Piloto automático: Sistema de navegação autónoma

Desde o início do crescente interesse na área de robótica que a navegação autónoma se apresenta como um problema de complexa resolução que, por isso, desperta vasto interesse no meio científico. Além disso, as capacidades da navegação autónoma aliadas à robótica permitem o desenvolvimento de variadas aplicações. O objectivo da navegação autónoma é conferir, a um dispositivo motor, capacidade de decisão relativa à locomoção. Para o efeito, utilizam-se sensores, como os sensores IMU, o receptor GPS e os encoders, para fornecer os dados essenciais à navegação. A dificuldade encontra-se no correcto processamento destes sinais uma vez que são susceptíveis a fontes de ruído. Este trabalho apresenta um sistema de navegação autónomo aplicado ao controlo de um robot. Para tal, desenvolveu-se uma aplicação que alberga todo o sistema de localização, navegação e controlo, acrescido de uma interface gráfica, que permite a visualização em mapa da movimentação autónoma do robot. Recorre-se ao Filtro de Kalman como método probabilístico de estimação de posição, em que os sinais dos vários sensores são conjugados e filtrados. Foram realizados vários testes de modo a avaliar a capacidade do robot atingir os pontos traçados e a sua autonomia no seguimento da trajectória pretendida.

Tecniche GPS/INS per l'anilisi dinamica di un ciclomotore

Nel seguente elaborato si espone l’utilizzo del sistema GPS/INS per la valutazione del moto di un ciclomotore. Tale sistema è composto da sensori GPS ( Global Navigation System ) per la misurazione della posizione, e da sensori INS ( Inertial Navigation System) per la misurazione dell’accelerazione e delle velocità angolari rispetto a tre assi coordinati. Chiaramente le misure di accelerazioni e di velocità angolari da parte dei sensori, presentano dei minimi errori, che però si ripercuotono sul posizionamento finale. Per limitare questo fenomeno e rendere la misura di velocità e posizione utilizzabile, un filtro di Kalman viene impiegato per correggere il risultato dell'integrazione usando le misurazioni del GPS. Il connubio tra il sistema INS e il sistema GPS è molto efficacie anche quando si ha una assenza di ricezione satellitare o perdita parziale dei satelliti (cycle slip). Infine è stato utilizzato uno smartphone sfruttando i sensori in esso presenti : accelerometri, giroscopi, GPS, per analizzare la dinamica di un ciclomotore, concentrandosi sull’assetto in particolar modo l’angolo di rollio. Tale prova è stata affrontata non tanto per validare il sistema GPS/INS, ma per provare una soluzione comoda e di basso costo per analizzare il moto di un ciclomotore.

Multi-robot control in highly dynamic, competitive environments

The control and coordination of multiple mobile robots is a challenging task; particularly in environments with multiple, rapidly moving obstacles and agents. This paper describes a robust approach to multi-robot control, where robustness is gained from competency at every layer of robot control. The layers are: (i) a central coordination system (MAPS), (ii) an action system (AES), (iii) a navigation module, and (iv) a low level dynamic motion control system. The multi-robot coordination system assigns each robot a role and a sub-goal. Each robot’s action execution system then assumes the assigned role and attempts to achieve the specified sub-goal. The robot’s navigation system directs the robot to specific goal locations while ensuring that the robot avoids any obstacles. The motion system maps the heading and speed information from the navigation system to force-constrained motion. This multi-robot system has been extensively tested and applied in the robot soccer domain using both centralized and distributed coordination.

Visualisation and browsing of image databases

In this chapter we provide a comprehensive overview of the emerging field of visualising and browsing image databases. We start with a brief introduction to content-based image retrieval and the traditional query-by-example search paradigm that many retrieval systems employ. We specify the problems associated with this type of interface, such as users not being able to formulate a query due to not having a target image or concept in mind. The idea of browsing systems is then introduced as a means to combat these issues, harnessing the cognitive power of the human mind in order to speed up image retrieval.We detail common methods in which the often high-dimensional feature data extracted from images can be used to visualise image databases in an intuitive way. Systems using dimensionality reduction techniques, such as multi-dimensional scaling, are reviewed along with those that cluster images using either divisive or agglomerative techniques as well as graph-based visualisations. While visualisation of an image collection is useful for providing an overview of the contained images, it forms only part of an image database navigation system. We therefore also present various methods provided by these systems to allow for interactive browsing of these datasets. A further area we explore are user studies of systems and visualisations where we look at the different evaluations undertaken in order to test usability and compare systems, and highlight the key findings from these studies. We conclude the chapter with several recommendations for future work in this area. © 2011 Springer-Verlag Berlin Heidelberg.

