Sistema de modelização tridimensional para ambientes não estruturados

A navegação de veículos autónomos em ambientes não estruturados continua a ser um problema em aberto. A complexidade do mundo real ainda é um desafio. A difícil caracterização do relevo irregular, dos objectos dinâmicos e pouco distintos(e a inexistência de referências de localização) tem sido alvo de estudo e do desenvolvimento de vários métodos que permitam de uma forma eficiente, e em tempo real, modelizar o espaço tridimensional. O trabalho realizado ao longo desta dissertação insere-se na estratégia do Laboratório de Sistemas Autónomos (LSA) na pesquisa e desenvolvimento de sistemas sensoriais que possibilitem o aumento da capacidade de percepção das plataformas robóticas. O desenvolvimento de um sistema de modelização tridimensional visa acrescentar aos projectos LINCE (Land INtelligent Cooperative Explorer) e TIGRE (Terrestrial Intelligent General proposed Robot Explorer) maior autonomia e capacidade de exploração e mapeamento. Apresentamos alguns sensores utilizados para a aquisição de modelos tridimensionais, bem como alguns dos métodos mais utilizados para o processo de mapeamento, e a sua aplicação em plataformas robóticas. Ao longo desta dissertação são apresentadas e validadas técnicas que permitem a obtenção de modelos tridimensionais. É abordado o problema de analisar a cor e geometria dos objectos, e da criação de modelos realistas que os representam. Desenvolvemos um sistema que nos permite a obtenção de dados volumétricos tridimensionais, a partir de múltiplas leituras de um Laser Range Finder bidimensional de médio alcance. Aos conjuntos de dados resultantes associamos numa nuvem de pontos coerente e referenciada. Foram desenvolvidas e implementadas técnicas de segmentação que permitem inspeccionar uma nuvem de pontos e classifica-la quanto às suas características geométricas, bem como ao tipo de estruturas que representem. São apresentadas algumas técnicas para a criação de Mapas de Elevação Digital, tendo sido desenvolvida um novo método que tira partido da segmentação efectuada

Building 3D City Models: Testing and Comparing Laser Scanning and Low-Cost UAV Data Using FOSS Technologies

Contém resumo

Extracció del mapa de profunditat a partir d'una seqüència d'imatges

Aquest projecte resol les fases inicials d'un altre projecte més gran que té com a objectiu la conversió automàtica de seqüències d'imatges a 3D. El projecte s'ha centrat en la reconstrucció calibrada de col·leccions d'imatges mitjançant la tècnica anomenada structure from motion. Aquesta tècnica forma part de l'àmbit de la visió per computador i s'utilitza per obtenir la posició i l'orientació de les diferents càmeres juntament amb una reconstrucció 3D de l'escena en forma de núvol de punts.

Computing the persistent homology of range images with alpha shapes

Laser scanning is becoming an increasingly popular method for measuring 3D objects in industrial design. Laser scanners produce a cloud of 3D points. For CAD software to be able to use such data, however, this point cloud needs to be turned into a vector format. A popular way to do this is to triangulate the assumed surface of the point cloud using alpha shapes. Alpha shapes start from the convex hull of the point cloud and gradually refine it towards the true surface of the object. Often it is nontrivial to decide when to stop this refinement. One criterion for this is to do so when the homology of the object stops changing. This is known as the persistent homology of the object. The goal of this thesis is to develop a way to compute the homology of a given point cloud when processed with alpha shapes, and to infer from it when the persistent homology has been achieved. Practically, the computation of such a characteristic of the target might be applied to power line tower span analysis.

