High-Precision Surface Inspection: Uncertainty Evaluation within an Accuracy Range of 15μm with Triangulation-based Laser Line Scanners

Triangulation-based range sensors, e.g. laser line scanners, are used for high-precision geometrical acquisition of free-form surfaces, for reverse engineering tasks or quality management. In contrast to classical tactile measuring devices, these scanners generate a great amount of 3D-points in a short period of time and enable the inspection of soft materials. However, for accurate measurements, a number of aspects have to be considered to minimize measurement uncertainties. This study outlines possible sources of uncertainties during the measurement process regarding the scanner warm-up, the impact of laser power and exposure time as well as scanner’s reaction to areas of discontinuity, e.g. edges. All experiments were performed using a fixed scanner position to avoid effects resulting from imaging geometry. The results show a significant dependence of measurement accuracy on the correct adaption of exposure time as a function of surface reflectivity and laser power. Additionally, it is illustrated that surface structure as well as edges can cause significant systematic uncertainties

Challenges and present fields of action at laser scanner based deformation analyses

Due to improved laser scanning technology, laser scanner based deformation analyses are presently widespread. These deformation analyses are no longer based on individual points representing the deformation of an object at selected positions. Instead, they are based on a large number of scan points sampling the whole object. This fact either leads to challenges regarding metrological aspects as well as regarding modeling aspects: –– Estimating and quantifying spatial correlations between scan points and incorporating them into the deformation analysis –– Separating the laser scanners’ internal systematic errors from areal deformations –– Minimizing the bias at areal deformation analyses due to a worse network configuration and limited object knowledge –– Developing freeform parameterizations to reproduce arbitrary areal deformations of an object by individual parameters –– Incorporating an extended uncertainty model considering also model errors due to imperfect knowledge and simplification of the sampled object. –– Only when considering all of these aspects, laser scanner based deformation analyses can benefit from the potential of the areal object sampling. This study aims at naming and reasoning these aspects. Furthermore, it introduces first methodologies and approaches for dealing with them

Aiming at self-calibration of terrestrial laser scanners using only one single object and one single scan

When using terrestrial laser scanners for high quality analyses, calibrating the laser scanner is crucial due to unavoidable misconstruction of the instrument leading to systematic errors. Consequently, the development of calibration fields for laser scanner self-calibration is widespread in the literature. However, these calibration fields altogether suffer from the fact that the calibration parameters are estimated by analyzing the parameter differences of a limited number of substitute objects (targets or planes) scanned from different stations. This study investigates the potential of self-calibrating a laser scanner by scanning one single object with one single scan. This concept is new since it uses the deviation of each sampling point to the scanned object for calibration. Its applicability rests upon the integration of model knowledge that is used to parameterize the scanned object. Results show that this calibration approach is feasible leading to improved surface approximations. However, it makes great demands on the functional model of the calibration parameters, the stochastic model of the adjustment, the scanned object and the scanning geometry. Hence, to gain constant and physically interpretable calibration parameters, further improvement especially regarding functional and stochastic model is demanded

Biased and unbiased estimates based on laser scans of surfaces with unknown deformations

The estimates based on laser scans of surfaces with unknown deformations are biased and not reproducible when changing the scanning geometry. While the existence of a bias is only disadvantageous at some applications, non-reproducible estimates are never desired. Hence, this varying bias and its origin need to be investigated – since this situation has not been examined sufficiently in the literature. Analyzing this situation, the dependence of the estimation on the network configuration is highlighted: the network configuration – studied similarly to geodetic networks – rules about the impact of the deformation. As pointed out, this impact can be altered by manipulating the network configuration. Therefore, several strategies are proposed. These include manipulations of the least-squares adjustment as well as robust estimation. It is revealed that the reproducibility of the estimates can indeed be significantly increased by some of the proposed least-squares manipulations. However, the bias can only be significantly reduced by robust estimation

Laser scanning based growth analysis of plants as a new challenge for deformation monitoring

Nowadays, the areal deformation analysis has become an important task in engineering geodesy. Thereby, not only manmade objects are of high interest, also natural objects, like plant organs, are focused more frequently. Thus, the analysis of leaf growth, i. e. the spatial development of the leaf surface, can be seen as a problem of deformation monitoring. In contrast to classical geodetic tasks, the absolute size of the deformation of the leaf surface is small, but usually great compared to the object size. Due to the optical characteristics of leaf surfaces, the point clouds, commonly acquired with high precision close-up laser scanners, provide a point-to-point distance that is small or equal compared to the measurement accuracy. Thus, the point clouds are usually processed and the leaf area is derived from a triangulation-based surface representation (mesh), resulting in a significant uncertainty of area calculation. In this paper, we illustrate the lacks of the mesh-based leaf area calculation. Using high precision gauge blocks as well as a number of tomato leaves, uncertainties of the area derivation are revealed and evaluated. The application of a B-spline approximation illustrates the advantages of an approximation-based approach and introduces the prospect for further research

Optimizing the Target-based Calibration Procedure of Terrestrial Laser Scanners : Optimierung des zielzeichenbasierten Kalibrierprozesses terrestrischer Laserscanner

