Orientação semi-automática de uma sequência de pares de imagens frontais por fototriangulação a partir de fotocoordenadas extraídas pelo SIFT

Pós-graduação em Ciências Cartográficas - FCT

Caminhamento fotogramétrico com arranjo triangular de câmaras fotográficas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

The use of remote sensing imagery for monitoring recovery in the aftermath of a natural disaster: the Hurricane Katrina Case

Although Recovery is often defined as the less studied and documented phase of the Emergency Management Cycle, a wide literature is available for describing characteristics and sub-phases of this process. Previous works do not allow to gain an overall perspective because of a lack of systematic consistent monitoring of recovery utilizing advanced technologies such as remote sensing and GIS technologies. Taking into consideration the key role of Remote Sensing in Response and Damage Assessment, this thesis is aimed to verify the appropriateness of such advanced monitoring techniques to detect recovery advancements over time, with close attention to the main characteristics of the study event: Hurricane Katrina storm surge. Based on multi-source, multi-sensor and multi-temporal data, the post-Katrina recovery was analysed using both a qualitative and a quantitative approach. The first phase was dedicated to the investigation of the relation between urban types, damage and recovery state, referring to geographical and technological parameters. Damage and recovery scales were proposed to review critical observations on remarkable surge- induced effects on various typologies of structures, analyzed at a per-building level. This wide-ranging investigation allowed a new understanding of the distinctive features of the recovery process. A quantitative analysis was employed to develop methodological procedures suited to recognize and monitor distribution, timing and characteristics of recovery activities in the study area. Promising results, gained by applying supervised classification algorithms to detect localization and distribution of blue tarp, have proved that this methodology may help the analyst in the detection and monitoring of recovery activities in areas that have been affected by medium damage. The study found that Mahalanobis Distance was the classifier which provided the most accurate results, in localising blue roofs with 93.7% of blue roof classified correctly and a producer accuracy of 70%. It was seen to be the classifier least sensitive to spectral signature alteration. The application of the dissimilarity textural classification to satellite imagery has demonstrated the suitability of this technique for the detection of debris distribution and for the monitoring of demolition and reconstruction activities in the study area. Linking these geographically extensive techniques with expert per-building interpretation of advanced-technology ground surveys provides a multi-faceted view of the physical recovery process. Remote sensing and GIS technologies combined to advanced ground survey approach provides extremely valuable capability in Recovery activities monitoring and may constitute a technical basis to lead aid organization and local government in the Recovery management.

Tecniche numeriche di studio della sicurezza stradale: il caso della provincia di Bologna