Remote sensing for three-dimensional modelling of hydromorphology

Successful management of rivers requires an understanding of the fluvial processes that govern them. This, in turn cannot be achieved without a means of quantifying their geomorphology and hydrology and the spatio-temporal interactions between them, that is, their hydromorphology. For a long time, it has been laborious and time-consuming to measure river topography, especially in the submerged part of the channel. The measurement of the flow field has been challenging as well, and hence, such measurements have long been sparse in natural environments. Technological advancements in the field of remote sensing in the recent years have opened up new possibilities for capturing synoptic information on river environments. This thesis presents new developments in fluvial remote sensing of both topography and water flow. A set of close-range remote sensing methods is employed to eventually construct a high-resolution unified empirical hydromorphological model, that is, river channel and floodplain topography and three-dimensional areal flow field. Empirical as well as hydraulic theory-based optical remote sensing methods are tested and evaluated using normal colour aerial photographs and sonar calibration and reference measurements on a rocky-bed sub-Arctic river. The empirical optical bathymetry model is developed further by the introduction of a deep-water radiance parameter estimation algorithm that extends the field of application of the model to shallow streams. The effect of this parameter on the model is also assessed in a study of a sandy-bed sub-Arctic river using close-range high-resolution aerial photography, presenting one of the first examples of fluvial bathymetry modelling from unmanned aerial vehicles (UAV). Further close-range remote sensing methods are added to complete the topography integrating the river bed with the floodplain to create a seamless high-resolution topography. Boat- cart- and backpack-based mobile laser scanning (MLS) are used to measure the topography of the dry part of the channel at a high resolution and accuracy. Multitemporal MLS is evaluated along with UAV-based photogrammetry against terrestrial laser scanning reference data and merged with UAV-based bathymetry to create a two-year series of seamless digital terrain models. These allow the evaluation of the methodology for conducting high-resolution change analysis of the entire channel. The remote sensing based model of hydromorphology is completed by a new methodology for mapping the flow field in 3D. An acoustic Doppler current profiler (ADCP) is deployed on a remote-controlled boat with a survey-grade global navigation satellite system (GNSS) receiver, allowing the positioning of the areally sampled 3D flow vectors in 3D space as a point cloud and its interpolation into a 3D matrix allows a quantitative volumetric flow analysis. Multitemporal areal 3D flow field data show the evolution of the flow field during a snow-melt flood event. The combination of the underwater and dry topography with the flow field yields a compete model of river hydromorphology at the reach scale.

Reconstruction tridimensionnelle pour projection sur surfaces arbitraires.

Ce mémoire s'inscrit dans le domaine de la vision par ordinateur. Elle s'intéresse à la calibration de systèmes de caméras stéréoscopiques, à la mise en correspondance caméra-projecteur, à la reconstruction 3D, à l'alignement photométrique de projecteurs, au maillage de nuages de points, ainsi qu'au paramétrage de surfaces. Réalisé dans le cadre du projet LightTwist du laboratoire Vision3D, elle vise à permettre la projection sur grandes surfaces arbitraires à l'aide de plusieurs projecteurs. Ce genre de projection est souvent utilisé en arts technologiques, en théâtre et en projection architecturale. Dans ce mémoire, on procède au calibrage des caméras, suivi d'une reconstruction 3D par morceaux basée sur une méthode active de mise en correspondance, la lumière non structurée. Après un alignement et un maillage automatisés, on dispose d'un modèle 3D complet de la surface de projection. Ce mémoire introduit ensuite une nouvelle approche pour le paramétrage de modèles 3D basée sur le calcul efficace de distances géodésiques sur des maillages. L'usager n'a qu'à délimiter manuellement le contour de la zone de projection sur le modèle. Le paramétrage final est calculé en utilisant les distances obtenues pour chaque point du modèle. Jusqu'à maintenant, les méthodes existante ne permettaient pas de paramétrer des modèles ayant plus d'un million de points.

Automatic Orientation of Multi-Scale Terrestrial Images for 3D Reconstruction

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Diseño, optimización y análisis de sistemas basados en técnicas láser, para el modelado geométrico, registro y documentación, aplicados a entidades de interés patrimonial.

