Inertial LiDAR Motion Distortion Correction on Spherical Mobile Mapping Systems for Planetary Exploration

In this paper, we present an algorithm countering the motion distortion observed in LiDAR point clouds due to the inherent inertial rotations when recorded with a spherical mobile mapping system. State-of-the-art motion distortion correction algorithms focus on more rotationally restricted systems, such as UAV, rovers, or cars, where often a "dead-reckoning" approach is utilized to account for the vehicles linear velocity. Thus, the algorithm presented in this paper is based on a motion model for spherical systems, taking only the angular velocities into account. We show, despite explicitly omitting a model for the linear velocity of the scanner, and assuming constant angular velocity between two frames, that our approach outperforms state-of-the-art algorithms which use a false model for the linear velocities. To verify this, we test our algorithm on 3D point clouds recorded with a Livox MID-100 mounted on a spherical mobile mapping system, and compare the accuracy to an algorithm proposed in the Livox-SDK. To do this, we have ground truth point clouds available from a terrestrial laser scanner (TLS). Our algorithm consistently reduces the motion distortion from low (5 Hz) to high (50 Hz) LiDAR sampling frequencies, such that the point clouds are well-suited for further processing steps such as odometry or mapping. The code for our algorithm is open source [1].