Submitted by Fernando Souza (fernandoafsou@gmail.com) on 2017-08-16T12:39:19Z No. of bitstreams: 1 arquivototal.pdf: 6585826 bytes, checksum: 7c4b9710f530b142defafd4f6be7d1a8 (MD5) / Made available in DSpace on 2017-08-16T12:39:19Z (GMT). No. of bitstreams: 1 arquivototal.pdf: 6585826 bytes, checksum: 7c4b9710f530b142defafd4f6be7d1a8 (MD5) Previous issue date: 2016-02-19 / Abstract This paper aims to present a novel approach in planar RGB-D SLAM, here called Object Subtraction SLAM (OS-SLAM), using only low-cost RGB-D sensors such as the Microsoft Kinect. Our approach subtracts objects from the 3D environment and creates a clean 3D map projecting estimated planes without identified objects encountered along the mapping procedure aiming to increase accuracy. To validate our approach we performed four experiments, three in a real environment and one with an open dataset comparing them with other state-of-the-art algorithms. The algorithms were applied to a TurtleBot 2 platform which has a RGB-D sensor as its main sensor. The results demonstrated the efficiency on generated a clean and accurate map using the OS-SLAM algorithm. / Resumo Este trabalho tem como objetivo apresentar uma nova abordagem em RGB-D Planar SLAM, aqui chamada SLAM Baseado em Subtração de Objetos (OS-SLAM), utilizando apenas sensores RGB-D de baixo custo, como o Microsoft Kinect. Essa abordagem subtrai objetos do ambiente 3D e cria um mapa 3D limpo, projetando planos estimados sem os objetos identificados e encontrados ao longo do procedimento de mapeamento. Para validar esta abordagem, foram realizados quatro experimentos. Três deles em um ambiente real e um com um conjunto de dados abertos comparando-os com outros algoritmos do estado-da-arte. Os algoritmos foram aplicados a uma plataforma turtlebot 2, que tem um sensor RGB-D como seu sensor principal. Os resultados demonstraram a eficiência na geração de mapas limpos e precisos utilizando o algoritmo OS-SLAM

Cette thèse propose des modèles cartographiques à grande échelle d'environnements urbains et ruraux à l'aide de données en 3D acquises par plusieurs robots. La mémoire contribue de deux manières principales au domaine de recherche de la cartographie. La première contribution est la création d'une nouvelle structure, CoMapping, qui permet de générer des cartes 3D de façon collaborative. Cette structure s’applique aux environnements extérieurs en ayant une approche décentralisée. La fonctionnalité de CoMapping comprend les éléments suivants : Tout d’abord, chaque robot réalise la construction d'une carte de son environnement sous forme de nuage de points.Pour cela, le système de cartographie a été mis en place sur des ordinateurs dédiés à chaque voiture, en traitant les mesures de distance à partir d'un LiDAR 3D se déplaçant en six degrés de liberté (6-DOF). Ensuite, les robots partagent leurs cartes locales et fusionnent individuellement les nuages de points afin d'améliorer leur estimation de leur cartographie locale. La deuxième contribution clé est le groupe de métriques qui permettent d'analyser les processus de fusion et de partage de cartes entre les robots. Nous présentons des résultats expérimentaux en vue de valider la structure CoMapping et ses métriques. Tous les tests ont été réalisés dans des environnements extérieurs urbains du campus de l’École Centrale de Nantes ainsi que dans des milieux ruraux. / This thesis proposes large-scale mapping model of urban and rural environments using 3D data acquired by several robots. The work contributes in two main ways to the research field of mapping. The first contribution is the creation of a new framework, CoMapping, which allows to generate 3D maps in a cooperative way. This framework applies to outdoor environments with a decentralized approach. The CoMapping's functionality includes the following elements: First of all, each robot builds a map of its environment in point cloud format.To do this, the mapping system was set up on computers dedicated to each vehicle, processing distance measurements from a 3D LiDAR moving in six degrees of freedom (6-DOF). Then, the robots share their local maps and merge the point clouds individually to improve their local map estimation. The second key contribution is the group of metrics that allow to analyze the merging and card sharing processes between robots. We present experimental results to validate the CoMapping framework with their respective metrics. All tests were carried out in urban outdoor environments on the surrounding campus of the École Centrale de Nantes as well as in rural areas.