La tesi dottorale in oggetto prende spunto da alcune considerazioni di base relative alla salute di una comunità. Infatti quest’ultima si fonda sulla sicurezza dell’ambiente in cui vive e sulla qualità delle relazioni tra i suoi componenti. In questo ambito la mobilità rappresenta uno degli elementi di maggior criticità, sia per la sicurezza delle persone, che per la salute pubblica, che per le conseguenze sull’ambiente che ne derivano. Negli ultimi anni la circolazione stradale è notevolmente aumentata è questo ha portato a notevoli aspetti negativi, uno dei quali è connesso agli incidenti stradali. In tale ambito viene ricordato che l’Unione Europea ha da tempo indicato come obiettivo prioritario il miglioramento della sicurezza stradale e nel 2001 ha fissato il traguardo di dimezzare entro il 2010 il numero delle vittime degli incidenti stradali. Non ultima, l’approvazione da parte del Parlamento europeo e del Consiglio di un atto legislativo (d’imminente pubblicazione sulla GU Europea) relativo alla gestione della sicurezza in tutte le fasi della pianificazione, della progettazione e del funzionamento delle infrastrutture stradali, in cui si evidenzia l’esigenza di una quantificazione della sicurezza stradale. In tale contesto viene sottolineato come uno dei maggiori problemi nella gestione della sicurezza stradale sia la mancanza di un metodo affidabile per stimare e quantificare il livello di sicurezza di una strada esistente o in progetto. Partendo da questa considerazione la tesi si sviluppa mettendo in evidenza le grandezza fondamentali nel problema della sicurezza stradale, (grado di esposizione, rischio d’incidente e le possibili conseguenze sui passeggeri) e analizzando i sistemi adottati tradizionalmente per effettuare analisi di sicurezza: • Statistiche dei dati storici d’incidente; • Previsione da modelli basati su analisi di regressione dei dati incidentali; • Studi Before-After; • Valutazione da giudizi di esperti. Dopo aver analizzato gli aspetti positivi e negativi delle alternative in parola, viene proposto un nuovo approccio, che combina gli elementi di ognuno dei metodi sopra citati in un algoritmo di previsione incidentale. Tale nuovo algoritmo, denominato Interactive Highway Safety Design Model (IHSDM) è stato sviluppato dalla Federal Highway Administration in collaborazione con la Turner Fairbank Higway Research Center ed è specifico per le strade extraurbane a due corsie. Il passo successivo nello sviluppo della tesi è quello di un’analisi dettagliata del modello IHSDM che fornisce il numero totale di incidenti previsti in un certo intervallo temporale. Viene analizzata la struttura del modello, i limiti d’applicabilità, le equazioni che ne sono alla base e i coefficienti moltiplicativi relativi ad ogni caratteristica geometrica e funzionale. Inoltre viene presentata un’ampia analisi di sensibilità che permette di definire quale sia l’influenza d’ogni singolo Fattore di Previsione incidentale (Accident Predication Factor) sul risultato finale. Dai temi trattati, emerge chiaramente come la sicurezza è legata a più sistemi tra loro interconnessi e che per utilizzare e migliorare i modelli previsionali è necessario avere a disposizione dati completi, congruenti, aggiornati e facilmente consultabili. Infatti, anche quando sono disponibili elementi su tutti gli incidenti avvenuti, spesso mancano informazioni di dettaglio ma fondamentali, riguardanti la strada come ad esempio il grado di curvatura, la larghezza della carreggiata o l’aderenza della pavimentazione. In tale ottica, nella tesi viene presentato il Sistema Informativo Stradale (SIS) della Provincia di Bologna, concepito come strumento di gestione delle problematiche inerenti la viabilità e come strumento di supporto per la pianificazione degli interventi e la programmazione delle risorse da investire sulla rete. Viene illustrato come il sistema sia in grado di acquisire, elaborare ed associare dati georeferenziati relativi al territorio sia sotto forma di rappresentazioni grafiche, sia mediante informazioni descrittive di tipo anagrafico ed alfanumerico. Quindi viene descritto il rilievo ad alto rendimento, effettuato con l’ausilio di un laboratorio mobile multifunzionale (Mobile Mapping System), grazie al quale è stato possibile definire con precisione il grafo completo delle strade provinciali e il database contenente i dati relativi al patrimonio infrastrutturale. Tali dati, relativi alle caratteristiche plano-altimetriche dell’asse (rettifili, curve planimetriche, livellette, raccordi altimetrici, ecc...), alla sezione trasversale (numero e larghezza corsie, presenza di banchine, ecc..), all’ambiente circostante e alle strutture annesse vengono presentati in forma completa specificando per ognuno la variabilità specifica. Inoltre viene evidenziato come il database si completi con i dati d’incidentali georeferenziati sul grafo e compresivi di tutte le informazioni contenute nel modello ISTAT CTT/INC spiegandone le possibili conseguenze sul campo dell’analisi di sicurezza. La tesi si conclude con l’applicazione del modello IHSDM ad un caso reale, nello specifico la SP255 di S.Matteo Decima. Infatti tale infrastruttura sarà oggetto di un miglioramento strutturale, finanziato dalla Regione Emilia Romagna, che consistente nell’allargamento della sede stradale attraverso la realizzazione di una banchina pavimentata di 1.00m su entrambi i lati della strada dalla prog. km 19+000 al km 21+200. Attraverso l’utilizzo dell’algoritmo di previsione incidentale è stato possibile quantificare gli effetti di questo miglioramento sul livello di sicurezza dell’infrastruttura e verificare l’attendibilità del modello con e senza storia incidentale pregressa. Questa applicazione ad un caso reale mette in evidenza come le informazioni del SIS possano essere sfruttate a pieno per la realizzazione di un analisi di sicurezza attraverso l’algoritmo di previsione incidentale IHSDM sia nella fase di analisi di uno specifico tronco stradale che in quella fondamentale di calibrazione del modello ad una specifica rete stradale (quella della Provincia di Bologna). Inoltre viene sottolineato come la fruibilità e la completezza dei dati a disposizione, possano costituire la base per sviluppi di ricerca futuri, come ad esempio l’indagine sulle correlazioni esistenti tra le variabili indipendenti che agiscono sulla sicurezza stradale.

