in order to estimate the LiDAR extrinsic parameters by successive steps algorithm: fitting plane, Euler's angles estimation of rotation, height estimation and parameters optimization. Results are presented in terms of precision and robustness against the LiDAR range accuracy proving the performance of this calibration method.