scholarly journals Towards footwear manufacturing 4.0: shoe sole robotic grasping in assembling operations

2021 ◽  
Author(s):  
Guillermo Oliver ◽  
Pablo Gil ◽  
Jose F. Gomez ◽  
Fernando Torres
Keyword(s):  
Industry 4.0 ◽  
Laser Scanner ◽  
Point Clouds ◽  
Average Score ◽  
Low Density ◽  
Contour Extraction ◽  
Shoe Industry ◽  
Simulated Environment ◽  
Dense Point ◽  
Different Shapes

AbstractIn this paper, we present a robotic workcell for task automation in footwear manufacturing such as sole digitization, glue dispensing, and sole manipulation from different places within the factory plant. We aim to make progress towards shoe industry 4.0. To achieve it, we have implemented a novel sole grasping method, compatible with soles of different shapes, sizes, and materials, by exploiting the particular characteristics of these objects. Our proposal is able to work well with low density point clouds from a single RGBD camera and also with dense point clouds obtained from a laser scanner digitizer. The method computes antipodal grasping points from visual data in both cases and it does not require a previous recognition of sole. It relies on sole contour extraction using concave hulls and measuring the curvature on contour areas. Our method was tested both in a simulated environment and in real conditions of manufacturing at INESCOP facilities, processing 20 soles with different sizes and characteristics. Grasps were performed in two different configurations, obtaining an average score of 97.5% of successful real grasps for soles without heel made with materials of low or medium flexibility. In both cases, the grasping method was tested without carrying out tactile control throughout the task.

scholarly journals Estimating tree stem diameters and volume from smartphone photogrammetric point clouds

2019 ◽  
Vol 93 (3) ◽  
pp. 411-429 ◽  
Author(s):  
Maria Immacolata Marzulli ◽  
Pasi Raumonen ◽  
Roberto Greco ◽  
Manuela Persia ◽  
Patrizia Tartarino
Keyword(s):  
Low Cost ◽  
Three Dimensional ◽  
Laser Scanner ◽  
Point Clouds ◽  
Stem Volume ◽  
Forest Plot ◽  
3D Point Clouds ◽  
Dense Point ◽  
Minimum Number ◽  
Scale Point

Abstract Methods for the three-dimensional (3D) reconstruction of forest trees have been suggested for data from active and passive sensors. Laser scanner technologies have become popular in the last few years, despite their high costs. Since the improvements in photogrammetric algorithms (e.g. structure from motion—SfM), photographs have become a new low-cost source of 3D point clouds. In this study, we use images captured by a smartphone camera to calculate dense point clouds of a forest plot using SfM. Eighteen point clouds were produced by changing the densification parameters (Image scale, Point density, Minimum number of matches) in order to investigate their influence on the quality of the point clouds produced. In order to estimate diameter at breast height (d.b.h.) and stem volumes, we developed an automatic method that extracts the stems from the point cloud and then models them with cylinders. The results show that Image scale is the most influential parameter in terms of identifying and extracting trees from the point clouds. The best performance with cylinder modelling from point clouds compared to field data had an RMSE of 1.9 cm and 0.094 m3, for d.b.h. and volume, respectively. Thus, for forest management and planning purposes, it is possible to use our photogrammetric and modelling methods to measure d.b.h., stem volume and possibly other forest inventory metrics, rapidly and without felling trees. The proposed methodology significantly reduces working time in the field, using ‘non-professional’ instruments and automating estimates of dendrometric parameters.

scholarly journals PEDESTRIAN DETECTION BY LASER SCANNING AND DEPTH IMAGERY

2016 ◽  
Vol XLI-B3 ◽  
pp. 465-468
Author(s):  
A. Barsi ◽  
T. Lovas ◽  
B. Molnar ◽  
A. Somogyi ◽  
Z. Igazvolgyi
Keyword(s):  
Laser Scanning ◽  
Pedestrian Detection ◽  
Laser Scanner ◽  
Point Clouds ◽  
Shopping Mall ◽  
Complex Flow ◽  
Video Footage ◽  
Flow Parameters ◽  
Dense Point ◽  
Commercial Applications

