Registration And Feature Extraction From Terrestrial Laser Scanner Point Clouds For Aerospace Manufacturing

Aircraft wing manufacture is becoming increasingly digitalised. For example, it is becoming possible to produce on-line digital representations of individual structural elements, components and tools as they are deployed during assembly processes. When it comes to monitoring a manufacturing environment, imaging systems can be used to track objects as they move about the workspace, comparing actual positions, alignments, and spatial relationships with the digital representation of the manufacturing process. Active imaging systems such as laser scanners and laser trackers can capture measurements within the manufacturing environment, which can be used to deduce information about both the overall stage of manufacture and progress of individual tasks. This paper is concerned with the in-line extraction of spatial information such as the location and orientation of drilling templates which are used with hand drilling tools to ensure drilled holes are accurately located. In this work, a construction grade terrestrial laser scanner, the Leica RTC360, is used to capture an example aircraft wing section in mid-assembly from several scan locations. Point cloud registration uses 1.5"white matte spherical targets that are interchangeable with the SMR targets used by the Leica AT960 MR laser tracker, ensuring that scans are connected to an established metrology control network used to define the coordinate space. Point cloud registration was achieved to sub-millimetre accuracy when compared to the laser tracker network. The location of drilling templates on the surface of the wing skin are automatically extracted from the captured and registered point clouds. When compared to laser tracker referenced hole centres, laser scanner drilling template holes agree to within 0.2mm

3D Digital Surveying and Modelling of Cave Geometry: Application to Paleolithic Rock Art

3D digital surveying and modelling of cave geometry represents a relevant approach for research, management and preservation of our cultural and geological legacy. In this paper, a multi-sensor approach based on a terrestrial laser scanner, a high-resolution digital camera and a total station is presented. Two emblematic caves of Paleolithic human occupation and situated in northern Spain, “Las Caldas” and “Peña de Candamo”, have been chosen to put in practise this approach. As a result, an integral and multi-scalable 3D model is generated which may allow other scientists, pre-historians, geologists…, to work on two different levels, integrating different Paleolithic Art datasets: (1) a basic level based on the accurate and metric support provided by the laser scanner; and (2) a advanced level using the range and image-based modelling

A review of laser scanning for geological and geotechnical applications in underground mining

Laser scanning can provide timely assessments of mine sites despite adverse challenges in the operational environment. Although there are several published articles on laser scanning, there is a need to review them in the context of underground mining applications. To this end, a holistic review of laser scanning is presented including progress in 3D scanning systems, data capture/processing techniques and primary applications in underground mines. Laser scanning technology has advanced significantly in terms of mobility and mapping, but there are constraints in coherent and consistent data collection at certain mines due to feature deficiency, dynamics, and environmental influences such as dust and water. Studies suggest that laser scanning has matured over the years for change detection, clearance measurements and structure mapping applications. However, there is scope for improvements in lithology identification, surface parameter measurements, logistic tracking and autonomous navigation. Laser scanning has the potential to provide real-time solutions but the lack of infrastructure in underground mines for data transfer, geodetic networking and processing capacity remain limiting factors. Nevertheless, laser scanners are becoming an integral part of mine automation thanks to their affordability, accuracy and mobility, which should support their widespread usage in years to come

Reconstrucción digital de estructuras de tejados históricos: desarrollo de un flujo de trabajo de análisis altamente automatizado

