Evaluating Positioning Uncertainty of Spherical Targets in Laser Scanning

2012 ◽  
Vol 523-524 ◽  
pp. 356-361
Author(s):  
Ichiro Tanaka ◽  
Hiroshi Masuda ◽  
Masakazu Enomoto ◽  
Kenjiro Takai Miura
Keyword(s):  
Least Squares ◽  
Laser Scanning ◽  
Large Diameter ◽  
Point Clouds ◽  
Least Squares Fitting ◽  
Laser Scanners ◽  
Standard Deviations

Spherical targets are useful for registration of point-clouds. In this paper we discuss the positioning uncertainty by laser scanners. We measured spheres of relatively large diameter from about 9m distance, and calculated their positions by the least-squares fitting. The scanning was iterated thirty times and the standard deviations of fitting result were calculated to indicate positioning uncertainty. The result shows smaller positioning uncertainty in comparison with the range noise listed in the specifications.

scholarly journals L1-NORM FITTING OF ELLIPTIC PARABOLOIDS WITH PRIOR INFORMATION FOR ENHANCED CONIFEROUS TREE LOCALIZATION IN ALS POINT CLOUDS

2019 ◽  
Vol IV-2/W5 ◽  
pp. 429-436
Author(s):  
P. Polewski ◽  
W. Yao ◽  
M. Heurich
Keyword(s):  
Least Squares ◽  
Laser Scanning ◽  
Point Clouds ◽  
Absolute Error ◽  
Quadratic Program ◽  
L1 Norm ◽  
Individual Tree ◽  
Elliptic Paraboloid ◽  
Least Squares Fitting ◽  
Crown Shape

<p><strong>Abstract.</strong> Airborne laser scanning (ALS) is an established tool for deriving various tree characteristics in forests. In some applications, an accurate pointwise estimate of the tree position is required. For dense data acquired by TLS or UAV-mounted scanners, this can be achieved by locating the stem, whose center coordinates are then used for deriving the planimetric tree position. However, in case of standard ALS data this is often not an option due to the low probability of obtaining stem hits in operational scenarios of forest mapping campaigns. This paper presents an alternative, indirect approach where the tree position is approximated as the center of a quadric surface which best represents the tree crown shape. The study targets coniferous trees due to their distinct crown shape which may be approximated by an elliptic paraboloid. It is assumed that individual tree point clusters are given and the task is to find the tree center for each cluster. We first consider the general problem of fitting an elliptic paraboloid with a known axis and an L1 residual norm error criterion, which is more robust to outliers compared to least-squares fitting. We formulate this problem as a quadratically constrained quadratic program (QCQP), and show how prior knowledge on the crown shape and center position can be incorporated. Next, a computationally simpler problem is considered where the paraboloid semiaxis lengths are constrained to be equal, and a corresponding linear program is constructed. Experiments on ALS datasets of forest plots from Bavaria, Germany and Oregon, USA reveal that a reduction in median tree position error of up to 20% can be attained compared to both least-squares fitting and other baseline techniques, resulting in an absolute error of ca. 22&amp;thinsp;cm on both datasets.</p>

scholarly journals A sensor skid for precise 3D modeling of production lines

2014 ◽  
Vol II-5 ◽  
pp. 117-122 ◽  
Author(s):  
J. Elseberg ◽  
D. Borrmann ◽  
J. Schauer ◽  
A. Nüchter ◽  
D. Koriath ◽  
...  
Keyword(s):  
3D Modeling ◽  
Production Line ◽  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Point Clouds ◽  
Production Lines ◽  
3D Point Clouds ◽  
Laser Scanners ◽  
Rapid Characterization

Motivated by the increasing need of rapid characterization of environments in 3D, we designed and built a sensor skid that automates the work of an operator of terrestrial laser scanners. The system combines terrestrial laser scanning with kinematic laser scanning and uses a novel semi-rigid SLAMmethod. It enables us to digitize factory environments without the need to stop production. The acquired 3D point clouds are precise and suitable to detect objects that collide with items moved along the production line.

scholarly journals Estimating Control Points for B-Spline Surfaces Using Fully Populated Synthetic Variance–Covariance Matrices for TLS Point Clouds

2021 ◽  
Vol 13 (16) ◽  
pp. 3124
Author(s):  
Jakob Raschhofer ◽  
Gabriel Kerekes ◽  
Corinna Harmening ◽  
Hans Neuner ◽  
Volker Schwieger
Keyword(s):  
Laser Scanning ◽  
Point Clouds ◽  
Covariance Matrices ◽  
Geometric Modelling ◽  
Deformation Analysis ◽  
Control Points ◽  
B Splines ◽  
Spline Surfaces ◽  
Standard Deviations ◽  
The Impact