El objetivo de la presente tesis doctoral es el desarrollo e implementación de un sistema para mejorar la metodología de extracción de la información geométrica necesaria asociada a los procesos de documentación de entidades de interés patrimonial, a partir de la información proporcionada por el empleo de sensores láser, tanto aéreos como terrestres. Para ello, inicialmente se realiza una presentación y justificación de los antecedentes y la problemática en el registro de información geométrica para el patrimonio, detallando todos aquellos sistemas de registro y análisis de la información geométrica utilizados en la actualidad. Este análisis permitirá realizar la comparación con los sistemas de registro basados en técnicas láser, aportando sugerencias de utilización para cada caso concreto. Posteriormente, se detallan los sistemas de registro basados en técnicas láser, comenzando por los sensores aerotransportados y concluyendo con el análisis pormenorizado de los sensores terrestres, tanto en su aplicación en modo estático como móvil. Se exponen las características técnicas y funcionamiento de cada uno de ellos, así como los ámbitos de aplicación y productos generados. Se analizan las fuentes de error que determinan la precisión que puede alcanzar el sistema. Tras la exposición de las características de los sistemas LiDAR, se detallan los procesos a realizar con los datos extraídos para poder generar la información necesaria para los diferentes tipos de objetos analizados. En esta exposición, se hace hincapié en los posibles riesgos que pueden ocurrir en algunas fases delicadas y se analizarán los diferentes algoritmos de filtrado y clasificación de los puntos, fundamentales en el procesamiento de la información LiDAR. Seguidamente, se propone una alternativa para optimizar los modelos de procesamiento existentes, basándose en el desarrollo de algoritmos nuevos y herramientas informáticas que mejoran el rendimiento en la gestión de la información LiDAR. En la implementación, se han tenido en cuenta características y necesidades particulares de la documentación de entidades de interés patrimonial, así como los diferentes ámbitos de utilización del LiDAR, tanto aéreo como terrestre. El resultado es un organigrama de las tareas a realizar desde la nube de puntos LiDAR hasta el cálculo de los modelos digitales del terreno y de superficies. Para llevar a cabo esta propuesta, se han desarrollado hasta 19 algoritmos diferentes que comprenden implementaciones para el modelado en 2.5D y 3D, visualización, edición, filtrado y clasificación de datos LiDAR, incorporación de información de sensores pasivos y cálculo de mapas derivados, tanto raster como vectoriales, como pueden ser mapas de curvas de nivel y ortofotos. Finalmente, para dar validez y consistencia a los desarrollos propuestos, se han realizado ensayos en diferentes escenarios posibles en un proceso de documentación del patrimonio y que abarcan desde proyectos con sensores aerotransportados, proyectos con sensores terrestres estáticos a media y corta distancia, así como un proyecto con un sensor terrestre móvil. Estos ensayos han permitido definir los diferentes parámetros necesarios para el adecuado funcionamiento de los algoritmos propuestos. Asimismo, se han realizado pruebas objetivas expuestas por la ISPRS para la evaluación y comparación del funcionamiento de algoritmos de clasificación LiDAR. Estas pruebas han permitido extraer datos de rendimiento y efectividad del algoritmo de clasificación presentado, permitiendo su comparación con otros algoritmos de prestigio existentes. Los resultados obtenidos han constatado el funcionamiento satisfactorio de la herramienta. Esta tesis está enmarcada dentro del proyecto Consolider-Ingenio 2010: “Programa de investigación en tecnologías para la valoración y conservación del patrimonio cultural” (ref. CSD2007-00058) realizado por el Consejo Superior de Investigaciones Científicas y la Universidad Politécnica de Madrid. ABSTRACT: The goal of this thesis is the design, development and implementation of a system to improve the extraction of useful geometric information in Heritage documentation processes. This system is based on information provided by laser sensors, both aerial and terrestrial. Firstly, a presentation of recording geometric information for Heritage processes is done. Then, a justification of the background and problems is done too. Here, current systems for recording and analyzing the geometric information are studied. This analysis will perform the comparison with the laser system techniques, providing suggestions of use for each specific case. Next, recording systems based on laser techniques are detailed. This study starts with airborne sensors and ends with terrestrial ones, both in static and mobile application. The technical characteristics and operation of each of them are described, as well as the areas of application and generated products. Error sources are also analyzed in order to know the precision this technology can achieve. Following the presentation of the LiDAR system characteristics, the processes to generate the required information for different types of scanned objects are described; the emphasis is on the potential risks that some steps can produce. Moreover different filtering and classification algorithms are analyzed, because of their main role in LiDAR processing. Then, an alternative to optimize existing processing models is proposed. It is based on the development of new algorithms and tools that improve the performance in LiDAR data management. In this implementation, characteristics and needs of the documentation of Heritage entities have been taken into account. Besides, different areas of use of LiDAR are considered, both air and terrestrial. The result is a flowchart of tasks from the LiDAR point cloud to the calculation of digital terrain models and digital surface models. Up to 19 different algorithms have been developed to implement this proposal. These algorithms include implementations for 2.5D and 3D modeling, viewing, editing, filtering and classification of LiDAR data, incorporating information from passive sensors and calculation of derived maps, both raster and vector, such as contour maps and orthophotos. Finally, in order to validate and give consistency to the proposed developments, tests in different cases have been executed. These tests have been selected to cover different possible scenarios in the Heritage documentation process. They include from projects with airborne sensors, static terrestrial sensors (medium and short distances) to mobile terrestrial sensor projects. These tests have helped to define the different parameters necessary for the appropriate functioning of the proposed algorithms. Furthermore, proposed tests from ISPRS have been tested. These tests have allowed evaluating the LiDAR classification algorithm performance and comparing it to others. Therefore, they have made feasible to obtain performance data and effectiveness of the developed classification algorithm. The results have confirmed the reliability of the tool. This investigation is framed within Consolider-Ingenio 2010 project titled “Programa de investigación en tecnologías para la valoración y conservación del patrimonio cultural” (ref. CSD2007-00058) by Consejo Superior de Investigaciones Científicas and Universidad Politécnica de Madrid.

