Abstract
Terrestrial laser scanning systems are steadily increasing in many fields of engineering, geoscience and architecture namely for fast data acquisition, 3-D modeling and mapping. Similarly to other precision instruments, these systems provide measurements with implicit systematic errors. Systematic errors are physically corrected by manufacturers before delivery and sporadically afterwards. The approach presented herein tackles the raw observables acquired by a laser scanner with additional parameters, a set of geometric calibration parameters that model the systematic error of the instrument to achieve the most accurate point cloud outputs, improving eventual workflow owing to less filtering, better registration and best 3D modeling. This paper presents a fully automatic strategy to calibrate geometrically terrestrial laser scanning datasets. The strategy is tested with multiple scans taken by a FARO FOCUS 3D, a phase-based terrestrial laser scanner. A calibration with local parameters for datasets is undertaken to improve the raw observables and a weighted mathematical index is proposed to select the most significant set of additional parameters. The improvements achieved are exposed, highlighting the necessity of correcting the terrestrial laser scanner before handling multiple data sets.
