Comparison of low-cost handheld LiDAR-based SLAM systems for mapping underground tunnels

The use of mobile mapping technologies (MMT) has become increasingly popular across various applications such as forestry, cultural heritage, mining, and civil engineering. While Simultaneous Localization and Mapping (SLAM) algorithms have greatly improved in recent years with regards to accuracy, robustness, and cooperativity, it is important to understand the limitations and strengths of each metrological measurement method to ensure the provision of 3D data of appropriate quality for the selected application. In this study, we perform a comparative analysis of three LiDAR-based handheld mobile mapping systems with survey-grade reference point clouds in a challenging test area of a partially collapsed underground tunnel. We investigate various aspects of 3D data quality, including accuracy and completeness, and present an improved method for 3D data completeness assessment aimed at evaluating SLAM-derived point clouds. The results demonstrate unique and diverse strengths and shortcomings of the tested mapping systems, which provide valuable guidelines for selecting an appropriate system for subterranean applications.