Exploiting Robust Estimators in Phase Correlation of 3D Point Clouds for 6 DoF Pose Estimation

作     者：Yusheng XU Rong HUANG Xiaohua TONG Uwe STILLA Yusheng XU;Rong HUANG;Xiaohua TONG;Uwe STILLA

作者机构：Photogrammetry and Remote SensingTechnical University of MunichMunich 80333Germany College of Surveying and Geo-informaticsTongji UniversityShanghai 200092China 

出 版 物：《Journal of Geodesy and Geoinformation Science》 (测绘学报（英文版）)

年 卷 期：2021年第4卷第3期

页      面：72-90页

学科分类：083002[工学-环境工程] 0830[工学-环境科学与工程（可授工学、理学、农学学位）] 081802[工学-地球探测与信息技术] 08[工学] 0818[工学-地质资源与地质工程] 080203[工学-机械设计及理论] 081602[工学-摄影测量与遥感] 0816[工学-测绘科学与技术] 0802[工学-机械工程] 

基　　金：National Key Research and Development Program of China under Project(No.2018YFB0505400) National Natural Science Foundation of China(No.41631178) 

主　　题：registration phase correlation robust estimators pose estimation 

摘      要：Point cloud registration is a fundamental task in both remote sensing,photogrammetry,and computer vision,which is to align multiple point clouds to the same coordinate *** in LiDAR odometry,by conducting the transformation between two adjacent scans,the pose of the platform can be *** be specific,the goal is to recover the relative six-degree-of-freedom(6 DoF)pose between the source point cloud and the target point *** this paper,we explore the use of robust estimators in the phase correlation when registering two point clouds,enabling a 6 DoF pose estimation between point clouds in a sub-voxel *** estimator is a rule for calculating an estimate of a given quantity based on observed data.A robust estimator is an estimation rule that is insensitive to nonnormality and can estimate parameters of a given objective function from noisy *** proposed registration method is theoretically insensitive to noise and outliers than correspondence-based *** core steps are involved in the method:transforming point clouds from the spatial domain to the frequency domain,decoupling of rotations and translations,and using robust estimators to estimate phase *** the estimation of transformation parameters lies in the calculation of phase shifts,robust estimators play a vital role in shift estimation *** this paper,we have tested the performance of six different robust estimators and provide comparisons and discussions on the contributions of robust estimators in the 3D phase *** point clouds from two urban scenarios and one indoor scene are *** validate the proposed method can reach performance that predominant rotation and translation errors reaching less than 0.5°and 0.5 m,***,the performance of various tested robust estimators is compared and discussed.