Scene Reconstruction And Understanding By RGB-D Sensors

This thesis investigates interactive scene reconstruction and understanding using RGB-D data only. Indeed, we believe that depth cameras will still be in the near future a cheap and low-power 3D sensing alternative suitable for mobile devices too. Therefore, our contributions build on top of state-of-the-art approaches to achieve advances in three main challenging scenarios, namely mobile mapping, large scale surface reconstruction and semantic modeling. First, we will describe an effective approach dealing with Simultaneous Localization And Mapping (SLAM) on platforms with limited resources, such as a tablet device. Unlike previous methods, dense reconstruction is achieved by reprojection of RGB-D frames, while local consistency is maintained by deploying relative bundle adjustment principles. We will show quantitative results comparing our technique to the state-of-the-art as well as detailed reconstruction of various environments ranging from rooms to small apartments. Then, we will address large scale surface modeling from depth maps exploiting parallel GPU computing. We will develop a real-time camera tracking method based on the popular KinectFusion system and an online surface alignment technique capable of counteracting drift errors and closing small loops. We will show very high quality meshes outperforming existing methods on publicly available datasets as well as on data recorded with our RGB-D camera even in complete darkness. Finally, we will move to our Semantic Bundle Adjustment framework to effectively combine object detection and SLAM in a unified system. Though the mathematical framework we will describe does not restrict to a particular sensing technology, in the experimental section we will refer, again, only to RGB-D sensing. We will discuss successful implementations of our algorithm showing the benefit of a joint object detection, camera tracking and environment mapping.

Entwicklung und Anwendung von mobilen Messstrategien und Analysemethoden zur Untersuchung urbanen Aerosols