A flexible approach for geometric modelling of point clouds obtained from Terrestrial Laser Scanning (TLS) is by means of B-splines. These functions have gained some popularity in the engineering geodesy as they provide a suitable basis for a spatially continuous and parametric deformation analysis. In the predominant studies on geometric modelling of point clouds by B-splines, uncorrelated and equally weighted measurements are assumed. Trying to overcome this, the elementary errors theory is applied for establishing fully populated covariance matrices of TLS observations that consider correlations in the observed point clouds. In this article, a systematic approach for establishing realistic synthetic variance–covariance matrices (SVCMs) is presented and afterward used to model TLS point clouds by B-splines. Additionally, three criteria are selected to analyze the impact of different SVCMs on the functional and stochastic components of the estimation results. Plausible levels for variances and covariances are obtained using a test specimen of several dm—dimension. It is used to identify the most dominant elementary errors under laboratory conditions. Starting values for the variance level are obtained from a TLS calibration. The impact of SVCMs with different structures and different numeric values are comparatively investigated. Main findings of the paper are that for the analyzed object size and distances, the structure of the covariance matrix does not significantly affect the location of the estimated surface control points, but their precision in terms of the corresponding standard deviations. Regarding the latter, properly setting the main diagonal terms of the SVCM is of superordinate importance compared to setting the off-diagonal ones. The investigation of some individual errors revealed that the influence of their standard deviation on the precision of the estimated parameters is primarily dependent on the scanning distance. When the distance stays the same, one-sided influences on the precision of the estimated control points can be observed with an increase in the standard deviations.

The Advantages of Using Laser Scanners in Surveying in Protected Sites

2015 ◽  
pp. 382-402
Author(s):  
Gülhan Benli
Keyword(s):  
Protected Areas ◽  
Point Cloud ◽  
Laser Scanning ◽  
Three Dimensional ◽  
Terrestrial Laser Scanning ◽  
Point Clouds ◽  
Point Cloud Data ◽  
Cloud Data ◽  
Laser Scanners ◽  
Point Data

Since the 2000s, terrestrial laser scanning, as one of the methods used to document historical edifices in protected areas, has taken on greater importance because it mitigates the difficulties associated with working on large areas and saves time while also making it possible to better understand all the particularities of the area. Through this technology, comprehensive point data (point clouds) about the surface of an object can be generated in a highly accurate three-dimensional manner. Furthermore, with the proper software this three-dimensional point cloud data can be transformed into three-dimensional rendering/mapping/modeling and quantitative orthophotographs. In this chapter, the study will present the results of terrestrial laser scanning and surveying which was used to obtain three-dimensional point clouds through three-dimensional survey measurements and scans of silhouettes of streets in Fatih in Historic Peninsula in Istanbul, which were then transposed into survey images and drawings. The study will also cite examples of the facade mapping using terrestrial laser scanning data in Istanbul Historic Peninsula Project.

scholarly journals Influence of DEM Elaboration Methods on the USLE Model Topographical Factor Parameter on Steep Slopes

2020 ◽  
Vol 12 (21) ◽  
pp. 3540
Author(s):  
Edyta Kruk ◽  
Przemysław Klapa ◽  
Marek Ryczek ◽  
Krzysztof Ostrowski
Keyword(s):  
Soil Loss ◽  
Laser Scanning ◽  
Point Clouds ◽  
Surface Flow ◽  
Aerial Photographs ◽  
Data Generation ◽  
Additional Time ◽  
Slope Length ◽  
Erosion Processes ◽  
Laser Scanners

