Multi-level information fusion for environment aware robotic navigation

This thesis develops the hardware and software framework for an integrated navigation system. Dynamic data fusion algorithms are used to develop a system with a high level of resistance to the typical problems that affect standard navigation systems.

Three dimensional digitisation of plant leaves

Realistic plant models are important for leaf area and plant volume estimation, reconstruction of growth canopies, structure generation of the plant, reconstruction of leaf surfaces and agrichemical spray droplet modelling. This article investigates several different scanning devices for obtaining a three dimensional digitisation of plant leaves with a point cloud resolution of 200-500μm. The devices tested were a Roland mdx-20, Microsoft Kinect, Roland lpx-250, Picoscan and Artec S. The applicability of each of these devices for scanning plant leaves is discussed. The most suitable tested digitisation device for scanning plant leaves is the Artec S scanner.

Efficiently capturing large, complex cultural heritage sites with a handheld mobile 3D laser mapping system

Accurate three-dimensional representations of cultural heritage sites are highly valuable for scientific study, conservation, and educational purposes. In addition to their use for archival purposes, 3D models enable efficient and precise measurement of relevant natural and architectural features. Many cultural heritage sites are large and complex, consisting of multiple structures spatially distributed over tens of thousands of square metres. The process of effectively digitising such geometrically complex locations requires measurements to be acquired from a variety of viewpoints. While several technologies exist for capturing the 3D structure of objects and environments, none are ideally suited to complex, large-scale sites, mainly due to their limited coverage or acquisition efficiency. We explore the use of a recently developed handheld mobile mapping system called Zebedee in cultural heritage applications. The Zebedee system is capable of efficiently mapping an environment in three dimensions by continually acquiring data as an operator holding the device traverses through the site. The system was deployed at the former Peel Island Lazaret, a culturally significant site in Queensland, Australia, consisting of dozens of buildings of various sizes spread across an area of approximately 400 × 250 m. With the Zebedee system, the site was scanned in half a day, and a detailed 3D point cloud model (with over 520 million points) was generated from the 3.6 hours of acquired data in 2.6 hours. We present results demonstrating that Zebedee was able to accurately capture both site context and building detail comparable in accuracy to manual measurement techniques, and at a greatly increased level of efficiency and scope. The scan allowed us to record derelict buildings that previously could not be measured because of the scale and complexity of the site. The resulting 3D model captures both interior and exterior features of buildings, including structure, materials, and the contents of rooms.

An application of fuzzy DL-Based semantic perception to soil container classification

Semantic perception and object labeling are key requirements for robots interacting with objects on a higher level. Symbolic annotation of objects allows the usage of planning algorithms for object interaction, for instance in a typical fetchand-carry scenario. In current research, perception is usually based on 3D scene reconstruction and geometric model matching, where trained features are matched with a 3D sample point cloud. In this work we propose a semantic perception method which is based on spatio-semantic features. These features are defined in a natural, symbolic way, such as geometry and spatial relation. In contrast to point-based model matching methods, a spatial ontology is used where objects are rather described how they "look like", similar to how a human would described unknown objects to another person. A fuzzy based reasoning approach matches perceivable features with a spatial ontology of the objects. The approach provides a method which is able to deal with senor noise and occlusions. Another advantage is that no training phase is needed in order to learn object features. The use-case of the proposed method is the detection of soil sample containers in an outdoor environment which have to be collected by a mobile robot. The approach is verified using real world experiments.

Estudio comparativo del láser escáner aplicado a patrimonio

[ES] Este proyecto se ha realizado a partir de los datos del siguiente proyecto de documentación geométrica, desde donde pueden encontrarse enlaces adicionales a otros documentos relacionados:

Avaliação de correlações para propriedades físico-químicas de frações de petróleo

O petróleo é uma mistura complexa consistindo em um número muito grande de hidrocarbonetos. A descrição completa de todos os hidrocarbonetos existentes nessas misturas é inviável experimentalmente ou consome tempo excessivo em simulações computacionais. Por esta razão, uma abordagem molecular completa para cálculos de propriedades dessas misturas é substituído por uma abordagem pseudo-componente ou por correlações entre propriedades macroscópicas. Algumas dessas propriedades são utilizadas de acordo com a regulamentação de venda de combustíveis, e.g., para gasolina. Dependendo do esquema de refino e do óleo cru utilizado para produção desse combustível, uma larga variedade de valores é encontrada para as propriedades de correntes de processo que compõe o combustível final. A fim de planejar com precisão adequada a mistura dessas correntes, modelos devem estar disponíveis para o cálculo preciso das propriedades necessárias. Neste trabalho, oito séries de combustíveis brasileiros e duas séries de combustíveis estrangeiros foram analisadas: frações de gasolina, querosene, gasóleo e diesel. As propriedades analisadas para as frações são: número de octano, teor de aromáticos, teor de enxofre, índice de refração, densidade, ponto de fulgor, ponto de fluidez, ponto de congelamento, ponto de névoa, ponto de anilina, pressão de vapor Reid e número de cetano. Diversas correlações foram avaliadas e os melhores desempenhos foram destacados, permitindo uma estimação precisa das propriedades do combustível avaliado. Um processo de re-estimação de parâmetros foi aplicado e novos modelos foram ajustados em comparação com os dados experimentais. Esta estratégia permitiu uma estimativa mais exata das propriedades analisadas, sendo verificada por um aumento considerável no desempenho estatístico dos modelos. Além disso, foi apresentado o melhor modelo para cada propriedade e cada série

Live 3D shape reconstruction, recognition and registration

We present a video-based system which interactively captures the geometry of a 3D object in the form of a point cloud, then recognizes and registers known objects in this point cloud in a matter of seconds (fig. 1). In order to achieve interactive speed, we exploit both efficient inference algorithms and parallel computation, often on a GPU. The system can be broken down into two distinct phases: geometry capture, and object inference. We now discuss these in further detail. © 2011 IEEE.

