Browsing by Author "Schwieger, Volker (Prof. Dr.-Ing. habil. Dr. h.c.)"

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Open Access
An elementary error model for terrestrial laser scanning
(2023) Kerekes, Gabriel; Schwieger, Volker (Prof. Dr.-Ing. habil. Dr. h.c.)
Terrestrial Laser Scanning (TLS) is a recent method in engineering geodesy area-wise deformation analysis. After a TLS scan, the result for each epoch is a point cloud that describes the object’s geometry. For each point cloud, the stochastic properties are important for a reliable decision concerning the current object geometry. Generally, the stochastic properties are described by a stochastic model. Currently, stochastic models for TLS observations are highly disputed and incomplete. A realistic stochastic model is necessary for typical applications like structural deformation analysis for buildings and civil engineering constructions. This work presents a method to define a stochastic model in form of a synthetic variance-covariance matrix (SVCM) for TLS observations. It relies on the elementary error theory defined by Bessel and Hagen at the beginning of the 19th century and adapted for geodetic observations by Pelzer and Schwieger at the end of the 20th century. According to this theory, different types of errors that affect TLS measurements are classified into three groups: non-correlating, functional correlating, and stochastic correlating errors. For each group, different types of errors are studied based on the error sources that affect TLS observations. These types are classified as instrument-specific errors, environment-related errors, and object surface-related errors. Regarding instrument errors, calibration models for high-end laser scanners are studied. For the propagation medium of TLS observations, the effects of air temperature, air pressure and vertical temperature gradient on TLS distances and vertical angles are studied. An approach based on time series theory is used for extracting the spatial correlations between observation lines. For the object’s surface properties, the effect of surface roughness and reflectivity on the distance measurement is considered. Both parameters affect the variances and covariances in the stochastic model. For each of the error types, examples based on own research or literature are given. After establishing the model, four different study cases are used to exemplify the utility of a fully populated SVCM. The scenarios include real objects measured under laboratory and field conditions and simulated objects. The first example outlines the results from the SVCM based on a simulated wall with an analysis of the variance and covariance contribution. In the second study case, the role of the SVCM in a sphere adjustment is highlighted. A third study case presents a deformation analysis of a wooden tower. Finally, the fourth example shows how to derive an optimal TLS station point based on the SVCM trace. All in all, this thesis brings a contribution by defining a new stochastic model based on the elementary error theory in the form a SVCM for TLS measurements. It may be used for purposes such as analysis of error magnitude on scanned objects, adjustment of surfaces, or finding an optimal TLS station point position with regard to predefined criteria.
Open Access
Entwicklung eines tachymeter-basierten Zielsystems
(2023) Hassan, Aiham; Schwieger, Volker (Prof. Dr.-Ing. habil. Dr. h.c.)
Im Rahmen dieser Arbeit wird ein Prototyp für ein flexibel einsetzbares Tachymeterzielsystem (TZS) zur Vermessung verdeckter Objektpunkte entwickelt und empirisch anhand von Testmessungen untersucht. Die Ergebnisse dieser Untersuchungen zeigen, dass das Potenzial des TZS vielversprechend ist. Des Weiteren wird die Methode der lokalen Sensitivitätsanalyse zur Identifikation der wichtigen Eingangsgrößen für das deterministische Modell des TZS eingesetzt. Anhand der Ergebnisse dieser Analyse wird eine Optimierung dieses Modells durchgeführt.
Open Access
Identifikation von Systemmodellen zur dreidimensionalen Zustandsschätzung eines Peilschiffs mit Propellerantrieb unter Verwendung eines Multi-Sensorsystems
(2021) Scheider, Annette; Schwieger, Volker (Prof. Dr.-Ing. habil. Dr. h.c.)