Overlapping Range Images using Genetics Algorithms

El artículo aborda el problema del encaje de diversas imágenes de una misma escena capturadas por escáner 3d para generar un único modelo tridimensional. Para ello se utilizaron algoritmos genéticos. ABSTRACT: This work introduces a solution based on genetic algorithms to find the overlapping area between two point cloud captures obtained from a three-dimensional scanner. Considering three translation coordinates and three rotation angles, the genetic algorithm evaluates the matching points in the overlapping area between the two captures given that transformation. Genetic simulated annealing is used to improve the accuracy of the results obtained by the genetic algorithm.

Deciduous tree reconstruction algorithm based on cylinder fitting from mobile terrestrial laser scanned point clouds

Vector reconstruction of objects from an unstructured point cloud obtained with a LiDAR-based system (light detection and ranging) is one of the most promising methods to build three dimensional models of orchards. The cylinder fitting method for woody structure reconstruction of leafless trees from point clouds obtained with a mobile terrestrial laser scanner (MTLS) has been analysed. The advantage of this method is that it performs reconstruction in a single step. The most time consuming part of the algorithm is generation of the cylinder direction, which must be recalculated at the inclusion of each point in the cylinder. The tree skeleton is obtained at the same time as the cluster of cylinders is formed. The method does not guarantee a unique convergence and the reconstruction parameter values must be carefully chosen. A balanced processing of clusters has also been defined which has proven to be very efficient in terms of processing time by following the hierarchy of branches, predecessors and successors. The algorithm was applied to simulated MTLS of virtual orchard models and to MTLS data of real orchards. The constraints applied in the method have been reviewed to ensure better convergence and simpler use of parameters. The results obtained show a correct reconstruction of the woody structure of the trees and the algorithm runs in linear logarithmic time

3DCOMET: 3D compression methods test dataset

The use of 3D data in mobile robotics applications provides valuable information about the robot’s environment. However usually the huge amount of 3D information is difficult to manage due to the fact that the robot storage system and computing capabilities are insufficient. Therefore, a data compression method is necessary to store and process this information while preserving as much information as possible. A few methods have been proposed to compress 3D information. Nevertheless, there does not exist a consistent public benchmark for comparing the results (compression level, distance reconstructed error, etc.) obtained with different methods. In this paper, we propose a dataset composed of a set of 3D point clouds with different structure and texture variability to evaluate the results obtained from 3D data compression methods. We also provide useful tools for comparing compression methods, using as a baseline the results obtained by existing relevant compression methods.