Seit Anbeginn der Menschheitsgeschichte beeinflussen die Menschen ihre Umwelt. Durch anthropogene Emissionen ändert sich die Zusammensetzung der Atmosphäre, was einen zunehmenden Einfluss unter anderem auf die Atmosphärenchemie, die Gesundheit von Mensch, Flora und Fauna und das Klima hat. Die steigende Anzahl riesiger, wachsender Metropolen geht einher mit einer räumlichen Konzentration der Emission von Luftschadstoffen, was vor allem einen Einfluss auf die Luftqualität der windabwärts gelegenen ruralen Regionen hat. In dieser Doktorarbeit wurde im Rahmen des MEGAPOLI-Projektes die Abluftfahne der Megastadt Paris unter Anwendung des mobilen Aerosolforschungslabors MoLa untersucht. Dieses ist mit modernen, zeitlich hochauflösenden Instrumenten zur Messung der chemischen Zusammensetzung und Größenverteilung der Aerosolpartikel sowie einiger Spurengase ausgestattet. Es wurden mobile Messstrategien entwickelt und angewendet, die besonders geeignet zur Charakterisierung urbaner Emissionen sind. Querschnittsmessfahrten durch die Abluftfahne und atmosphärische Hintergrundluftmassen erlaubten sowohl die Bestimmung der Struktur und Homogenität der Abluftfahne als auch die Berechnung des Beitrags der urbanen Emissionen zur Gesamtbelastung der Atmosphäre. Quasi-Lagrange’sche Radialmessfahrten dienten der Erkundung der räumlichen Erstreckung der Abluftfahne sowie auftretender Transformationsprozesse der advehierten Luftschadstoffe. In Kombination mit Modellierungen konnte die Struktur der Abluftfahne vertieft untersucht werden. Flexible stationäre Messungen ergänzten den Datensatz und ließen zudem Vergleichsmessungen mit anderen Messstationen zu. Die Daten einer ortsfesten Messstation wurden zusätzlich verwendet, um die Alterung des organischen Partikelanteils zu beschreiben. Die Analyse der mobilen Messdaten erforderte die Entwicklung einer neuen Methode zur Bereinigung des Datensatzes von lokalen Störeinflüssen. Des Weiteren wurden die Möglichkeiten, Grenzen und Fehler bei der Anwendung komplexer Analyseprogramme zur Berechnung des O/C-Verhältnisses der Partikel sowie der Klassifizierung der Aerosolorganik untersucht. Eine Validierung verschiedener Methoden zur Bestimmung der Luftmassenherkunft war für die Auswertung ebenfalls notwendig. Die detaillierte Untersuchung der Abluftfahne von Paris ergab, dass diese sich anhand der Erhöhung der Konzentrationen von Indikatoren für unprozessierte Luftverschmutzung im Vergleich zu Hintergrundwerten identifizieren lässt. Ihre eher homogene Struktur kann zumeist durch eine Gauß-Form im Querschnitt mit einem exponentiellen Abfall der unprozessierten Schadstoffkonzentrationen mit zunehmender Distanz zur Stadt beschrieben werden. Hierfür ist hauptsächlich die turbulente Vermischung mit Umgebungsluftmassen verantwortlich. Es konnte nachgewiesen werden, dass in der advehierten Abluftfahne eine deutliche Oxidation der Aerosolorganik im Sommer stattfindet; im Winter hingegen ließ sich dieser Prozess während der durchgeführten Messungen nicht beobachten. In beiden Jahreszeiten setzt sich die Abluftfahne hauptsächlich aus Ruß und organischen Partikelkomponenten im PM1-Größenbereich zusammen, wobei die Quellen Verkehr und Kochen sowie zusätzlich Heizen in der kalten Jahreszeit dominieren. Die PM1-Partikelmasse erhöhte sich durch die urbanen Emissionen im Vergleich zum Hintergrundwert im Sommer in der Abluftfahne im Mittel um 30% und im Winter um 10%. Besonders starke Erhöhungen ließen sich für Polyaromaten beobachten, wo im Sommer eine mittlere Zunahme von 194% und im Winter von 131% vorlag. Jahreszeitliche Unterschiede waren ebenso in der Größenverteilung der Partikel der Abluftfahne zu finden, wo im Winter im Gegensatz zum Sommer keine zusätzlichen nukleierten kleinen Partikel, sondern nur durch Kondensation und Koagulation angewachsene Partikel zwischen etwa 10nm und 200nm auftraten. Die Spurengaskonzentrationen unterschieden sich ebenfalls, da chemische Reaktionen temperatur- und mitunter strahlungsabhängig sind. Weitere Anwendungsmöglichkeiten des MoLa wurden bei einer Überführungsfahrt von Deutschland an die spanische Atlantikküste demonstriert, woraus eine Kartierung der Luftqualität entlang der Fahrtroute resultierte. Es zeigte sich, dass hauptsächlich urbane Ballungszentren von unprozessierten Luftschadstoffen betroffen sind, advehierte gealterte Substanzen jedoch jede Region beeinflussen können. Die Untersuchung der Luftqualität an Standorten mit unterschiedlicher Exposition bezüglich anthropogener Quellen erweiterte diese Aussage um einen Einblick in die Variation der Luftqualität, abhängig unter anderem von der Wetterlage und der Nähe zu Emissionsquellen. Damit konnte gezeigt werden, dass sich die entwickelten Messstrategien und Analysemethoden nicht nur zur Untersuchung der Abluftfahne einer Großstadt, sondern auch auf verschiedene andere wissenschaftliche und umweltmesstechnische Fragestellungen anwenden lassen.

Estudio de visibilidad en carreteras usando modelos digitales de elevación de alta resolución

El estudio de la distancia de visibilidad disponible en carreteras es de gran importancia para la seguridad vial. Los Mobile Mapping Systems (MMS) permiten capturar los elementos de las carreteras existentes y su entorno con alta resolución y rendimiento, obteniendo nubes de puntos 3D (LIDAR) con precisión centimétrica y fotografías panorámicas. El tratamiento de la ingente cantidad de datos que estos equipos proporcionan se ha efectuado con herramientas específicas de tratamiento de datos LIDAR y de ESRI. El cálculo de la distancia de visibilidad disponible se ha realizado mediante una aplicación que funciona sobre ArcGIS. Todo ello permite estimar la distancia de visibilidad disponible con gran precisión, utilizando tanto modelos digitales del terreno como de superficie, de manera que es posible analizar la influencia que tienen la vegetación y otros elementos de las márgenes. Se describen las técnicas utilizadas y su aplicación práctica a una carretera de la Comunidad de Madrid.