Pedestrian flow is much less regulated and controlled compared to vehicle traffic. Estimating flow parameters would support many safety, security or commercial applications. Current paper discusses a method that enables acquiring information on pedestrian movements without disturbing and changing their motion. Profile laser scanner and depth camera have been applied to capture the geometry of the moving people as time series. Procedures have been developed to derive complex flow parameters, such as count, volume, walking direction and velocity from laser scanned point clouds. Since no images are captured from the faces of pedestrians, no privacy issues raised. The paper includes accuracy analysis of the estimated parameters based on video footage as reference. Due to the dense point clouds, detailed geometry analysis has been conducted to obtain the height and shoulder width of pedestrians and to detect whether luggage has been carried or not. The derived parameters support safety (e.g. detecting critical pedestrian density in mass events), security (e.g. detecting prohibited baggage in endangered areas) and commercial applications (e.g. counting pedestrians at all entrances/exits of a shopping mall).

scholarly journals A comparison of multi-view 3D reconstruction of a rock wall using several cameras and a laser scanner

2014 ◽  
Vol XL-5 ◽  
pp. 573-580 ◽  
Author(s):  
K. Thoeni ◽  
A. Giacomini ◽  
R. Murtagh ◽  
E. Kniest
Keyword(s):  
3D Reconstruction ◽  
Point Cloud ◽  
Laser Scanner ◽  
Ground Truth ◽  
Point Clouds ◽  
Digital Cameras ◽  
Rock Wall ◽  
Geological Features ◽  
Dense Point ◽  
Sharp Edges

This work presents a comparative study between multi-view 3D reconstruction using various digital cameras and a terrestrial laser scanner (TLS). Five different digital cameras were used in order to estimate the limits related to the camera type and to establish the minimum camera requirements to obtain comparable results to the ones of the TLS. The cameras used for this study range from commercial grade to professional grade and included a GoPro Hero 1080 (5 Mp), iPhone 4S (8 Mp), Panasonic Lumix LX5 (9.5 Mp), Panasonic Lumix ZS20 (14.1 Mp) and Canon EOS 7D (18 Mp). The TLS used for this work was a FARO Focus 3D laser scanner with a range accuracy of ±2 mm. The study area is a small rock wall of about 6 m height and 20 m length. The wall is partly smooth with some evident geological features, such as non-persistent joints and sharp edges. Eight control points were placed on the wall and their coordinates were measured by using a total station. These coordinates were then used to georeference all models. A similar number of images was acquired from a distance of between approximately 5 to 10 m, depending on field of view of each camera. The commercial software package PhotoScan was used to process the images, georeference and scale the models, and to generate the dense point clouds. Finally, the open-source package CloudCompare was used to assess the accuracy of the multi-view results. Each point cloud obtained from a specific camera was compared to the point cloud obtained with the TLS. The latter is taken as ground truth. The result is a coloured point cloud for each camera showing the deviation in relation to the TLS data. The main goal of this study is to quantify the quality of the multi-view 3D reconstruction results obtained with various cameras as objectively as possible and to evaluate its applicability to geotechnical problems.

scholarly journals ONLY IMAGE BASED FOR THE 3D METRIC SURVEY OF GOTHIC STRUCTURES BY USING FRAME CAMERAS AND PANORAMIC CAMERAS

2016 ◽  
Vol XLI-B5 ◽  
pp. 363-370 ◽  
Author(s):  
A. Pérez Ramos ◽  
G. Robleda Prieto
Keyword(s):  
Laser Scanning ◽  
Imaging Techniques ◽  
Laser Scanner ◽  
Point Clouds ◽  
Office Work ◽  
Light Conditions ◽  
External Quality ◽  
Panoramic Cameras ◽  
Dense Point ◽  
Close Range

