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>

Development, Calibration and Evaluation of a Portable and Direct Georeferenced Laser Scanning System for Kinematic 3D Mapping

2015 ◽  
Vol 9 (4) ◽  
Author(s):  
Erik Heinz ◽  
Christian Eling ◽  
Markus Wieland ◽  
Lasse Klingbeil ◽  
Heiner Kuhlmann
Keyword(s):  
Laser Scanning ◽  
Attitude Determination ◽  
Low Cost ◽  
Laser Scanner ◽  
Point Clouds ◽  
Scanning System ◽  
Planar Surfaces ◽  
Laser Scanners ◽  
Scanning Geometry ◽  
Laser Scanning System

AbstractIn recent years, kinematic laser scanning has become increasingly popular because it offers many benefits compared to static laser scanning. The advantages include both saving of time in the georeferencing and a more favorable scanning geometry. Often mobile laser scanning systems are installed on wheeled platforms, which may not reach all parts of the object. Hence, there is an interest in the development of portable systems, which remain operational even in inaccessible areas. The development of such a portable laser scanning system is presented in this paper. It consists of a lightweight direct georeferencing unit for the position and attitude determination and a small low-cost 2D laser scanner. This setup provides advantages over existing portable systems that employ heavy and expensive 3D laser scanners in a profiling mode.A special emphasis is placed on the system calibration, i. e. the determination of the transformation between the coordinate frames of the direct georeferencing unit and the 2D laser scanner. To this end, a calibration field is used, which consists of differently orientated georeferenced planar surfaces, leading to estimates for the lever arms and boresight angles with an accuracy of mm and one-tenth of a degree. Finally, point clouds of the mobile laser scanning system are compared with georeferenced point clouds of a high-precision 3D laser scanner. Accordingly, the accuracy of the system is in the order of cm to dm. This is in good agreement with the expected accuracy, which has been derived from the error propagation of previously estimated variance components.

scholarly journals Application of 3D Laser Scanning for Digitization, Design and Analysis of Multistoried Building

2021 ◽  
Author(s):  
Abdul Qadir Bhatti ◽  
◽  
Abdul Wahab ◽  
Wadea Sindi ◽  
◽  
...  
Keyword(s):  
Structural Damage ◽  
Point Cloud ◽  
Laser Scanning ◽  
Passive Control ◽  
Complex Geometry ◽  
Laser Scanner ◽  
Point Clouds ◽  
Historical Building ◽  
Laser Scanners ◽  
Original Construction

Laser scanning is a fast-developing technology, which collects millions of points and creates a framework within a few minutes, generating a 'point cloud' of the structure. Laser scanning is a quite new but rapidly evolving technology that has been reviewed. this research study has used most modern models of laser scanners and their accompanying software that are capable of accurate capture and alignment of point clouds. Consequently, the laser scans have precisely captured the current geometry of each structure, which is irregular in many cases due to inherently complex geometry, anomalies during the original construction, aging, deterioration, and structural damage. As both the exterior and interior of the structure have been scanned, the point cloud became a digital 3D image of the historical building, which can be virtually toured from inside and outside. A 4-story public building was scanned using a 3D laser scanner to determine the architectural and structural drawings of the response to an earthquake. The application of passive control using a damper with the laser scanner has been modelled in this study. The results corroborate that this technique provides the best outcomes for reducing seismic damage collapses.

scholarly journals LiDAR-Based Glass Detection for Improved Occupancy Grid Mapping

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2263
Author(s):  
Haileleol Tibebu ◽  
Jamie Roche ◽  
Varuna De Silva ◽  
Ahmet Kondoz
Keyword(s):  
Laser Scanner ◽  
Point Clouds ◽  
Light Detection And Ranging ◽  
Test Results ◽  
New Approach ◽  
Occupancy Grid ◽  
Laser Scanners ◽  
Novel Method ◽  
Occupancy Grid Mapping ◽  
Cartesian Coordinate

Creating an accurate awareness of the environment using laser scanners is a major challenge in robotics and auto industries. LiDAR (light detection and ranging) is a powerful laser scanner that provides a detailed map of the environment. However, efficient and accurate mapping of the environment is yet to be obtained, as most modern environments contain glass, which is invisible to LiDAR. In this paper, a method to effectively detect and localise glass using LiDAR sensors is proposed. This new approach is based on the variation of range measurements between neighbouring point clouds, using a two-step filter. The first filter examines the change in the standard deviation of neighbouring clouds. The second filter uses a change in distance and intensity between neighbouring pules to refine the results from the first filter and estimate the glass profile width before updating the cartesian coordinate and range measurement by the instrument. Test results demonstrate the detection and localisation of glass and the elimination of errors caused by glass in occupancy grid maps. This novel method detects frameless glass from a long range and does not depend on intensity peak with an accuracy of 96.2%.

