COMBINATION OF TLS AND SLAM LIDAR FOR LEVEE MONITORING

Abstract. Monitoring of engineering structures is important for ensuring safety of operation. Traditional surveying methods have proven to be reliable; however, the advent of new point cloud technologies such as terrestrial laser scanning (TLS) and small unmanned aerial systems (sUAS) have provided an unprecedented wealth of data. Furthermore, simultaneous localization and mapping (SLAM) is now able to facilitate the collection of registered point clouds on the fly. SLAM is most successful when applied to indoor environments where the algorithm can identify primitives (points, planes, lines) for registration, but it can be problematic in outdoor settings where there is absence of constructed features. This work includes the collection of SLAM-based LiDAR data along a levee for the purpose of inspection and monitoring. Due to the outdoor setting and absence of man-made features, the resulting point cloud was considerably distorted due to erroneous drift in sensor orientation. A correction algorithm is proposed that relies on reference TLS point cloud data to remove drift distortions identified in the SLAM LiDAR. Results indicate an alignment between the corrected SLAM LiDAR and TLS data of around ±10cm, which is sufficient for general inspection and multi-epoch monitoring of levees. The algorithm is based on common points identified in the TLS and SLAM data and necessitates that the SLAM LiDAR is collected in individual, one-way lines to allow correction of distortions as a function of distance from the starting point. This approach increases the efficiency of LiDAR-based levee monitoring by reducing the time required to survey the levees.