Zur Gewährleistung der Verkehrssicherheit auf deutschen Binnenwasserstraßen wird in regelmäßigen Intervallen die Gewässersohle messtechnisch erfasst. Hierzu werden Peilschiffe eingesetzt, die mit Echoloten ausgerüstet sind. Um die so erfassten Messdaten georeferenzieren zu können, muss das Peilschiff mit geeigneter Sensorik zur Positionsbestimmung ausgerüstet werden. Gegenwärtig werden hierzu meist GNSS-Empfänger eingesetzt. Es zeigt sich jedoch, dass es immer wieder zu Lücken in der so erfassten Trajektorie des Schiffs kommt. Zur Lösung dieses Problems werden Messdaten von mehreren Sensoren (Multi-Sensorsystem) erfasst. Um die Messdaten mittels eines Extended Kalman Filter (EKF) prozessieren zu können, werden mehrere Systemmodelle gebildet, evaluiert und ins EKF integriert. Durch die kombinierte Auswertung können auch in Bereichen ohne GNSS-Empfang Positionslösungen bereitgestellt werden.
Open Access
Towards improved targetless registration and deformation analysis of TLS point clouds using patch-based segmentation
(2023) Yang, Yihui; Schwieger, Volker (Prof. Dr.-Ing. habil. Dr. h.c.)
The geometric changes in the real world can be captured by measuring and comparing the 3D coordinates of object surfaces. Traditional point-wise measurements with low spatial resolution may fail to detect inhomogeneous, anisotropic and unexpected deformations, and thus cannot reveal complex deformation processes. 3D point clouds generated from laser scanning or photogrammetric techniques have opened up opportunities for an area-wise acquisition of spatial information. In particular, terrestrial laser scanning (TLS) exhibits rapid development and wide application in areal geodetic monitoring owing to the high resolution and high quality of acquired point cloud data. However, several issues in the process chain of TLS-based deformation monitoring are still not solved satisfactorily. This thesis mainly focuses on the targetless registration and deformation analysis of TLS point clouds, aiming to develop novel data-driven methods to tackle the current challenges. For most deformation processes of natural scenes, in some local areas no shape deformations occur (i.e., these areas are rigid), and even the deformation directions show a certain level of consistency when these areas are small enough. Further point cloud processing, like stability and deformation analyses, could benefit from the assumptions of local rigidity and consistency of deformed point clouds. In this thesis, thereby, three typical types of locally rigid patches - small planar patches, geometric primitives, and quasi-rigid areas - can be generated from 3D point clouds by specific segmentation techniques. These patches, on the one hand, can preserve the boundaries between rigid and non-rigid areas and thus enable spatial separation with respect to surface stability. On the other hand, local geometric information and empirical stochastic models could be readily determined by the points in each patch. Based on these segmented rigid patches, targetless registration and deformation analysis of deformed TLS point clouds can be improved regarding accuracy and spatial resolution. Specifically, small planar patches like supervoxels are utilized to distinguish the stable and unstable areas in an iterative registration process, thus ensuring only relatively stable points are involved in estimating transformation parameters. The experimental results show that the proposed targetless registration method has significantly improved the registration accuracy. These small planar patches are also exploited to develop a novel variant of the multiscale model-to-model cloud comparison (M3C2) algorithm, which constructs prisms extending from planar patches instead of the cylinders in standard M3C2. This new method separates actual surface variations and measurement uncertainties, thus yielding lower-uncertainty and higher-resolution deformations. A coarse-to-fine segmentation framework is used to extract multiple geometric primitives from point clouds, and rigorous parameter estimations are performed individually to derive high-precision parametric deformations. Besides, a generalized local registration-based pipeline is proposed to derive dense displacement vectors based on segmented quasi-rigid areas that are corresponded by areal geometric feature descriptors. All proposed methods are successfully verified and evaluated by simulated and/or real point cloud data. The choice of proposed deformation analysis methods for specific scenarios or applications is also provided in this thesis.
Open Access
Untersuchungen zum geometrischen Verhalten von Holz mittels optischer Sensoren
(2024) Schmitt, Annette; Schwieger, Volker (Prof. Dr.-Ing. habil. Dr. h.c.)