Point clouds of measurements in the Dechen Cave near Iserlohn, Germany

Modeling natural phenomena from 3D information enhances our understanding of the environment. Dense 3D point clouds are increasingly used as highly detailed input datasets. In addition to the capturing techniques of point clouds with LiDAR, low-cost sensors have been released in the last few years providing access to new research fields and facilitating 3D data acquisition for a broader range of applications. This letter presents an analysis of different speleothem features using 3D point clouds acquired with the gaming device Microsoft® Kinect. We compare the Kinect sensor with terrestrial LiDAR reference measurements using the KinFu pipeline for capturing complete 3D objects (< 4m**3). The results demonstrate the suitability of the Kinect to capture flowstone walls and to derive morphometric parameters of cave features. Although the chosen capturing strategy (KinFu) reveals a high correlation (R2=0.92) of stalagmite morphometry along the vertical object axis, a systematic overestimation (22% for radii and 44% for volume) is found. The comparison of flowstone wall datasets predominantly shows low differences (mean of 1 mm with 7 mm standard deviation) of the order of the Kinect depth precision. For both objects the major differences occur at strongly varying and curved surface structures (e.g. with fine concave parts).

Modelo para reconstrução 3D de cenas baseado em imagens

3D Reconstruction is the process used to obtain a detailed graphical model in three dimensions that represents some real objectified scene. This process uses sequences of images taken from the scene, so it can automatically extract the information about the depth of feature points. These points are then highlighted using some computational technique on the images that compose the used dataset. Using SURF feature points this work propose a model for obtaining depth information of feature points detected by the system. At the ending, the proposed system extract three important information from the images dataset: the 3D position for feature points; relative rotation and translation matrices between images; the realtion between the baseline for adjacent images and the 3D point accuracy error found.

Creazione di una costmap 2D per la navigazione di un rover terrestre

L’obiettivo di questa tesi è riuscire ad elaborare una point cloud 3D proveniente dal laser scanner per individuare possibili ostacoli e creare con essa, successivamente, una mappa che permetta la navigazione di un rover.

Impact of Curling and Warping on Concrete Pavement, TR-668, 2016

Portland cement concrete (PCC) pavement undergoes repeated environmental load-related deflection resulting from temperature and moisture variations across the pavement depth. This phenomenon, referred to as PCC pavement curling and warping, has been known and studied since the mid-1920s. Slab curvature can be further magnified under repeated traffic loads and may ultimately lead to fatigue failures, including top-down and bottom-up transverse, longitudinal, and corner cracking. It is therefore important to measure the “true” degree of curling and warping in PCC pavements, not only for quality control (QC) and quality assurance (QA) purposes, but also to achieve a better understanding of its relationship to long-term pavement performance. In order to better understand the curling and warping behavior of PCC pavements in Iowa and provide recommendations to mitigate curling and warping deflections, field investigations were performed at six existing sites during the late fall of 2015. These sites included PCC pavements with various ages, slab shapes, mix design aspects, and environmental conditions during construction. A stationary light detection and ranging (LiDAR) device was used to scan the slab surfaces. The degree of curling and warping along the longitudinal, transverse, and diagonal directions was calculated for the selected slabs based on the point clouds acquired using LiDAR. The results and findings are correlated to variations in pavement performance, mix design, pavement design, and construction details at each site. Recommendations regarding how to minimize curling and warping are provided based on a literature review and this field study. Some examples of using point cloud data to build three-dimensional (3D) models of the overall curvature of the slab shape are presented to show the feasibility of using this 3D analysis method for curling and warping analysis.