The Steam Turbine Retrofitting of Six Boiling Water Reactor Units Using Innovative Engineering and Laser Scanning Techniques

2009 ◽  
Author(s):  
Mike Jones ◽  
David J. Nelmes
Keyword(s):  
Steam Turbine ◽  
Laser Scanning ◽  
Laser Scanner ◽  
Boiling Water ◽  
Boiling Water Reactors ◽  
Extensive Experience ◽  
Turbine Generators ◽  
The Usa ◽  
Water Reactors ◽  
Scan Data

Alstom Power is executing the steam turbine retrofit of six nuclear units for Exelon Generation in the USA. The existing turbine-generators are an 1800 RPM General Electric design originally rated at 912 MWe and 1098 MWe and powered by Boiling Water Reactors. 18 Low Pressure inner modules will be replaced, with the first due to be installed in March 2010. This project is particularly challenging — the aggressive retrofit installation schedule is compounded by the requirement to handle radioactively contaminated equipment and also comply with demanding regulations applicable to BWR plant. The author’s company has extensive experience in the steam turbine retrofit business, having supplied around 800 retrofit cylinders globally since the 1970’s. However, this LP upgrade challenges the established techniques used in the business and requires extraordinary effort. Traditional retrofit engineering and installation principles have been interrogated and developed to meet the specific requirements of this project. Innovative techniques are introduced, including the extensive use of the Leica HDS 6000 laser scanner to model the existing plant. The approach has advanced the field of steam turbine retrofit design and installation significantly. The first section of this paper focuses on the extraordinary considerations of the project and the challenges surrounding BWR plant. The second part describes the laser scanning technique and the application of scan data. It outlines the innovative solutions which have been developed.

scholarly journals Segmentation and Multi-Scale Convolutional Neural Network-Based Classification of Airborne Laser Scanner Data

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3347 ◽  
Author(s):  
Zhishuang Yang ◽  
Bo Tan ◽  
Huikun Pei ◽  
Wanshou Jiang
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Laser Scanning ◽  
Laser Scanner ◽  
Region Growing ◽  
Point Clouds ◽  
Classification Method ◽  
Multi Scale ◽  
Airborne Laser

The classification of point clouds is a basic task in airborne laser scanning (ALS) point cloud processing. It is quite a challenge when facing complex observed scenes and irregular point distributions. In order to reduce the computational burden of the point-based classification method and improve the classification accuracy, we present a segmentation and multi-scale convolutional neural network-based classification method. Firstly, a three-step region-growing segmentation method was proposed to reduce both under-segmentation and over-segmentation. Then, a feature image generation method was used to transform the 3D neighborhood features of a point into a 2D image. Finally, feature images were treated as the input of a multi-scale convolutional neural network for training and testing tasks. In order to obtain performance comparisons with existing approaches, we evaluated our framework using the International Society for Photogrammetry and Remote Sensing Working Groups II/4 (ISPRS WG II/4) 3D labeling benchmark tests. The experiment result, which achieved 84.9% overall accuracy and 69.2% of average F1 scores, has a satisfactory performance over all participating approaches analyzed.

scholarly journals FINE REGISTRATION OF KILO-STATION NETWORKS - A MODERN PROCEDURE FOR TERRESTRIAL LASER SCANNING DATA SETS

2016 ◽  
Vol XLI-B5 ◽  
pp. 485-492
Author(s):  
J.-F. Hullo
Keyword(s):  
Laser Scanning ◽  
Laser Scanner ◽  
Data Sets ◽  
Data Set ◽  
Information Models ◽  
3D Network ◽  
Laser Scanners ◽  
Building Information ◽  
Set Up ◽  
Fine Registration