In Deutschland geht rund ein Drittel des jährlichen CO2-Ausstoßes auf dem Bausektor zurück. Davon ist zwar nur ein Viertel dem Bau von Hochbauten zu zuschreiben. Gerade deshalb müssen im Hochbau Innovationen und alternative Materialien und Bauweisen entwickelt werden, damit Deutschland seine Klimaziele erreicht. Neben dem hohen CO2-Ausstoß hat die Betonbauweise den Nachteil, dass die Rohstoffe von Beton wie zum Beispiel Kies, Sand oder Kalkstein, endliche Ressourcen sind. Eine Alternative zur Betonbauweise ist der jahrtausendealte Holzbau, der in letzten Jahren eine Renaissance erlebt hat. Durch einen nachhaltigen Holzanbau und eine nachhaltige, ressourcenschonende Bauweise kann Holzbau zu einer echten Alternative werden. Jedoch ist Holz ein anisotroper, inhomogener und poröser Werkstoff, dessen Eigenschaften stark richtungsabhängig und abhängig von Umwelteinflüssen sind. Dies macht die Bemessung von Holzbauwerken kompliziert und unattraktiv. Speziell bei Flächentragwerken wie Schalen, die in der Regel sehr filigran sind, haben Umwelteinflüsse wie Feuchte und Temperatur einen Einfluss auf die Standfestigkeit. Daher ist eine regelmäßige Überwachung der Struktur notwendig. Im Bauingenieurwesen werden für solche Aufgaben häufig Dehnmessstreifen eingesetzt. Diese liefern lediglich sehr lokal geltende Messwerte, von denen nur mittels mechanischer Modelle auf das gesamte Objekt geschlossen werden kann. Daher bietet es sich an, für Flächentragwerke optische Sensoren wie zum Beispiel Laserscanner einzusetzen. Im Rahmen dieser Arbeit werden verschiedene Holzobjekte, wie zum Beispiel Platten, Vierkanthölzer und Schalen, unter verschiedenen Umwelteinflüssen, wie Feuchte und Temperatur, untersucht. Ziel ist es dabei, die auftretenden Formänderungen durch Umwelteinflüsse mittels Laserscanner und Lasertracker zu detektieren. Unter anderem werden mehrere Holzplatten in Klimakammern unter definierten Bedingungen untersucht. So wird in einem ersten Versuch der Einfluss von Temperaturänderungen auf eine Holzplatte untersucht. Es zeigt sich, dass dieser zwar sehr gering ist, aber mittels Lasertracker zumindest in radialer Faserrichtung signifikant aufdeckbar ist. In einem weiteren Versuch werden Holzplatten zunächst in einer Klimakammer mit Feuchteregelung bei 95 % Luftfeuchte gelagert und anschließend bei 12 % Luftfeuchte getrocknet. Zwischenzeitlich werden die Platten mittels Lasertracker und Laserscanner vermessen. Hier lassen sich die Verformungen mit dem Lasertracker in allen drei Faserrichtungen signifikant detektieren. Die Messungen mit dem Laserscanner ermöglichen aufgrund des aus der Aufnahmekonfiguration folgenden Registrierungsfehlers keine Aufdeckung der Verformungen, da der Schwellwert für signifikante Verformungen zu hoch ist. In einem weiteren Laborversuch werden die Verformungen durch die Umwelteinflüsse auf belastete Vierkanthölzer untersucht. Auch hierfür kann gezeigt werden, dass der Lasertracker genutzt werden kann. Verifiziert wurden die Ergebnisse hierbei durch eine Finite-Elemente-Simulation, der Materialparameter aus der Literatur zugrunde liegen. Neben den Laborversuchen werden auch Untersuchungen an einem adaptiven Schalentragwerk aus Holz mit dem Laserscanner durchgeführt. Für die Auswertung der Laserscannerdaten wird eine Methode zur Detektion von signifikanten Formänderungen auf Basis von synthetischen Punktfehlern und der Deformationsanalyse implementiert. Alle Ergebnisse der Messungen sind plausibel und mit Literaturangaben vergleichbar, dennoch ist Holz als natürlich wachsender Rohstoff sehr anspruchsvoll und individuell.
