OSIRIS-REx OLA point cloud registration based on keypoints matching

Ji Feng, Rong Huang, Huan Xie, Yaqiong Wang, Xiangsui Zeng, Jie Chen, Yifan Wang, Hongji Ni
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Abstract

The OSIRIS-Rex Laser Altimeter (OLA) is the first scanning lidar instrument to fly a planetary mission. The OLA scans Bennu for about a month during the Orbit B mission phase and obtains 911 frames of point clouds. Due to the uncertainty of spacecraft position and pointing, there will be offsets between overlapping point clouds. In our method, the point cloud is first projected onto a plane, and then the keypoints are extracted using the SIFT algorithm. Finally, we perform coarse and global adjustments based on keypoints. However, low accuracy of the corresponding keypoints will lead to bad registration. In order to improve the accuracy of keypoints matching and point cloud registration, we use the tuple test and RANSAC algorithm to eliminate mismatched points. For the overlapping point clouds of two frames, the RMSE between keypoints is about 0.04m after registration. The results show that this method can improve the accuracy of point cloud registration to a certain extent and meet the application requirements.
基于关键点匹配的OSIRIS-REx OLA点云配准
OSIRIS-Rex激光高度计(OLA)是第一个执行行星任务的扫描激光雷达仪器。在轨道B任务阶段,OLA对Bennu进行了大约一个月的扫描,获得了911帧的点云。由于航天器位置和指向的不确定性,重叠点云之间会产生偏移。该方法首先将点云投影到平面上,然后使用SIFT算法提取关键点。最后,根据关键点进行粗调整和全局调整。然而,相应的关键点精度低,会导致配准不良。为了提高关键点匹配和点云配准的精度,我们使用元组测试和RANSAC算法来消除不匹配点。对于两帧重叠的点云,配准后关键点之间的RMSE约为0.04m。结果表明,该方法能在一定程度上提高点云配准的精度,满足应用要求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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