Indoor Gothic apse provides a complex environment for virtualization using imaging techniques due to its light conditions and architecture. Light entering throw large windows in combination with the apse shape makes difficult to find proper conditions to photo capture for reconstruction purposes. Thus, documentation techniques based on images are usually replaced by scanning techniques inside churches. Nevertheless, the need to use Terrestrial Laser Scanning (TLS) for indoor virtualization means a significant increase in the final surveying cost. So, in most cases, scanning techniques are used to generate dense point clouds. However, many Terrestrial Laser Scanner (TLS) internal cameras are not able to provide colour images or cannot reach the image quality that can be obtained using an external camera. Therefore, external quality images are often used to build high resolution textures of these models. This paper aims to solve the problem posted by virtualizing indoor Gothic churches, making that task more affordable using exclusively techniques base on images. It reviews a previous proposed methodology using a DSRL camera with 18-135 lens commonly used for close range photogrammetry and add another one using a HDR 360° camera with four lenses that makes the task easier and faster in comparison with the previous one. Fieldwork and office-work are simplified. The proposed methodology provides photographs in such a good conditions for building point clouds and textured meshes. Furthermore, the same imaging resources can be used to generate more deliverables without extra time consuming in the field, for instance, immersive virtual tours. In order to verify the usefulness of the method, it has been decided to apply it to the apse since it is considered one of the most complex elements of Gothic churches and it could be extended to the whole building.

Point-Based Virtual Environment for Detecting Scaffolding, Wearing, and Cracks of Furnace Walls

2018 ◽  
Author(s):  
Yuki Shinozaki ◽  
Hiroshi Masuda
Keyword(s):  
Blast Furnace ◽  
Virtual Environment ◽  
Laser Scanner ◽  
Point Clouds ◽  
Spline Surfaces ◽  
Dense Point ◽  
Multiple Resolutions ◽  
Normal Wall ◽  
The Difference ◽  
Production Facilities

Maintenance of production facilities is important in various industries. Since production facilities degrade their original functions during their long life-cycle, it is necessary to periodically make deterioration diagnosis and renovate to restore functions. In recent years, the terrestrial laser scanner allows us to capture dense point-clouds from large production facilities. Point-based virtual environment is promising for supporting maintenance of production facilities. In this paper, we discuss the deterioration diagnosis of production facilities based on point-clouds when the original shapes of production facilities are unknown. As an example of production facilities, we consider the blast furnace, which is mainly used to produce metals from molten materials. We classify deterioration on the blast furnace as wearing, scaffolding, and cracks, and automatically detect them from point-clouds. In our method, the normal wall shape is estimated by fitting low-resolution B-spline surfaces to point-clouds, and deterioration is detected as the difference between the reference surface and the point-clouds. While wearing and scaffolding regions are relatively large, cracks are thin lines. In order to detect different scales of deterioration, we introduce the reference surfaces with multiple resolutions. In our experiments, the three types of deterioration could be successfully detected from dense point-clouds.

scholarly journals EXTENDING THE LIFE OF VIRTUAL HERITAGE: REUSE OF TLS POINT CLOUDS IN SYNTHETIC STEREOSCOPIC SPHERICAL IMAGES

2017 ◽  
Vol XLII-2/W3 ◽  
pp. 317-323
Author(s):  
J. Garcia Fernandez ◽  
K. Tammi ◽  
A. Joutsiniemi
Keyword(s):  
Data Dissemination ◽  
Expert Knowledge ◽  
Laser Scanner ◽  
Point Clouds ◽  
Digital Data ◽  
Visual Fatigue ◽  
Built Heritage ◽  
Virtual Heritage ◽  
Dense Point ◽  
Spherical Images