We propose a complete methodology for the fine registration and referencing of kilo-station networks of terrestrial laser scanner data currently used for many valuable purposes such as 3D as-built reconstruction of Building Information Models (BIM) or industrial asbuilt mock-ups. This comprehensive target-based process aims to achieve the global tolerance below a few centimetres across a 3D network including more than 1,000 laser stations spread over 10 floors. This procedure is particularly valuable for 3D networks of indoor congested environments. In situ, the use of terrestrial laser scanners, the layout of the targets and the set-up of a topographic control network should comply with the expert methods specific to surveyors. Using parametric and reduced Gauss-Helmert models, the network is expressed as a set of functional constraints with a related stochastic model. During the post-processing phase inspired by geodesy methods, a robust cost function is minimised. At the scale of such a data set, the complexity of the 3D network is beyond comprehension. The surveyor, even an expert, must be supported, in his analysis, by digital and visual indicators. In addition to the standard indicators used for the adjustment methods, including Baarda’s reliability, we introduce spectral analysis tools of graph theory for identifying different types of errors or a lack of robustness of the system as well as <i>in fine</i> documenting the quality of the registration.

scholarly journals INTEGRATING TOPOGRAPHIC, PHOTOGRAMMETRIC AND LASER SCANNING TECHNIQUES FOR A SCAN-TO-BIM PROCESS

2021 ◽  
Vol XLIII-B2-2021 ◽  
pp. 883-890
Author(s):  
M. Lo Brutto ◽  
E. Iuculano ◽  
P. Lo Giudice
Keyword(s):  
Laser Scanning ◽  
Building Information Modeling ◽  
Laser Scanner ◽  
Point Clouds ◽  
Parametric Modeling ◽  
Information Modeling ◽  
Survey Method ◽  
The Real ◽  
Building Information ◽  
Heritage Building

Abstract. The preservation of historic buildings can often be particularly difficult due to the lack of detailed information about architectural features, construction details, etc.. However, in recent years considerable technological innovation in the field of Architecture, Engineering, and Construction (AEC) has been achieved by the Building Information Modeling (BIM) process. BIM was developed as a methodology used mainly for new construction but, given its considerable potential, this approach can also be successfully used for existing buildings, especially for buildings of historical and architectural value. In this case, it is more properly referred to as Historic – or Heritage – Building Information Modeling (HBIM). In the HBIM process, it is essential to precede the parametric modeling phase of the building with a detailed 3D survey that allows the acquisition of all geometric information. This methodology, called Scan-to-BIM, involves the use of 3D survey techniques for the production of point clouds as a geometric “database” for parametric modeling. The Scan-to-BIM approach can have several issues relating to the complexity of the survey. The work aims to apply the Scan-to-BIM approach to the survey and modeling of a historical and architectural valuable building to test a survey method, based on integrating different techniques (topography, photogrammetry and laser scanning), that improves the data acquisition phase. The “Real Cantina Borbonica” (Cellar of Royal House of Bourbon) in Partinico (Sicily, Italy) was chosen as a case study. The work has allowed achieving the HBIM of the “Real Cantina Borbonica” and testing an approach based exclusively on a topographic constraint to merge in the same reference system all the survey data (laser scanner and photogrammetric point clouds).

scholarly journals COMBINATION OF THERMAL AND GEOMETRIC INFORMATION FOR BIM ENRICHMENT

2019 ◽  
Vol XLII-2/W15 ◽  
pp. 719-725 ◽  
Author(s):  
H. Macher ◽  
M. Boudhaim ◽  
P. Grussenmeyer ◽  
M. Siroux ◽  
T. Landes
Keyword(s):  
Laser Scanning ◽  
Thermal Analyses ◽  
Laser Scanner ◽  
Point Clouds ◽  
Existing Buildings ◽  
Energy Audit ◽  
Geometric Information ◽  
Information Models ◽  
Building Information ◽  
Reduction Of Energy Consumption