The dissertation deals with utilisation of multispectral optical measurement for data fusion that may be used for visual telepresence and indoor/outdoor mapping by heterogeneous mobile robotic system. Optical proximity sensors, thermal imagers, and tricolour cameras are used for the fusion. The described algorithms are optimised to work in real-time and implemented on CASSANDRA robotic system made by our robotic research group.

Darbe yra siekiama išanalizuoti trimačio kartografinio vaizdo (žemėlapio) informatyvumo galimybes autoriaus sukurtų trimačių žemėlapių (modelių) pagrindu. Darbe apžvelgiami trimačio kartografinio vaizdo kūrimo metodai ir priemonės. Svarbų indelį trimačių kartografinių kūrinių sudaryme šiandien vaidina atskira grafinio dizaino kryptis – infografika. Tačiau trimatį kartografavimą palaikančių kompiuterinių programų nėra daug, pagrindinės iš jų leidžiančios sudarinėti erdvinius modelius yra ArcGIS ir AutoCAD. ArcGIS grafinio trimačio vizualizavimo ir Google SketchUp programinės įrangos pagrindu sukurti 4 trimačiai įvairių teminių sričių žemėlapiai. Informatyvumo nustatymo tikslui pasiekti yra vykdomas trimačių kartografinių ženklų informatyvumo, informacijos talpumo (kartografuojamų rodiklių kiekio atžvilgiu) bei panaudojimo tyrimas. Taip pat atliekama kartografijos profesionalų bei teminių sričių specialistų apklausa. Rezultatuose išryškėja pradinių kartografuojamų duomenų analizės svarba. Tinkamai parinkus kartografinį metodą leidžiantį atskleisti trečios dimensijos papildomas galimybes trimatis žemėlapis tampa informatyvesnis lyginant su įprastu planiniu kartografiniu vaizdu. Santykinių – hipotetinių paviršių žemėlapiai, kuriuose naudojami struktūriniai ženklai tinkamiausi socialinių rodiklių, o kombinuojant su tolydžiu paviršiumi – ir fiziniams reiškiniams kartografuoti. / The author is seeking to analize three-dimensional cartographical view informative opportunities created by the author 3D maps (models) basis. The paper gives an overview of 3D cartographic display methods and instruments. Important role in nowadays 3D mapping plays a separate graphic design trend – infographics. However 3D mapping computer programs are not many, the main ones allowing a spatial model are ArcGIS and AutoCAD. Basis of 3D graphics and imaging software ArcGIS together with Google SketchUp were created 4 different 3D thematic maps. Informative purpose is atchieved by research of 3D cartographic signs informative-capacity and uses potential. Also were done a poll of mapping professionals and thematic cartography specialists. Initial results revealed the importance of mapping data analysis. Properly selected mapping method allows to reveal additional opportunities of third dimension, in this way the map becomes more informative comparing it with two-dimensional map. Relative – hyphotethical surfaces maps in which are used structural cartographic signs is most appropriate for mapping of social indicators. And in the combination with continual surface (terrain model) – is appropriate for mapping of natural phenomena.