Recent advances in Terrestrial Laser Scanner (TLS), in terms of cost and flexibility, have consolidated this technology as an essential tool for the documentation and digitalization of Cultural Heritage. However, once the TLS data is used, it basically remains stored and left to waste.How can highly accurate and dense point clouds (of the built heritage) be processed for its reuse, especially to engage a broader audience? This paper aims to answer this question by a channel that minimizes the need for expert knowledge, while enhancing the interactivity with the as-built digital data: <i>Virtual Heritage Dissemination through the production of VR content</i>. <br><br> Driven by the ProDigiOUs project’s guidelines on data dissemination (EU funded), this paper advances in a production path to transform the point cloud into virtual stereoscopic spherical images, taking into account the different visual features that produce depth perception, and especially those prompting visual fatigue while experiencing the VR content. Finally, we present the results of the Hiedanranta’s scans transformed into stereoscopic spherical animations.

scholarly journals ONLY IMAGE BASED FOR THE 3D METRIC SURVEY OF GOTHIC STRUCTURES BY USING FRAME CAMERAS AND PANORAMIC CAMERAS

2016 ◽  
Vol XLI-B5 ◽  
pp. 363-370
Author(s):  
A. Pérez Ramos ◽  
G. Robleda Prieto
Keyword(s):  
Laser Scanning ◽  
Imaging Techniques ◽  
Laser Scanner ◽  
Point Clouds ◽  
Office Work ◽  
Light Conditions ◽  
External Quality ◽  
Panoramic Cameras ◽  
Dense Point ◽  
Close Range

Indoor Gothic apse provides a complex environment for virtualization using imaging techniques due to its light conditions and architecture. Light entering throw large windows in combination with the apse shape makes difficult to find proper conditions to photo capture for reconstruction purposes. Thus, documentation techniques based on images are usually replaced by scanning techniques inside churches. Nevertheless, the need to use Terrestrial Laser Scanning (TLS) for indoor virtualization means a significant increase in the final surveying cost. So, in most cases, scanning techniques are used to generate dense point clouds. However, many Terrestrial Laser Scanner (TLS) internal cameras are not able to provide colour images or cannot reach the image quality that can be obtained using an external camera. Therefore, external quality images are often used to build high resolution textures of these models. This paper aims to solve the problem posted by virtualizing indoor Gothic churches, making that task more affordable using exclusively techniques base on images. It reviews a previous proposed methodology using a DSRL camera with 18-135 lens commonly used for close range photogrammetry and add another one using a HDR 360° camera with four lenses that makes the task easier and faster in comparison with the previous one. Fieldwork and office-work are simplified. The proposed methodology provides photographs in such a good conditions for building point clouds and textured meshes. Furthermore, the same imaging resources can be used to generate more deliverables without extra time consuming in the field, for instance, immersive virtual tours. In order to verify the usefulness of the method, it has been decided to apply it to the apse since it is considered one of the most complex elements of Gothic churches and it could be extended to the whole building.

scholarly journals TRATAMIENTO DE DATOS TLS MEDIANTE EL EMPLEO DE IMÁGENES ESFÉRICAS: APLICACIÓN A LA DOCUMENTACIÓN DE LA SALA CAPITULAR DE LA CATEDRAL DE JAÉN

2016 ◽  
Author(s):  
JOSE MIGUEL GOMEZ-LOPEZ ◽  
José L. Pérez-García ◽  
Carlos Colomo ◽  
Javier Cardenal ◽  
Emilio Mata
Keyword(s):  
Data Processing ◽  
Cultural Heritage ◽  
Information Extraction ◽  
Laser Scanner ◽  
Point Clouds ◽  
Terrestrial Laser Scanner ◽  
Dense Point ◽  
Study Case ◽  
Spherical Images

Nowadays, one of the techniques more used for documentation of cultural heritage is terrestrial laser scanner (TLS). This kind of instrumental has become essential in this kind of heritage projects. However, in many projects, the captured information by these systems are excessive, which hinders its data processing and information extraction. But when the documentation purpose is limited to the visualization or dissemination, the final products can be simpler than those obtained from the dense point clouds and the resulting detailed models. In this paper it is presented an approach based on TLS data processed with spherical images algorithms. TLS point clouds are used to simulate spherical images allowing the storage, processing, visualization and dissemination of both data and products. This approach has been applied to a real study case in the documentation of the chapterhouse of the Cathedral of Jaén.