Open Access
Use of non-linearity as a characteristic in the selection of filtering algorithms in kinematic positioning
(2020) Pham, Dung; Schwieger, Volker (Prof. Dr.-Ing. habil. Dr. h.c.)
Selection of an optimal filtering algorithm for kinematic positioning systems constitutes one of the most extensively studied applications in the surveyor engineering community. The ability of a filtering algorithm is often assessed through its performance. The performance of a filtering algorithm is frequently evaluated in terms of accuracy and computational time. According to the accuracy parameter, it is often determined by a comparison between true trajectory and the estimated one from an algorithm. However, the true trajectory is commonly unknown in real-life situations, and thus the accuracy of the filtering algorithm cannot be assessed in this manner. Indeed, lack of true trajectory is one of the primary obstacles in the evaluation of the performance of filtering algorithms. The non-linearity of the model, on the other hand, can be determined without any information about the true trajectory and is also associated with the abilities of algorithms. So far, however, very little attention has been paid to the role of the decision of filtering algorithms based on non-linearity. Thus, this study proposes an alternative characteristic in the assessment of the performance of filtering algorithms, which is the non-linearity of the observation model. This research aims to assess the ability of non-linear characteristic for the choice of an optimal filtering algorithm. In this research, the data are simulated by the Monte Carlo method. The abilities of filtering algorithms are investigated on the extended Kalman filter (EKF), unscented Kalman filter (UKF), and particle filter (PF). These algorithms are widely utilized in kinematic positioning, and they are appropriate for various levels of non-linearity. The current study evaluated the influence of the algorithm’s accuracy on three factors: measurement uncertainty, observation geometry, and the number of observations. These algorithms are also assessed on their computational times according to a certain scenario. Regarding measures of non-linearity, three different indicators are examined for the non-linearity of both system and observation models. The coefficient of determination, 1-R2, is utilized as a single indicator to measure the non-linearity of each function of the above models. The M and 1-MVA, known as the deviation of a non-linear function from linearity and multivariate association, respectively, can be used as indicators to quantify the non-linearity of numerous functions of the above models jointly. The 1-MVA indicator is proposed for the first time to quantify the non-linearity of models. From analyses of the accuracy and non-linearity, the relationship between them is determined with changing measurement uncertainty and observation geometry in several scenarios. Based on the established relationship between accuracy and non-linearity, the choice of an optimal algorithm is analyzed through numerical examples. These results indicate that the accuracy of these algorithms is strongly influenced by measurement uncertainty, observation geometry, and the number of observations. The accuracy obtained by PF is higher than that of UKF and EKF. Conversely, the computational time of EKF is shorter than that of UKF and PF. According to measures of non-linearity, the above-proposed indicators are suitable, and the tendency of non-linearity of a model obtained by these indicators is the same. The non-linearity of the system model is small due to the given small amount of standard deviations of the disturbance quantities. Inversely, the non-linearity of the observation model is high due to high measurement uncertainties, or poor observation geometries. The main finding of this research is that both non-linearity of the observation model and position accuracy are influenced by factors of measurement uncertainty and observation geometry. Therefore, the relationship between the position accuracy and the non-linearity of the observation model is established based on these factors. This relationship is strong, which is assessed by the goodness-of-fit value of the best fitting function. In addition, another important result from the present research is that the fitting function described for this relationship changes due to influencing factors of scenarios. The established relationship constitutes the main limitation of this characteristic in application. As a result, instead of accuracy, the non-linearity of the observation model can be employed for the assessment of algorithms when the true trajectory is not available. However, the optimal algorithm can only be selected using these factors in some special cases. For a general case of arbitrary scenarios’ factors, the non-linear characteristic cannot be used for this purpose.