This thesis is about the intelligent compression of large 3D point cloud datasets. The non-parametric method that we describe simultaneously generates a continuous representation of the workspace surfaces from discrete laser samples and decimates the dataset, retaining only locally salient samples. Our framework attains decimation factors in excess of two orders of magnitude without significant degradation in fidelity. The work presented here has a specific focus on gathering and processing laser measurements taken from a moving platform in outdoor workspaces. We introduce a somewhat unusual parameterisation of the problem and look to Gaussian Processes as the fundamental machinery in our processing pipeline. Our system compresses laser data in a fashion that is naturally sympathetic to the underlying structure and complexity of the workspace. In geometrically complex areas, compression is lower than that in geometrically bland areas. We focus on this property in detail and it leads us well beyond a simple application of non-parametric techniques. Indeed, towards the end of the thesis we develop a non-stationary GP framework whereby our regression model adapts to the local workspace complexity. Throughout we construct our algorithms so that they may be efficiently implemented. In addition, we present a detailed analysis of the proposed system and investigate model parameters, metric errors and data compression rates. Finally, we note that this work is predicated on a substantial amount of robotics engineering which has allowed us to produce a high quality, peer reviewed, dataset - the first of its kind.

The aim of this work is to develop research on 3D building modeling. In particular, the research in aerial-based 3D building reconstruction is a topic very developed since 1990. However, it is necessary to pursue the research since the actual approaches for 3D massive building reconstruction (although efficient) still encounter problems in generalization, coherency, accuracy. Besides, the recent developments of street acquisition systems such as Mobile Mapping Systems open new perspectives for improvements in building modeling in the sense that the terrestrial data (very dense and accurate) can be exploited with more performance (in comparison to the aerial investigation) to enrich the building models at facade level (e.g., geometry, texturing).Hence, aerial and terrestrial based building modeling approaches are individually proposed. At aerial level, we describe a direct and featureless approach for simple polyhedral building reconstruction from a set of calibrated aerial images. At terrestrial level, several approaches that essentially describe a 3D urban facade modeling pipeline are proposed, namely, the street point cloud segmentation and classification, the geometric modeling of urban facade and the occlusion-free facade texturing

This thesis presents a use of 3D laser range finder designed for purposes of autnonomous mobile systems. The 3D scanner is built as extension of 2D laser range finder with rotation module. In the first section is described laser range finder SICK LMS 291 and his pitching construction along with used software tools. Second part deals with design and implementation of algorithms for data reading and their processing with methods of surface reconstruction, octree and object segmentation with Hough transform.

The diploma thesis deals with the use of Laser-Induced Breakdown Spectroscopy (LIBS) for depth profiling and 3D mapping of the zinc-coated steel used in the automotive industry. Before creating depth maps and depth profiles, optimization of the experiment was performed. It was shown that the LIBS technique is suited for making depth profiles and depth maps. The theoretical part deals with the description of the LIBS instrumentation, characteristics of plasma, and assembling of scientific papers which reflect the up to date knowledge about depth profiling and mapping with the use of the LIBS technique. The experimental part describes the optimization of the experiment. Gate delay, the depth and the diameter of craters using the profilometer, the position of the focal plane relative to the sample surface, and selection of spectral lines with the smallest residual signal and small scattering of data were optimized. Depth profiles of zinc, iron, chromium and manganese with the depth map of zinc and iron were made, and also the depth resolution for both elements was calculated.

Natural caves represent one of the most difficult environments to map with modern 3D technologies. In this study I tested two relatively new methods for 3D mapping in Tipton-Haynes Cave near Johnson City, Tennessee: Structure from Motion Photogrammetry and Computer Vision using Tango, an RGB-D (Red Green Blue and Depth) technology. Many different aspects of these two methods were analyzed with respect to the needs of average cave explorers. Major considerations were cost, time, accuracy, durability, simplicity, lighting setup, and drift. The 3D maps were compared to a conventional cave map drafted with measurements from a modern digital survey instrument called the DistoX2, a clinometer, and a measuring tape. Both 3D mapping methods worked, but photogrammetry proved to be too time consuming and laborious for capturing more than a few meters of passage. RGB-D was faster, more accurate, and showed promise for the future of low-cost 3D cave mapping.

No description available.