Calibration of Panoramic Terrestrial Laser Scanners using Planar Patches

Abstract. Using point clouds captured by Terrestrial Laser Scanners for measurement tasks with high-quality requirements is well established in engineering geodesy. However, mechanical imperfections within the scanners introduce systematic deviations into the captured point clouds, exceeding the impact of random measurement noise. Calibrating the scanners by estimating these internal imperfections allows these systematic errors to be corrected, thereby preventing misinterpretations of the measurement results. In this work, we implement a methodology that allows users of Terrestrial Laser Scanners to independently determine calibration parameters for panorama scanners and to correct the resulting point clouds using planar patches extracted directly from the captured data. Our work extends existing approaches by using a comprehensive calibration model of the National Institute of Standards and Technology (NIST), including all existing 18 calibration parameters. It relies on a network-based method to estimate transformations between TLS stations, utilizing plane parameters. In this process, calibration parameters are included as supplementary parameters. Additionally, we evaluate the methodology using a real-world point cloud of a water dam and demonstrate that it achieves a substantial reduction in systematic deviations in the magnitude of several millimeters, so that mainly random noise remain. Furthermore, by estimating calibration parameters within a dedicated state-of-the-art calibration field, we demonstrate that our method achieves a reduction in systematic errors comparable in magnitude to established calibration procedures. Although the nominal values of the estimated calibration parameters differ due to correlations among parameters, this performance is obtained without requiring specialized calibration environments.