Terrestrial laser scanner (TLS) measurements suffer from systematic errors due to internal misalignments. The magnitude of the resulting errors in the point cloud exceeds the magnitude of random errors in many applications. Hence, the task of calibration is important for using laser scanners at accuracy demanding applications. However, user-oriented calibration methods are still an active research subject. The majority of the work on this topic relies on the self-calibration of terrestrial laser scanners using targets. The existing solutions could benefit from further optimization, which would lead to a more efficient and user-friendly calibration process. This work aims at improving existing strategies for the target-based TLS calibration by improving the functional and stochastic model for TLS calibration, as well as conducting a sensitivity analysis to support the calibration field design. Based on the latter results, we implement a permanent calibration facility at the University of Bonn. The latter is used to calibrate a Leica ScanStation P20 terrestrial laser scanner. The success of the calibration is empirically demonstrated by reduced measurement errors at a typical TLS measurement example.Messungen terrestrischer Laserscanner (TLS) weisen systematische Abweichungen aufgrund interner Ausrichtungsabweichungen auf. Die Größe der resultierenden Abweichungen in der Punktwolke übersteigt in vielen Anwendungen die Größe zufälliger Abweichungen. Um Laserscanner für Anwendungen mit hohen Genauigkeitsanforderungen einsetzen zu können, ist daher eine Kalibrierung des Instruments unerlässlich. Kalibrierprozesse, die der Nutzer selber durchführen kann, sind nach wie vor ein aktuelles Forschungsthema. Der Großteil der Arbeit zu diesem Thema beruht auf der Selbstkalibrierung von terrestrischen Laserscannern unter Verwendung von Zielzeichen. Vorhandene Lösungen sind oftmals wenig effizient und/oder wenig benutzerfreundlich; Optimierungen sind hier sinnvoll. Diese Arbeit zielt darauf ab, bestehende Strategien für die zielbasierte TLS-Kalibrierung durch Anpassungen im funktionalen und stochastischen Modell zu verbessern und eine Sensitivitätsanalyse zum Design des Kalibrierfelds durchzuführen. Basierend auf den letztgenannten Ergebnissen installieren wir ein permanentes Kalibrierfeld in einer Einrichtung der Universität Bonn. Für die Leica ScanStation P20 belegen wir den Erfolg der Kalibrierung empirisch durch reduzierte Messabweichungen bei einem typischen TLS-Messbeispiel

Overview on Current Modelling Strategies of Point Clouds for Deformation Analysis : Überblick aktueller Methoden zur Modellierung von Punktwolken für die Deformationsanalyse

Terrestrial laser scanning was used for deformation monitoring of structures and geoscientific objects already at an early stage of its employment for engineering geodetic tasks. This paper gives an overview on current state of the art methods and fields of applications concerning the modelling of point clouds obtained with this measuring technology, by following two aims. On the one hand, the presentation of modelling methods used for retrieving deformation information additional to the ones given in /Bureick et al. 2016/ and /Wunderlich et al. 2016/ of this special issue, is intended. On the other hand, a structuring of the modelling methods with regard to the most common types of analysed measuring objects in engineering geodesy is performed. The aim of this structuring is to create a conceptual link between the model category according to /Ohlmann-Lauber & Schäfer 2011/, the adopted modelling strategy and the object type.Bereits frühzeitige Einsätze des terrestrischen Laserscannings für ingenieurgeodätische Aufgaben haben die Überwachung baulicher Strukturen und geowissenschaftlicher Messobjekte zum Inhalt. Dieser Überblicksartikel beschäftigt sich mit aktuellen Methoden und Anwendungsbereichen der Modellierung von Punktwolken aus terrestrischen Laserscans. Zwei Ziele werden dabei verfolgt: Einerseits werden zu den Beiträgen von /Bureick et al. 2016/ und /Wunderlich et al. 2016/ in diesem Schwerpunktheft ergänzende Modellierungsmethoden zur Herleitung der Deformationsinformation vorgestellt. Das zweite Ziel ist die Strukturierung der Modellierungsmethoden in Bezug zu häufig untersuchten Typen von Messobjekten. Damit soll eine thematische Verbindung zwischen den von /Ohlmann-Lauber & Schäfer 2011/ etablierten Modelltypen zur Ableitung von Deformationen, den Modellierungsmethoden und dem Typus des Messobjekts entstehen

Impact of spatial correlations on the surface estimation based on terrestrial laser scanning

In terms of high precision requested deformation analyses, evaluating laser scan data requires the exact knowledge of the functional and stochastic model. If this is not given, a parameter estimation leads to insufficient results. Simulating a laser scanning scene provides the knowledge of the exact functional model of the surface. Thus, it is possible to investigate the impact of neglecting spatial correlations in the stochastic model. Here, this impact is quantified through statistical analysis. The correlation function, the number of scanning points and the ratio of colored noise in the measurements determine the covariances in the simulated observations. It is shown that even for short correlation lengths of less than 10 cm and a low ratio of colored noise the global test as well as the parameter test are rejected. This indicates a bias and inconsistency in the parameter estimation. These results are transferable to similar tasks of laser scanner based surface approximation