Progressive 3D reconstruction of infrastructure with videogrammetry

A number of methods are commonly used today to collect infrastructure's spatial data (time-of-flight, visual triangulation, etc.). However, current practice lacks a solution that is accurate, automatic, and cost-efficient at the same time. This paper presents a videogrammetric framework for acquiring spatial data of infrastructure which holds the promise to address this limitation. It uses a calibrated set of low-cost high resolution video cameras that is progressively traversed around the scene and aims to produce a dense 3D point cloud which is updated in each frame. It allows for progressive reconstruction as opposed to point-and-shoot followed by point cloud stitching. The feasibility of the framework is studied in this paper. Required steps through this process are presented and the unique challenges of each step are identified. Results specific to each step are also presented.

Automated 3D Structure Inference of Civil Infrastructure Using a Stereo Camera Set

The commercial far-range (>10m) infrastructure spatial data collection methods are not completely automated. They need significant amount of manual post-processing work and in some cases, the equipment costs are significant. This paper presents a method that is the first step of a stereo videogrammetric framework and holds the promise to address these issues. Under this method, video streams are initially collected from a calibrated set of two video cameras. For each pair of simultaneous video frames, visual feature points are detected and their spatial coordinates are then computed. The result, in the form of a sparse 3D point cloud, is the basis for the next steps in the framework (i.e., camera motion estimation and dense 3D reconstruction). A set of data, collected from an ongoing infrastructure project, is used to show the merits of the method. Comparison with existing tools is also shown, to indicate the performance differences of the proposed method in the level of automation and the accuracy of results.

Multi scale shape index for 3D object recognition

We present Multi Scale Shape Index (MSSI), a novel feature for 3D object recognition. Inspired by the scale space filtering theory and Shape Index measure proposed by Koenderink & Van Doorn [6], this feature associates different forms of shape, such as umbilics, saddle regions, parabolic regions to a real valued index. This association is useful for representing an object based on its constituent shape forms. We derive closed form scale space equations which computes a characteristic scale at each 3D point in a point cloud without an explicit mesh structure. This characteristic scale is then used to estimate the Shape Index. We quantitatively evaluate the robustness and repeatability of the MSSI feature for varying object scales and changing point cloud density. We also quantify the performance of MSSI for object category recognition on a publicly available dataset. © 2013 Springer-Verlag.

快速成型技术中分层算法的研究与进展

根据对零件制造精度和效率的关注程度的不同,开发出了多种分层算法。在同等加工时间的情况下,根据加工精度的不同,将这些分层算法分为等层厚分层算法和适应性分层算法两类。通过对STL模型、原始CAD模型和点云数据的分析,讨论了两类分层算法的研究和发展,然后介绍了斜边分层算法和曲面分层算法等先进分层算法的原理和成果,最后讨论了快速成型分层算法的研究方向和趋势。

基于点集曲面投影算法的自由曲面匹配

测量数据的精确定位是实现复杂曲面加工检测的关键,针对测量点云数据与NURBS表示的CAD自由曲面模型匹配中求最近点计算方面存在的问题,提出了一种简单、有效的寻找最近点的方法。该方法与由测量点集评估给定曲面上的最近点的传统算法相反,采用点集曲面(point set surface,PSS)投影算法,对给定自由曲面模型上有限个点与不附加任何几何和拓扑信息的散乱点集之间进行粗匹配获得初始位置,进而以最近点迭代算法(ICP)完成测量数据定位的精确调整,达到全局及局部最优的目标。实验结果表明,采用PSS投影算法法寻找最近点不仅效率高,而且能得到全局匹配结果,可以为精匹配提供较好的计算初值,减少了ICP算法进行二次匹配时,迭代次数及执行时间并且精度得到了较大提高。

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.

Front tracking with moving-least-squares surfaces

The representation of interfaces by means of the algebraic moving-least-squares (AMLS) technique is addressed. This technique, in which the interface is represented by an unconnected set of points, is interesting for evolving fluid interfaces since there is]to surface connectivity. The position of the surface points can thus be updated without concerns about the quality of any surface triangulation. We introduce a novel AMLS technique especially designed for evolving-interfaces applications that we denote RAMLS (for Robust AMLS). The main advantages with respect to previous AMLS techniques are: increased robustness, computational efficiency, and being free of user-tuned parameters. Further, we propose a new front-tracking method based on the Lagrangian advection of the unconnected point set that defines the RAMLS surface. We assume that a background Eulerian grid is defined with some grid spacing h. The advection of the point set makes the surface evolve in time. The point cloud can be regenerated at any time (in particular, we regenerate it each time step) by intersecting the gridlines with the evolved surface, which guarantees that the density of points on the surface is always well balanced. The intersection algorithm is essentially a ray-tracing algorithm, well-studied in computer graphics, in which a line (ray) is traced so as to detect all intersections with a surface. Also, the tracing of each gridline is independent and can thus be performed in parallel. Several tests are reported assessing first the accuracy of the proposed RAMLS technique, and then of the front-tracking method based on it. Comparison with previous Eulerian, Lagrangian and hybrid techniques encourage further development of the proposed method for fluid mechanics applications. (C) 2008 Elsevier Inc. All rights reserved.