Determining geometric error model parameters of a terrestrial laser scanner through two-face, length-consistency, and network methods

Abstract

Terrestrial laser scanners (TLS) are increasingly used in large-scale manufacturing and assembly where required measurement uncertainties are on the order of few tenths of a millimeter or smaller. In order to meet these stringent requirements, systematic errors within a TLS are compensated in situ through self-calibration. In the network method of self-calibration, numerous targets distributed in the work-volume are measured from multiple locations with the TLS to determine the parameters of the TLS error model. In this paper, we propose two new self-calibration methods, the two-face method and the length-consistency method. The length-consistency method is proposed as a more efficient way of realizing the network method where the length between any pair of targets from multiple TLS positions are compared to determine TLS model parameters. The two-face method is a two-step process. In the first step, many model parameters are determined directly from the difference between front-face and back-face measurements of targets distributed in the work volume. In the second step, all remaining model parameters are determined through the length-consistency method. We compare the two-face method, the length-consistency method, and the network method in terms of the uncertainties in the model parameters, and demonstrate the validity of our techniques using a calibrated scale bar and front-face back-face target measurements. The clear advantage of these self-calibration methods is that a reference instrument or calibrated artifacts are not required, thus significantly lowering the cost involved in the calibration process.