[EN] Planning on adaptive reuse, maintenance and restoration of historic timber structuresrequiresextensive architectural and structural analysis of the actual condition. Current methods for a modellingof roof constructions consist of several manual steps including the time-consuming dimensional modelling. The continuous development of terrestrial laser scanners increases the accuracy, comfort and speed of the surveying work inroof constructions. Resultingpoint clouds enabledetailed visualisation of theconstructionsrepresented by single points or polygonal meshes, but in fact donot containinformation about the structural system and the beam elements. The developed workflow containsseveral processing steps on the point cloud dataset. The most important among them arethenormal vector computation, the segmentation of points to extract planarfaces, a classification of planarsegmentsto detect the beam side facesand finally theparametric modelling of the beams on the basis of classified segments. Thisenablesa highly automated transitionfrom raw point cloud data to a geometric model containing beams of the structural system. The geometric model,as well as additional information about the structural properties of involved wooden beams and their joints,is necessaryinput for a furtherstructural modellingof timber constructions. The results of the workflow confirm that the proposed methods work well for beams with a rectangularcross-section and minor deformations. Scan shadows and occlusionof beamsby additional installationsor interlockingbeamsdecreases the modelling performance, but in generala high level ofaccuracy and completeness isachieved ata high degree of automation.[ES] Las estructuras históricas de madera requieren un análisis arquitectónico y estructural exhaustivo de su condición real en aras de planificar la reutilización flexible, el mantenimiento y la restauración. Los métodos actuales que modelan las construcciones de cubiertas pasan por aplicar varias etapas en modo manual, que incluye el lento modelado dimensional. El desarrollo continuo de escáneres láser terrestres aumenta la exactitud, la comodidad y la velocidad del trabajo topográfico en construcciones de tejados. Las nubes de puntos resultantes permiten la visualización detallada de las construcciones representadas por puntos o mallas poligonales, pero de hecho no contienen información sobre el sistema estructural y los elementos del travesaño. El flujo de trabajo desarrollado contiene varias etapas de procesamiento en el conjunto de datos de la nube de puntos. Los más importantes son el cálculo del vector normal, la segmentación de puntos que extraen caras planas, la clasificación de segmentos planos que detectan las caras laterales del travesaño y, finalmente, el modelado paramétrico de los travesaños en función de los segmentos clasificados. Esto permite una transición altamente automatizada de los datos de la nube de puntos brutos a un modelo geométrico que contiene los travesaños del sistema estructural. El modelo geométrico, así como la información adicional sobre las propiedades estructurales de las vigas de madera involucradas y de sus juntas, es información necesaria de entrada para el modelado estructural eventual de las construcciones de madera. Los resultados del flujo de trabajo confirman que los métodos propuestos funcionan bien en travesaños que presentan secciones transversales rectangulares y deformaciones menores. Las sombras en los escaneados y las oclusiones de los travesaños a partir de instalaciones adicionales o vigas entrelazados disminuye el rendimiento del modelado, pero en general se logra un nivel de exactitud e integridad elevado con un alto grado de automatización.Pöchtrager, M.; Styhler-Aydın, G.; Döring-Williams, M.; Pfeifer, N. (2018). Digital reconstruction of historic roof structures: developing a workflow for a highly automated analysis. Virtual Archaeology Review. 9(19):21-33. doi:10.4995/var.2018.8855SWORD2133919Attene, M., & Spagnuolo, M. (2000). Automatic surface reconstruction from point sets in space. Computer Graphics Forum, 19(3), 457-465. doi:10.1111/1467-8659.00438Baik, A., Yaagoubi, R., & Boehm, J. (2015). Integration of Jeddah historical BIM and 3D GIS for documentation and restoration of historical monument. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, XL-5/W7, 29-34. doi:10.5194/isprsarchives-XL-5-W7-29-2015Bassier, M., Hadjidemetriou, G., Vergauwen, M., Van Roy, N., & Verstrynge, E. (2016). Implementation of Scan-to-BIM and FEM for the Documentation and Analysis of Heritage Timber Roof Structures. In M. Ioannides, E. Fink, A. Moropoulou, M. Hagedorn-Saupe, A. Fresa, G. Liestøl, . . . P. Grussenmeyer (Ed.), Digital Heritage. Progress in Cultural Heritage: Documentation, Preservation, and Protection. EuroMed 2016 (pp. 79-90). Springer, Cham. doi:10.1007/978-3-319-48496-9_7Besl, P., & McKay, N. (1992). A method for registration of 3D Shapes. IEEE Transactions on Pattern Analysis and Machine Intelligence, 14, 239-254. doi:10.1109/34.121791Chida, A., & Masuda, H. (2016). Reconstruction of polygonal prisms from point-clouds of engineering facilities. Journal of Computational Design and Engineering, 3(4), 322-329. doi:10.1016/j.jcde.2016.05.003Dore, C., & Murphy, M. (2017). Current state of the art historic building information modelling. