The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publications Copernicus
Articles | Volume XLIII-B1-2022
30 May 2022
 | 30 May 2022


B. Suleymanoglu, M. Soycan, and C. Toth

Keywords: Indoor Mapping, UGV, LiDAR, SLAM, Sensor Fusion

Abstract. Indoor mapping is gaining more interest in both research as well as in emerging applications. Building information systems (BIM) and indoor navigation are probably the driving force behind this trend. For accurate mapping, the platform trajectory reconstruction, or in other words sensor orientation, is essential to reduce or even eliminate for extensive ground control. Simultaneous localization and mapping (SLAM) is the computation problem of how to simultaneously estimate the platform/sensor trajectory while reconstructing the object space; usually, a real-time operation is assumed. Here we investigate the performance of two LiDAR SLAM tools based on using indoor data, acquired by a remotely controlled robot sensor platform. All comparisons were performed on similar datasets using appropriate metrics and encouraging results were obtained as a consequence of initial test studies yet further research is needed to analyse these tools and their accuracy comprehensively.