<p><strong>Abstract.</strong> In the context of building renovation, infrared (IR) cameras are widely used to perform the energy audit of buildings. They allow analysing precisely the energetic performances of existing buildings and thermal analyses represent a key step for the reduction of energy consumption. They are also used to assess the thermal comfort of people living or working in a building. Building Information Models (BIM) are widespread to plan the rehabilitation of existing buildings and laser scanning is now commonly used to capture the geometry of buildings for as-built BIM creation. The combination of thermographic and geometric data presents a high number and variety of applications (Lagüela and Díaz-Vilariño, 2016). However, geometric and thermal information are generally acquired separately by different building stakeholders and thermal analyses are performed with independence of geometry. In this paper, the combination of thermal and geometric information is investigated for indoor of buildings. The aim of the project is to create 3D thermographic point clouds based on data acquired by a laser scanner and a thermal camera. Based on these point clouds, BIM models might be enriched with thermal information through the scan-to-BIM process.</p>

A novel method for extracting skeleton of fruit tree from 3D point clouds

2020 ◽  
pp. 2050051
Author(s):  
Shenglian lu ◽  
Guo Li ◽  
Jian Wang
Keyword(s):  
Laser Scanning ◽  
Laser Scanner ◽  
Point Clouds ◽  
Fruit Trees ◽  
Fruit Tree ◽  
Tree Canopy ◽  
3D Point Clouds ◽  
Novel Method ◽  
Manual Interaction ◽  
Traditional Approaches

Tree skeleton could be useful to agronomy researchers because the skeleton describes the shape and topological structure of a tree. The phenomenon of organs’ mutual occlusion in fruit tree canopy is usually very serious, this should result in a large amount of data missing in directed laser scanning 3D point clouds from a fruit tree. However, traditional approaches can be ineffective and problematic in extracting the tree skeleton correctly when the tree point clouds contain occlusions and missing points. To overcome this limitation, we present a method for accurate and fast extracting the skeleton of fruit tree from laser scanner measured 3D point clouds. The proposed method selects the start point and endpoint of a branch from the point clouds by user’s manual interaction, then a backward searching is used to find a path from the 3D point cloud with a radius parameter as a restriction. The experimental results in several kinds of fruit trees demonstrate that our method can extract the skeleton of a leafy fruit tree with highly accuracy.

scholarly journals Comparison of Three Algorithms to Estimate Tree Stem Diameter from Terrestrial Laser Scanner Data

Forests ◽  
2019 ◽  
Vol 10 (7) ◽  
pp. 599 ◽  
Author(s):  
Ravaglia ◽  
Fournier ◽  
Bac ◽  
Véga ◽  
Côté ◽  
...  
Keyword(s):  
Laser Scanner ◽  
Point Clouds ◽  
Stem Diameter ◽  
Trunk Diameter ◽  
Diameter At Breast Height ◽  
Breast Height ◽  
Forest Inventories ◽  
Laser Scanners ◽  
Step Algorithm ◽  
Coniferous Plantations

Terrestrial laser scanners provide accurate and detailed point clouds of forest plots, which can be used as an alternative to destructive measurements during forest inventories. Various specialized algorithms have been developed to provide automatic and objective estimates of forest attributes from point clouds. The STEP (Snakes for Tuboid Extraction from Point cloud) algorithm was developed to estimate both stem diameter at breast height and stem diameters along the bole length. Here, we evaluate the accuracy of this algorithm and compare its performance with two other state-of-the-art algorithms that were designed for the same purpose (i.e., the CompuTree and SimpleTree algorithms). We tested each algorithm against point clouds that incorporated various degrees of noise and occlusion. We applied these algorithms to three contrasting test sites: (1) simulated scenes of coniferous stands in Newfoundland (Canada), (2) test sites of deciduous stands in Phalsbourg (France), and (3) coniferous plantations in Quebec, Canada. In most cases, the STEP algorithm predicted diameter at breast height with higher R2 and lower RMSE than the other two algorithms. The STEP algorithm also achieved greater accuracy when estimating stem diameter in occluded and noisy point clouds, with mean errors in the range of 1.1 cm to 2.28 cm. The CompuTree and SimpleTree algorithms respectively produced errors in the range of 2.62 cm to 6.1 cm and 1.03 cm to 3.34 cm, respectively. Unlike CompuTree or SimpleTree, the STEP algorithm was not able to estimate trunk diameter in the uppermost portions of the trees. Our results show that the STEP algorithm is more adapted to extract DBH and stem diameter automatically from occluded and noisy point clouds. Our study also highlights that SimpleTree and CompuTree require data filtering and results corrections. Conversely, none of these procedures were applied for the implementation of the STEP algorithm.

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