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-2/W5, 185-192. doi:10.5194/isprsarchives-XLII-2-W5-185-2017Dorninger, P., Nothegger, C., & Rasztovits, S. (2013). Efficient 3-D documentation of Neptune fountain in the park of Schönbrunn palace at millimeter scale. Proceedings XXIV International CIPA Symposium, ISPRS Annals, II, 5/W1, 103-108. doi:10.5194/isprsannals-II-5-W1-103-2013Eßer, G., Styhler-Aydın, G., & Hochreiner, G. (2016a). Construction history and structural assessment of historic roofs - An interdisciplinary approach. In K. Van Balen, & E. Verstrynge (Eds.), Structural analysis of historical constructions. Anamnesis, diagnosis, therapy, controls (pp. 790-795). London, GB.Eßer, G., Styhler-Aydın, G., & Hochreiner, G. (2016b). The historic roof structures of the Vienna Hofburg: An innovative interdisciplinary approach in architectural sciences laying ground for structural modeling. In J. Eberhardsteiner, W. Winter, A. Fadai, & M. Pöll (Eds.), WCTE 2016. World conference on timber engineering (pp. 3039-3047). Wien, Austria.Fischler, M., & Bolles, R. (1981). Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Communications of the ACM, 24(6), 381-395. doi:10.1145/358669.358692Glira, P., Pfeifer, N., Briese, C., & Ressl, C. (2015). A Correspondence Framework for ALS Strip Adjustments based on Variants of the ICP Algorithm. Photogrammetrie, Fernerkundung, Geoinformation, 4, 275-289. doi:10.1127/pfg/2015/0270Hochreiner, G., Eßer, G., & Styhler-Aydın, G. (2016). Modern timber engineering methods in the context of historical timber structures. In J. Eberhardsteiner, W. Winter, A. Fadai, & M. Pöll (Eds.), WCTE 2016. World conference on timber engineering (pp. 4830-4838). Wien, Austria.Hoppe, H., DeRose, T., Duchamp, T., McDonald, J., & Stuetzle, W. (1992). Surface reconstruction from unorganized points. SIGGRAPH '92 Proceedings of the 19th annual conference on Computer graphics and interactive techniques. ACM SIGGRAPH Computer Graphics, 26(2), 71-78. doi:10.1145/142920.134011International Organization for Standardization. (2016). Industrial automation systems and integration -- Product data representation and exchange -- Part 21: Implementation methods: Clear text encoding of the exchange Structure. ISO/DIS Standard No. 10303-21. Retrieved from https://www.iso.org/standard/63141.html.Jung, J., Hong, S., Jeong, S., Kim, S., Cho, H., Hong, S., & Heo, J. (2014). Productive modeling for development of asbuilt BIM of existing indoor structures. Automation in Construction, 42, 68-77. doi:10.1016/j.autcon.2014.02.021Kazhdan, M., Bolitho, M., & Hoppe, H. (2006). Poisson surface reconstruction. Symposium on Geometry Processing (pp. 61-70). The Eurographics Association. doi:10.2312/SGP/SGP06/061-070Lee, J., Son, H., Kim, C., & Kim, C. (2013). Skeleton-based 3-D reconstruction of as-built pipelines from laser-scan data. Automation in Reconstruction, 35, 199-207. doi:10.1061/9780784412343.0031Li, W., Goodchild, M., & Church, R. (2013). An efficient measure of compactness for two-dimensional shapes and its application in regionalization problems. International Journal of Geographical Information Science, 1227-1250. doi:10.1080/13658816.2012.752093Nothegger, C., & Dorninger, P. (2009). 3D filtering of high-resolution terrestrial laser scanner point clouds for cultural heritage documentation. Photogrammetrie, Fernerkundung, Geoinformation, 1, 53-63. doi:10.1127/0935-1221/2009/0006Pfeifer, N., & Winterhalder, D. (2004). Modelling of tree cross sections from terrestrial laser scanning data with free-form curves. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 36(8/W2), 76-81.Pfeifer, N., Mandlburger, G., Otepka, J., & Karel, W. (2014). OPALS - A framework for Airborne Laser Scanning data analysis. Computers, Environment and Urban Systems, 45, 125-136. doi:10.1016/j.compenvurbsys.2013.11.002Pöchtrager, M., Styhler-Aydın, G., Döring-Williams, M., & Pfeifer, N. (2017). Automated Reconstruction of Historic Roof Structures from Point Clouds - Development and Examples. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, IV-2-W2, 195-202. doi:10.5194/isprs-annals-IV-2-W2-195-2017Rabbani, T., Dijkman, S., Van den Heuvel, F., & Vosselman, G. (2007). An integrated approach for modelling and global registration of point clouds. ISPRS Journal of Photogrammetry and Remote Sensing, 61(6), 355-370. doi:10.1016/j.isprsjprs.2006.09.006Raumonen, P., Kaasalainen, M., Åkerblom, M., Kaasalainen, S., Kaartinen, H., Vastaranta, M., . . . Lewis, P. (2013). Fast automatic precision tree models from terrestrial laser scanner data. Remote Sensing, 5(2), 491-520. doi:10.3390/rs5020491Stylianidis, E., & Remondino, F. (2016). 3D Recording, Documentation and Management of Cultural Heritage. Caithness, UK: Whittles Publishing.Thies, M., Pfeifer, N., Winterhalder, D., & Gorte, B. (2004). Three-dimensional reconstruction of stems for assessment of taper, sweep and lean based on laser scanning of standing trees. Scandinavian Journal of Forest Research, 19(6), 571-581. doi:10.1080/02827580410019562Thomson, C., & Boehm, J. (2015). Automatic geometry generation from point clouds for BIM. Remote Sensing, 7(9), 11753-11775. doi:10.3390/rs70911753Vosselman, G., & Maas, H.-G. (2010). Airborne and Terrestrial Laser Scanning. Caithness, UK: Whittles Publishing.Wang, D., Hollaus, M., Puttonen, E., & Pfeifer, N. (2016). Automatic and self-adaptive stem reconstruction in landslide-affected forests. Remote Sensing, 8(12), p. 974. doi:10.3390/rs8120974Wang, D., Kankare, V., Puttonen, E., Hollaus, M., & Pfeifer, N. (2016). Reconstructing stem cross section shapes from terrestrial laser scanning. IEEE Geoscience and Remote Sensing Letters, 14(2), 272-276. doi:10.1109/LGRS.2016.2638738Xiong, X., Adan, A., Akinci, B., & Huber, D. (2013). Automatic creation of semantically rich 3D building models from laser scanner data. Automation in Construction, 31, S. 325-337. doi:10.1016/j.autcon.2012.10.006Yang, X., Koehl, M., & Grussenmeyer, P. (2017). Parametric modelling of as-built beam framed structure in BIM environment. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-2/W3, 651-657. doi:10.5194/isprs-archives-XLII-2-W3-651-2017Zhang, R., & Zakhor, A. (2014). Automatic identification of window regions on indoor point clouds using LiDAR and cameras. Applications of Computer Vision (WACV), 2014 IEEE Winter Conference, 107-114. doi:10.1109/WACV.2014.683611

