A Comparison of Registration Methods for SLAM with the M8 Quanergy LiDAR

Abstract

LiDAR based SLAM is becoming affordable by new sensors such as the M8 Quanergy LiDAR, but there is still little work reporting on the accuracy attained with them. In this paper we report on the comparison of three registration methods applied to the estimation of the path followed by the LiDAR sensor and the registration of the overall cloud of points, namely the iterated closest points (ICP), Coherent Point Drift (CPD), and Normal Distributions Transform (NDT) registration methods. In our experiment, we found that the NDT method provides the most robust performance.