Development of a Horizontally Rotating 3D LiDAR System for Control Point Surveying in Lunar Environments using a Rover Harada Amane(a), Tomoki Sugihara(a), Rikako Shigefuji(a), Masanori Takigawa(b), Keitaro Kitamura(b),Takahiro Hiramatu(b), Tomowo Ohga(b), Hisatoshi Sano(b), Taizo Kobayashi(c) ,Masafumi Nakagawa(a)
a)Shibaura Institute of Technology
b)Asia Air Survey Co., Ltd.
c) Ritsumeikan University
Abstract
Robust surveying technologies are necessary for lunar development due to extreme environments, high transportation costs, and the need for accurate construction. Conventional image measurements struggle with regolith-covered surfaces, and GNSS is unavailable complicate LiDAR-based SLAM. Therefore, we have developed a LiDAR-SfM/MVS that combines LiDAR-SLAM with spherical markers for control point surveying and SfM/MVS for clouds. This method uses a turntable mounted 3D-LiDAR and multidirectional cameras. Previous experiments using a horizontal scanning 3D-LiDAR mounted on a rover showed the narrow vertical angle range of laser scanning prevents the rover from climing inclined surfaces when no vertical objects exist in the measured environment. To address this isssue, we developed a terrestrial LiDAR-like 3D measurement system consisting of a vertical scanning 3D-LiDAR mounted on a horizontal turntable. We also developed a self-calibration method based on point cloud matching with the iterative closest point algorithm to estimate the internal orientation parameters consisting of the line-of-sight offset angle, the rolling distortion angle, and the rotation axis offset distance. Experiments conducted on a lunar-simulated terrain confirmed that the proposed method achieved a spherical marker fitting accuracy of 0.01m or less for center position estimation. Registration errors using total station survey results averaged 0.0121m, and sequential LiDAR point cloud registration showed an average residual of 0.0271m, which is consistent with LiDAR^s 0.03m ranging accuracy. The LiDAR-SfM/MVS system generated dense point clouds with a point density of 0.01m or less, as well as an accuracy of 0.03m (RMSE) in registration between LiDAR and SfM/MVS point clouds. These results confirms that the proposed method meets the required measurement accuracy of 0.10m for unmanned construction. Future work will focus on hardening the sensor system to prepare it for the lunar environment.