Vídeo-Mapa: uma interface de geovisualização multimídia aplicada a transportes e meio ambiente.

A presente tese propõe uma metodologia de vídeo-mapeamento móvel georreferenciado a partir do desenvolvimento de protótipos que utilizam uma Interface de Geovisualização Multimídia para sincronizar o registro (em vídeo) de um local ou evento de interesse com a rota percorrida pelo veículo de inspeção (sobre mapa ou imagem), através da coleta de dados por sensores móveis: câmera digital, microfone, receptor GNSS e bússola digital. A interface permite a integração desses sensores com os atuais serviços de mapas digitais disponíveis na web. Sistemas como esse melhoram significativamente as análises temporais, a gestão e a tomada de decisão. A interface proposta e desenvolvida no presente trabalho é útil para muitas aplicações como ferramenta de monitoramento e inventário. Esta interface pode ser entendida como o componente visual de um sistema de mapeamento móvel ou como um sistema cartográfico alternativo ou complementar, para aplicações em que a precisão geométrica do receptor GNSS, na modalidade de navegação, é suficiente e sua acessibilidade, um fator competitivo. As aplicações desenvolvidas no presente trabalho foram duas: um sistema de monitoramento e inventário de placas de sinalização viária e um sistema de monitoramento de cheias/secas e inventário de propriedades na borda de reservatórios de hidroelétricas, ambos em pleno funcionamento.

Semantic mapping using mobile robots

Robotic mapping is the process of automatically constructing an environment representation using mobile robots. We address the problem of semantic mapping, which consists of using mobile robots to create maps that represent not only metric occupancy but also other properties of the environment. Specifically, we develop techniques to build maps that represent activity and navigability of the environment. Our approach to semantic mapping is to combine machine learning techniques with standard mapping algorithms. Supervised learning methods are used to automatically associate properties of space to the desired classification patterns. We present two methods, the first based on hidden Markov models and the second on support vector machines. Both approaches have been tested and experimentally validated in two problem domains: terrain mapping and activity-based mapping.

Environment mapping for mobile robots navigation using hierarchical neural network and omnivision

Autonomous robots must be able to learn and maintain models of their environments. In this context, the present work considers techniques for the classification and extraction of features from images in joined with artificial neural networks in order to use them in the system of mapping and localization of the mobile robot of Laboratory of Automation and Evolutive Computer (LACE). To do this, the robot uses a sensorial system composed for ultrasound sensors and a catadioptric vision system formed by a camera and a conical mirror. The mapping system is composed by three modules. Two of them will be presented in this paper: the classifier and the characterizer module. The first module uses a hierarchical neural network to do the classification; the second uses techiniques of extraction of attributes of images and recognition of invariant patterns extracted from the places images set. The neural network of the classifier module is structured in two layers, reason and intuition, and is trained to classify each place explored for the robot amongst four predefine classes. The final result of the exploration is the construction of a topological map of the explored environment. Results gotten through the simulation of the both modules of the mapping system will be presented in this paper. © 2008 IEEE.