Runoff erosion is an important theme in hydrological investigations. Models assessing soil erosion are based on various algorithms that determine the relief coefficient using rasterized digital elevation models (DEMs). For evaluation of soil loss, the most-used model worldwide is the USLE (Universal Soil Loss Equation), where the most essential part is the LS parameter, which is, in turn, generated from two parameters: L (slope length coefficient) and S (slope inclination). The most significant limitation of LS is the difficulty in obtaining the data needed to generate detailed DEMs. We investigated three popular data generation methods: aerial photographs (AP), aerial laser scanning (ALS), and terrestrial laser scanning (TLS) by assessing the quality and effect of DEMs generated from each method over an area of 40 m × 200 m in Silesia, Poland. Additionally, the relationship between particular LSUSLE  parameter components was carried out based on its final distribution. Our results show that resolution strongly influences DEMs and the LSUSLE  parameters. We found a strong relationship between the degree of height data resolution and the accuracy level of the calculated parameters. Based on our investigations we confirmed the highest influence on the LSUSLE  came from the S parameter. Additionally, we concluded that in examinations over large areas, terrestrial laser scanners are not ideal; the benefits of their additional accuracy are outweighed by the additional time and labor consumption; in addition, terrestrial-based scans are sometimes not possible due to ground obstacles the limited scope of most lasers. Aerial photographs or point clouds generated by aerial laser scanners are sufficient for most purposes connected with surface flow, and further developments can be based on the use of these techniques for obtaining ground information for modeling erosion processes.

scholarly journals COMPARISON WITH ACCURACY OF TERRESTRIAL LASER SCANNER BY USING POINT CLOUD ALIGNED WITH SHAPE MATCHING AND BEST FITTING METHODS

2019 ◽  
Vol XLII-2/W9 ◽  
pp. 535-541 ◽  
Author(s):  
T. Ogawa ◽  
Y. Hori
Keyword(s):  
Laser Scanning ◽  
Shape Matching ◽  
Laser Scanner ◽  
Point Clouds ◽  
Random Errors ◽  
Laser Scanners ◽  
Error Distributions ◽  
Best Fitting ◽  
Scan Data ◽  
Fitting In

<p><strong>Abstract.</strong> Recently operation systems of laser scanning have been obviously improved; for instance shape matching has been equipped with software on a post processing stage so measurement without any targets is a prerequisite condition of field surveying with laser scanners. Moreover a shape matching method enables us to easily register a pair of point clouds with some errors even if those data are scanned by several type scanners. Those slightly errors can influence accuracy of alignments if the object is large to require a lot of scans. Laser scanning data has random errors and accuracy of alignments can be improved by matching error distributions of pairs of point clouds to natural distributions. This method is called “best fitting” in contrast “shape matching” in a software, PolyWorks |Inspector. In this paper, accuracy of alignments between shape matching and best fitting is discussed. The scan data of three phaseshift laser scanners (FARO Focus 3D MS120, FARO Focus 3D X330 and Z+F Imager 5016) and two time-of-flight scanners (Leica BLK 360 and Leica Scan station C5) are used for analyses. Accuracy of alignments by using shape matching and best fitting methods is demonstrated by showing points of scan data with histograms of error distributions.</p>

scholarly journals Non-linear least squares fitting of Bézier surfaces to unstructured point clouds

2021 ◽  
Vol 6 (4) ◽  
pp. 3142-3159
Author(s):  
Joseph Lifton ◽  
◽  
Tong Liu ◽  
John McBride ◽  
◽  
...  
Keyword(s):  
Least Squares ◽  
Point Clouds ◽  
Linear Least Squares ◽  
Least Squares Fitting ◽  
Bézier Surfaces ◽  
Non Linear ◽  
Bezier Surfaces

scholarly journals Measurement of Forest Inventory Parameters with Apple iPad Pro and Integrated LiDAR Technology

2021 ◽  
Vol 13 (16) ◽  
pp. 3129
Author(s):  
Christoph Gollob ◽  
Tim Ritter ◽  
Ralf Kraßnitzer ◽  
Andreas Tockner ◽  
Arne Nothdurft
Keyword(s):  
Data Acquisition ◽  
Forest Inventory ◽  
Laser Scanning ◽  
Point Clouds ◽  
Acquisition Time ◽  
Ecosystem Monitoring ◽  
Individual Tree ◽  
3D Point Clouds ◽  
Apple Ipad ◽  
Laser Scanners

