Lidar-only 3D SLAM System Comparative Study

Abstract

Simultaneous localization and mapping (SLAM) is an attractive and hot research topic in computer vision, robotics, and artificial intelligence. Autonomous vehicles driving in unknown environments try to perceive and map the surrounding environment while recognizing their location and trajectory. In this paper, five state-of-the-art open-source 3D lidar-only SLAM algorithms are reviewed: LOAM, LeGO-LOAM, F-LOAM, BALM, and MULLS. We briefly introduce the characteristics of these algorithms. Finally, the experimental comparison is carried out to compare the absolute pose error (APE), efficiency, and operation memory occupation of each algorithm.