Fluid Dynamics Without Fluids

This chapter will discuss some interesting real applications where Fluid Dynamics equations found fruitful appliances without dealing with "strictly speaking" fluids. In particular, thanks to the large set of analyses performed over different kinds of fluids in different operating and boundary conditions, a wide range of Computational Fluid Dynamics algorithms flourished tackling different aspects, from convergence rate, to stability according to the discretization, to multigrid and linearization problems. This robust and thorough background, both on the- oretical and on practical aspects, made Computational Fluid Dynamics (CFD) appealing also to other sciences and applications where Fluid Dynamics equations, or similar equations very close to them, can be useful in describing complex phenomena not related to fluids. Some applications that will be discussed concern, e.g., Geometry of liquid snowflakes whose con- tour is growing steered by curvature, staring from a circle. Furthermore Image Restoration and Segmentation can also benefit from CFD since a set of evolutionary algorithms, based on level-set curvature flow equations, plays a fundamental role in steering active contours or snakes through the noise present in the image till the complete warping of the desired framed object. Also in this case advanced techniques like Ghost Fluids Method for two competing fluids dynamics can be used to separate different objects in images. Other interesting appli- cations that will be described concern applicability of CFD to surface extraction from cloud of points. This is a common problem when complex clouds of points, representing 3D objects or scenes are obtained by laser scanners or multi-camera vision systems. These points represent unambiguous features from corners or sharp edges and the final 3D closed surface must fit on these points smoothly interpolating empty space between them. Also in this case CFD can provide useful tools to define the evolution of a 3D surface representing the border between two competing fluids, one representing the "inside" and the other the "outside" of the object itself. The two fluids evolution will stop when surface sticks on all the 3D points: the viscosity of the two fluids will control the smoothness of this surface that will wrap the cloud and tur- bulence is used to model injection into grooves or narrow holes. This chapter will also discuss another interesting application of CFD to robotic navigation in complex environments where we are looking for the best path, both in terms of length and distance from objects, through a set of obstacles, different terrains traversability or path slope. Also in this case an imaginary fluid with a predefined viscosity floods from the robot position through the whole environ- ment, its front evolution speed, accordingly to CFD, will be slower in narrow passages and, once it reaches the target, it will define the easiest way

A multi-resolution methodology for archeological survey: the Pompeii forum

The article reports about a multi-resolution approach developed for the 3D modeling of the entire Roman Forum in Pompei, Italy. The archaeological area, approximately 150 x 80 m, contains more than 350 finds spread all over the forum as well as larger mural structures of previous buildings and temples. The interdisciplinary 3D modeling work consists of a multi-scale image- and range based digital documentation method developed to fulfill all the surveying and archaeological needs and exploit all the potentialities of the actual 3D modeling techniques. Data’s resolution spans from few decimeters down to few millimeters. The employed surveying methodologies have pros and cons which will be addressed and discussed. Preliminary results of the integration of different 3D data in seamlessly textured 3D model, are presented

Extracción de información geométrica y semántica mediante el tratamiento de datos 2D/3D para labores de documentación y rehabilitación del patrimonio arquitectónico

Las tareas de documentación digital del patrimonio arquitectónico requieren del manejo de muy diferentes tipos de datos. Los sistemas actuales de captura de datos permiten obtener enormes volúmenes de datos. Sin embargo la extracción de información que resulte útilpara la documentación digital supone un importante reto de investigación. Esta tesis se centra en el estudio y diseño de sistemas y metodologías que permitan extraer información relevante a partir de datos 20 y 30 utilizando técnicas de procesamiento de nubes de puntos, extracción automática de líneas características, superposición de imágenes a modelos tridimensionales para la obtención de modelos con información multicapa y ortofotos, y empleo de técnicas de inteligencia artificial (aprendizaje profundo) para el análisis y clasificación de imágenes de patrimonio arquitectónico.Se presentan también casos de uso realizados como la proyección de policromías sobre edificios patrimoniales, y por último se muestran los resultados obtenidos considerados más representativosDepartamento de Ingeniería de Sistemas y AutomáticaDoctorado en Ingeniería Industria

Semantische dreidimensionale Karten für autonome mobile Roboter

Intelligentes autonomes Roboterhandeln in Alltagsumgebungen erfordert den Einsatz von 3D-Karten, in denen Objekte klassifiziert sind. 3D-Karten sind u.a. zur Steuerung notwendig, damit der Roboter komplexen Hindernissen ausweichen und sich mit 6 Freiheitsgraden (x-, y-, z-Position, Nick-, Gier-, und Rollwinkel) lokalisieren kann. Soll der Roboter mit seiner Umgebung interagieren, wird Interpretation unumgänglich. Über erkannte Objekte kann der Roboter Schlussfolgerungen ziehen, sein Wissen wird inspizier- und kommunizierbar. Aus diesen Gründen ist die automatische und schnelle semantische 3D-Modellierung der Umgebung eine wichtige Fragestellung in der Robotik. 3D-Laserscanner sind eine junge Technologie, die die Erfassung räumlicher Daten revolutioniert und Robotern das dreidimensionale Abtasten von Objekten möglich macht. Die vorliegende Arbeit untersucht und evaluiert mit Hilfe eines 3D-Laserscanners und des mobilen Roboters Kurt3D die zur automatischen semantischen 3D-Kartenerstellung notwendigen Algorithmen. Der erste Teil der Arbeit beschäftigt sich mit der Aufgabe, 3D-Scans in einem globalen Koordinatensystem zu registrieren. Korrekte, global konsistente Modelle entstehen durch einen 6D-SLAM Algorithmus. Hierbei werden 6 Freiheitsgrade in der Roboterpose berücksichtigt, geschlossene Kreise erkannt und der globale Fehler minimiert. Die Basis des 6D-SLAM ist ein sehr schneller ICP-Algorithmus. Im zweiten Teil geht es darum, die Punktmodelle mit Semantik zu versehen. Dazu werden 3D-Flächen in einer digitalisierten 3D-Szene detektiert und interpretiert. Anschließend sucht ein effizienter Algorithmus nach Objekten und bestimmt deren Pose, ebenfalls mit 6 Freiheitsgraden. Schließlich wird der in den zahlreichen Experimenten verwendete, mobile Roboter Kurt3D vorgestellt.Semantic three dimensional maps for autonomous mobile robots Intelligent autonomous acting in unstructured environments requires 3D maps with labelled 3D objects. 3D maps are necessary to avoid collisions with complex obstacles and to self localize in six degrees of freedom (x-, y-, z-position, roll, yaw and pitch angle). Meaning becomes inevitable, if the robot has to interact with its environment. The robot is then able to reason about the objects; its knowledge becomes inspectable and communicable. These arguments lead to requiring automatic and fast semantic environment modelling in robotics. A revolutionary method for gaging environments are 3D scanners, which enable robots to scan objects in a non-contact way in three dimensions. The presented work examines and evaluates the algorithms needed for automatic semantic 3D map building using a 3D laser range finder and the mobile robot Kurt3D. The first part deals with the task to register 3D scans in a common coordinate system. Correct, globally consistent models result from a 6D SLAM algorithm. Hereby 6 degrees of freedom of the robot pose are considered, closed-loops are detected and the global error is minimized. 6D SLAM is based on a very fast ICP algorithm. In the second part semantic descriptions are derived from the point model. For that purpose 3D planes are detected and interpreted in the digitalized 3D scene. After that an efficient algorithm detects objects and estimates their pose with 6 degrees of freedom, too. Finally, the mobile robot Kurt3D, that was used in numerous experiments is presented