Probabilistic mapping with mobile robots in structured environments

La mayor parte de los entornos diseñados por el hombre presentan características geométricas específicas. En ellos es frecuente encontrar formas poligonales, rectangulares, circulares . . . con una serie de relaciones típicas entre distintos elementos del entorno. Introducir este tipo de conocimiento en el proceso de construcción de mapas de un robot móvil puede mejorar notablemente la calidad y la precisión de los mapas resultantes. También puede hacerlos más útiles de cara a un razonamiento de más alto nivel. Cuando la construcción de mapas se formula en un marco probabilístico Bayesiano, una especificación completa del problema requiere considerar cierta información a priori sobre el tipo de entorno. El conocimiento previo puede aplicarse de varias maneras, en esta tesis se presentan dos marcos diferentes: uno basado en el uso de primitivas geométricas y otro que emplea un método de representación cercano al espacio de las medidas brutas. Un enfoque basado en características geométricas supone implícitamente imponer un cierto modelo a priori para el entorno. En este sentido, el desarrollo de una solución al problema SLAM mediante la optimización de un grafo de características geométricas constituye un primer paso hacia nuevos métodos de construcción de mapas en entornos estructurados. En el primero de los dos marcos propuestos, el sistema deduce la información a priori a aplicar en cada caso en base a una extensa colección de posibles modelos geométricos genéricos, siguiendo un método de Maximización de la Esperanza para hallar la estructura y el mapa más probables. La representación de la estructura del entorno se basa en un enfoque jerárquico, con diferentes niveles de abstracción para los distintos elementos geométricos que puedan describirlo. Se llevaron a cabo diversos experimentos para mostrar la versatilidad y el buen funcionamiento del método propuesto. En el segundo marco, el usuario puede definir diferentes modelos de estructura para el entorno mediante grupos de restricciones y energías locales entre puntos vecinos de un conjunto de datos del mismo. El grupo de restricciones que se aplica a cada grupo de puntos depende de la topología, que es inferida por el propio sistema. De este modo, se pueden incorporar nuevos modelos genéricos de estructura para el entorno con gran flexibilidad y facilidad. Se realizaron distintos experimentos para demostrar la flexibilidad y los buenos resultados del enfoque propuesto. Abstract Most human designed environments present specific geometrical characteristics. In them, it is easy to find polygonal, rectangular and circular shapes, with a series of typical relations between different elements of the environment. Introducing this kind of knowledge in the mapping process of mobile robots can notably improve the quality and accuracy of the resulting maps. It can also make them more suitable for higher level reasoning applications. When mapping is formulated in a Bayesian probabilistic framework, a complete specification of the problem requires considering a prior for the environment. The prior over the structure of the environment can be applied in several ways; this dissertation presents two different frameworks, one using a feature based approach and another one employing a dense representation close to the measurements space. A feature based approach implicitly imposes a prior for the environment. In this sense, feature based graph SLAM was a first step towards a new mapping solution for structured scenarios. In the first framework, the prior is inferred by the system from a wide collection of feature based priors, following an Expectation-Maximization approach to obtain the most probable structure and the most probable map. The representation of the structure of the environment is based on a hierarchical model with different levels of abstraction for the geometrical elements describing it. Various experiments were conducted to show the versatility and the good performance of the proposed method. In the second framework, different priors can be defined by the user as sets of local constraints and energies for consecutive points in a range scan from a given environment. The set of constraints applied to each group of points depends on the topology, which is inferred by the system. This way, flexible and generic priors can be incorporated very easily. Several tests were carried out to demonstrate the flexibility and the good results of the proposed approach.

LADAR based mapping and obstacle detection system for service robots

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia Electrotécnica e de Computadores

Towards a Mobile Three-dimensional Modelling System for Underground Structures

Robotica 2012: 12th International Conference on Autonomous Robot Systems and Competitions April 11, 2012, Guimarães, Portugal

Application of Visual-Inertial SLAM for 3D Mapping of Underground Environments

The underground scenarios are one of the most challenging environments for accurate and precise 3d mapping where hostile conditions like absence of Global Positioning Systems, extreme lighting variations and geometrically smooth surfaces may be expected. So far, the state-of-the-art methods in underground modelling remain restricted to environments in which pronounced geometric features are abundant. This limitation is a consequence of the scan matching algorithms used to solve the localization and registration problems. This paper contributes to the expansion of the modelling capabilities to structures characterized by uniform geometry and smooth surfaces, as is the case of road and train tunnels. To achieve that, we combine some state of the art techniques from mobile robotics, and propose a method for 6DOF platform positioning in such scenarios, that is latter used for the environment modelling. A visual monocular Simultaneous Localization and Mapping (MonoSLAM) approach based on the Extended Kalman Filter (EKF), complemented by the introduction of inertial measurements in the prediction step, allows our system to localize himself over long distances, using exclusively sensors carried on board a mobile platform. By feeding the Extended Kalman Filter with inertial data we were able to overcome the major problem related with MonoSLAM implementations, known as scale factor ambiguity. Despite extreme lighting variations, reliable visual features were extracted through the SIFT algorithm, and inserted directly in the EKF mechanism according to the Inverse Depth Parametrization. Through the 1-Point RANSAC (Random Sample Consensus) wrong frame-to-frame feature matches were rejected. The developed method was tested based on a dataset acquired inside a road tunnel and the navigation results compared with a ground truth obtained by post-processing a high grade Inertial Navigation System and L1/L2 RTK-GPS measurements acquired outside the tunnel. Results from the localization strategy are presented and analyzed.