scholarly journals A COMPARISON OF TREE SEGMENTATION METHODS USING VERY HIGH DENSITY AIRBORNE LASER SCANNER DATA

2017 ◽  
Vol XLII-2/W7 ◽  
pp. 285-290 ◽  
Author(s):  
F. Pirotti ◽  
M. Kobal ◽  
J. R. Roussel
Keyword(s):  
Accuracy Assessment ◽  
Single Point ◽  
Unit Cost ◽  
Laser Scanner ◽  
Tree Height ◽  
Point Clouds ◽  
Research Direction ◽  
Height Distribution ◽  
Canopy Area ◽  
Dense Point

Developments of LiDAR technology are decreasing the unit cost per single point (e.g. single-photo counting). This brings to the possibility of future LiDAR datasets having very dense point clouds. In this work, we process a very dense point cloud (~200 points per square meter), using three different methods for segmenting single trees and extracting tree positions and other metrics of interest in forestry, such as tree height distribution and canopy area distribution. The three algorithms are tested at decreasing densities, up to a lowest density of ~5 point per square meter. <br><br> Accuracy assessment is done using Kappa, recall, precision and F-Score metrics comparing results with tree positions from groundtruth measurements in six ground plots where tree positions and heights were surveyed manually. Results show that one method provides better Kappa and recall accuracy results for all cases, and that different point densities, in the range used in this study, do not affect accuracy significantly. Processing time is also considered; the method with better accuracy is several times slower than the other two methods and increases exponentially with point density. Best performer gave Kappa = 0.7. The implications of metrics for determining the accuracy of results of point positions’ detection is reported. Motives for the different performances of the three methods is discussed and further research direction is proposed.

Using semi-global matching point clouds to estimate growing stock at the plot and stand levels: application for a broadleaf-dominated forest in central Europe

2015 ◽  
Vol 45 (1) ◽  
pp. 111-123 ◽  
Author(s):  
Christoph Stepper ◽  
Christoph Straub ◽  
Hans Pretzsch
Keyword(s):  
Point Cloud ◽  
Laser Scanner ◽  
Model Performance ◽  
Point Clouds ◽  
Training Data ◽  
Explanatory Variables ◽  
Growing Stock ◽  
Dense Point ◽  
Global Matching ◽  
The Impact

Dense image-based point clouds have great potential to accurately assess forest attributes such as growing stock. The objective of this study was to combine height and spectral information obtained from UltraCamXp stereo images to model the growing stock in a highly structured broadleaf-dominated forest (77.5 km2) in southern Germany. We used semi-global matching (SGM) to generate a dense point cloud and subtracted elevation values obtained from airborne laser scanner (ALS) data to compute canopy height. Sixty-seven explanatory variables were derived from the point cloud and an orthoimage for use in the model. Two different approaches — the linear regression model (lm) and the random forests model (rf) — were tested. We investigated the impact that varying amounts of training data had on model performance. Plot data from a previously acquired set of 1875 inventory plots was systematically eliminated to form three progressively less dense subsets of 937, 461, and 226 inventory plots. Model evaluation at the plot level (size: 500 m2) yielded relative root mean squared errors (RMSEs) ranging from 31.27% to 35.61% for lm and from 30.92% to 36.02% for rf. At the stand level (mean stand size: 32 ha), RMSEs from 14.76% to 15.73% for lm and from 13.87% to 14.99% for rf were achieved. Therefore, similar results were obtained from both modeling approaches. The reduction in the number of inventory plots did not considerably affect the precision. Our findings underline the potential for aerial stereo imagery in combination with ALS-based terrain heights to support forest inventory and management.

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