The estimation of single tree and complete stand information is one of the central tasks of forest inventory. In recent years, automatic algorithms have been successfully developed for the detection and measurement of trees with laser scanning technology. Nevertheless, most of the forest inventories are nowadays carried out with manual tree measurements using traditional instruments. This is due to the high investment costs for modern laser scanner equipment and, in particular, the time-consuming and incomplete nature of data acquisition with stationary terrestrial laser scanners. Traditionally, forest inventory data are collected through manual surveys with calipers or tapes. Practically, this is both labor and time-consuming. In 2020, Apple implemented a Light Detection and Ranging (LiDAR) sensor in the new Apple iPad Pro (4th Gen) and iPhone Pro 12. Since then, access to LiDAR-generated 3D point clouds has become possible with consumer-level devices. In this study, an Apple iPad Pro was tested to produce 3D point clouds, and its performance was compared with a personal laser scanning (PLS) approach to estimate individual tree parameters in different forest types and structures. Reference data were obtained by traditional measurements on 21 circular forest inventory sample plots with a 7 m radius. The tree mapping with the iPad showed a detection rate of 97.3% compared to 99.5% with the PLS scans for trees with a lower diameter at a breast height (dbh) threshold of 10 cm. The root mean square error (RMSE) of the best dbh measurement out of five different dbh modeling approaches was 3.13 cm with the iPad and 1.59 cm with PLS. The data acquisition time with the iPad was approximately 7.51 min per sample plot; this is twice as long as that with PLS but 2.5 times shorter than that with traditional forest inventory equipment. In conclusion, the proposed forest inventory with the iPad is generally feasible and achieves accurate and precise stem counts and dbh measurements with efficient labor effort compared to traditional approaches. Along with future technological developments, it is expected that other consumer-level handheld devices with integrated laser scanners will also be developed beyond the iPad, which will serve as an accurate and cost-efficient alternative solution to the approved but relatively expensive TLS and PLS systems. Such a development would be mandatory to broadly establish digital technology and fully automated routines in forest inventory practice. Finally, high-level progress is generally expected for the broader scientific community in forest ecosystem monitoring, as the collection of highly precise 3D point cloud data is no longer hindered by financial burdens.

Fusion of ground penetrating radar and laser scanning for infrastructure mapping

2021 ◽  
Vol 15 (1) ◽  
pp. 31-45
Author(s):  
Dominik Merkle ◽  
Carsten Frey ◽  
Alexander Reiterer
Keyword(s):  
Ground Penetrating Radar ◽  
Laser Scanning ◽  
Point Clouds ◽  
Soil Conditions ◽  
Positioning Systems ◽  
Subsurface Structures ◽  
Wall Structures ◽  
Surface Data ◽  
Laser Scanners ◽  
Ground Penetrating

AbstractMobile mapping vehicles, equipped with cameras, laser scanners (in this paper referred to as light detection and ranging, LiDAR), and positioning systems are limited to acquiring surface data. However, in this paper, a method to fuse both LiDAR and 3D ground penetrating radar (GPR) data into consistent georeferenced point clouds is presented, allowing imaging both the surface and subsurface. Objects such as pipes, cables, and wall structures are made visible as point clouds by thresholding the GPR signal’s Hilbert envelope. The results are verified with existing utility maps. Varying soil conditions, clutter, and noise complicate a fully automatized approach. Topographic correction of the GPR data, by using the LiDAR data, ensures a consistent ground height. Moreover, this work shows that the LiDAR point cloud, as a reference, increases the interpretability of GPR data and allows measuring distances between above ground and subsurface structures.

scholarly journals Elementary Error Model Applied to Terrestrial Laser Scanning Measurements: Study Case Arch Dam Kops

Mathematics ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 593
Author(s):  
Gabriel Kerekes ◽  
Volker Schwieger
Keyword(s):  
Laser Scanning ◽  
Linear Models ◽  
Functional Model ◽  
Point Clouds ◽  
Error Model ◽  
Arch Dam ◽  
Atmospheric Conditions ◽  
Atmospheric Parameters ◽  
Error Sources ◽  
Laser Scanners

All measurements are affected by systematic and random deviations. A huge challenge is to correctly consider these effects on the results. Terrestrial laser scanners deliver point clouds that usually precede surface modeling. Therefore, stochastic information of the measured points directly influences the modeled surface quality. The elementary error model (EEM) is one method used to determine error sources impact on variances-covariance matrices (VCM). This approach assumes linear models and normal distributed deviations, despite the non-linear nature of the observations. It has been proven that in 90% of the cases, linearity can be assumed. In previous publications on the topic, EEM results were shown on simulated data sets while focusing on panorama laser scanners. Within this paper an application of the EEM is presented on a real object and a functional model is introduced for hybrid laser scanners. The focus is set on instrumental and atmospheric error sources. A different approach is used to classify the atmospheric parameters as stochastic correlating elementary errors, thus expanding the currently available EEM. Former approaches considered atmospheric parameters functional correlating elementary errors. Results highlight existing spatial correlations for varying scanner positions and different atmospheric conditions at the arch dam Kops in Austria.

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