Use of Terrestrial Laser Scanning Technology for Long Term High Precision Deformation Monitoring

The paper presents a new methodology for high precision monitoring of deformations with a long term perspective using terrestrial laser scanning technology. In order to solve the problem of a stable reference system and to assure the high quality of possible position changes of point clouds, scanning is integrated with two complementary surveying techniques, i.e., high quality static GNSS positioning and precise tacheometry. The case study object where the proposed methodology was tested is a high pressure underground pipeline situated in an area which is geologically unstable

Calibration of full-waveform airborne laser scanning data for 3D object segmentation

Phd ThesisAirborne Laser Scanning (ALS) is a fully commercial technology, which has seen rapid uptake from the photogrammetry and remote sensing community to classify surface features and enhance automatic object recognition and extraction processes. 3D object segmentation is considered as one of the major research topics in the field of laser scanning for feature recognition and object extraction applications. The demand for automatic segmentation has significantly increased with the emergence of full-waveform (FWF) ALS, which potentially offers an unlimited number of return echoes. FWF has shown potential to improve available segmentation and classification techniques through exploiting the additional physical observables which are provided alongside the standard geometric information. However, use of the FWF additional information is not recommended without prior radiometric calibration, taking into consideration all the parameters affecting the backscattered energy. The main focus of this research is to calibrate the additional information from FWF to develop the potential of point clouds for segmentation algorithms. Echo amplitude normalisation as a function of local incidence angle was identified as a particularly critical aspect, and a novel echo amplitude normalisation approach, termed the Robust Surface Normal (RSN) method, has been developed. Following the radar equation, a comprehensive radiometric calibration routine is introduced to account for all variables affecting the backscattered laser signal. Thereafter, a segmentation algorithm is developed, which utilises the raw 3D point clouds to estimate the normal for individual echoes based on the RSN method. The segmentation criterion is selected as the normal vector augmented by the calibrated backscatter signals. The developed segmentation routine aims to fully integrate FWF data to improve feature recognition and 3D object segmentation applications. The routine was tested over various feature types from two datasets with different properties to assess its potential. The results are compared to those delivered through utilizing only geometric information, without the additional FWF radiometric information, to assess performance over existing methods. The results approved the potential of the FWF additional observables to improve segmentation algorithms. The new approach was validated against manual segmentation results, revealing a successful automatic implementation and achieving an accuracy of 82%

Detecting changes in forest structure over time with bi-temporal terrestrial laser scanning data

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