Algoritmo eficiente para aquisição de sinais de GPS por software

O NAVSTAR/GPS (NAVigation System with Timing And Ranging/Global Po- sitioning System), mais conhecido por GPS, _e um sistema de navegacão baseado em sat_elites desenvolvido pelo departamento de defesa norte-americano em meados de 1970. Criado inicialmente para fins militares, o GPS foi adaptado para o uso civil. Para fazer a localização, o receptor precisa fazer a aquisição de sinais dos satélites visíveis. Essa etapa é de extrema importância, pois é responsável pela detecção dos satélites visíveis, calculando suas respectivas frequências e fases iniciais. Esse processo pode demandar bastante tempo de processamento e precisa ser implementado de forma eficiente. Várias técnicas são utilizadas atualmente, mas a maioria delas colocam em conflito questões de projeto tais como, complexidade computacional, tempo de aquisição e recursos computacionais. Objetivando equilibrar essas questões, foi desenvolvido um método que reduz a complexidade do processo de aquisição utilizando algumas estratégias, a saber, redução do efeito doppler, amostras e tamanho do sinal utilizados, além do paralelismo. Essa estratégia é dividida em dois passos, um grosseiro em todo o espaço de busca e um fino apenas na região identificada previamente pela primeira etapa. Devido a busca grosseira, o limiar do algoritmo convencional não era mais aceitável. Nesse sentido, um novo limiar foi estabelecido baseado na variância dos picos de correlação. Inicialmente, é feita uma busca com pouca precisão comparando a variância dos cinco maiores picos de correlação encontrados. Caso a variância ultrapasse um certo limiar, a região de maior pico torna-se candidata à detecção. Por fim, essa região passa por um refinamento para se ter a certeza de detecção. Os resultados mostram que houve uma redução significativa na complexidade e no tempo de execução, sem que tenha sido necessário utilizar algoritmos muito complexos.

Seabed photographs taken along OFOS profiles during POLARSTERN cruise PS96 (ANT-XXXI/2 FROSN)

Within the context of the overall ecological working programme Dynamics of Antarctic Marine Shelf Ecosystems (DynAMo) of the PS96 (ANT-XXXI/2) cruise of RV "Polarstern" to the Weddell Sea (Dec 2015 to Feb 2016), seabed imaging surveys were carried out along drift profiles by means of the Ocean Floor Observation System (OFOS) of the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI) Bremerhaven. The setup and mode of deployment of the OFOS was similar to that described by Bergmann and Klages (2012, doi:10.1016/j.marpolbul.2012.09.018). OFOS is a surface-powered gear equipped with two downward-looking cameras installed side-by-side: one high-resolution, wide-angle still camera (CANON® EOS 5D Mark III; lens: Canon EF 24 f/1.4L II, f stop: 13, exposure time: 1/125 sec; in-air view angles: 74° (horizontal), 53° (vertical), 84° (diagonal); image size: 5760 x 3840 px = 21 MPix; front of pressure resistant camera housing consisting of plexiglass dome port) and one high-definition color video camera (SONY® FCB-H11). The system was vertically lowered over the stern of the ship with a broadband fibre-optic cable, until it hovers approximately 1.5 m above the seabed. It was then towed after the slowly sailing ship at a speed of approximately 0.5 kn (0.25 m/s). The ship's Global Acoustic Positioning System (GAPS), combining Ultra Short Base Line (USBL), Inertial Navigation System (INS) and satellite-based Global Positioning System (GPS) technologies, was used to gain highly precise underwater position data of the OFOS. During the profile, OFOS was kept hanging at the preferred height above the seafloor by means of the live video feed and occasional minor cable-length adjustments with the winch to compensate small-scale bathymetric variations in seabed morphology. Information on water depth and height above the seafloor were continuously recorded by means of OFOS-mounted sensors (GAPS transponder, Tritech altimeter). Three lasers, which are placed beside the still camera, emit parallel beams and project red light points, arranged as an equilateral triangle with a side length of 50 cm, in each photo, thus providing a scale that can be used to calculate the seabed area depicted in each image and/or measure the size of organisms or seabed features visible in the image. In addition, the seabed area depicted was estimated using altimeter-derived height above seafloor and optical characteristics of the OFOS still camera. In automatic mode, a seabed photo, depicting an area of approximately 3.45 m**2 (= 2.3 m x 1.5 m; with variations depending on the actual height above ground), was taken every 30 seconds to obtain series of "TIMER" stills distributed at regular distances along the profiles that vary in length depending on duration of the cast. At a ship speed of 0.5 kn, the average distance between seabed images was approximately 5 m. Additional "HOTKEY" photos were taken from interesting objects (organisms, seabed features, such as putative iceberg scours) when they appeared in the live video feed (which was also recorded, in addition to the stills, for documentation and possible later analysis). If any image from this collection is used, please cite the reference as given above.

On precise three-dimensional environment modeling via UAV-based photogrammetric systems

Abstract : Images acquired from unmanned aerial vehicles (UAVs) can provide data with unprecedented spatial and temporal resolution for three-dimensional (3D) modeling. Solutions developed for this purpose are mainly operating based on photogrammetry concepts, namely UAV-Photogrammetry Systems (UAV-PS). Such systems are used in applications where both geospatial and visual information of the environment is required. These applications include, but are not limited to, natural resource management such as precision agriculture, military and police-related services such as traffic-law enforcement, precision engineering such as infrastructure inspection, and health services such as epidemic emergency management. UAV-photogrammetry systems can be differentiated based on their spatial characteristics in terms of accuracy and resolution. That is some applications, such as precision engineering, require high-resolution and high-accuracy information of the environment (e.g. 3D modeling with less than one centimeter accuracy and resolution). In other applications, lower levels of accuracy might be sufficient, (e.g. wildlife management needing few decimeters of resolution). However, even in those applications, the specific characteristics of UAV-PSs should be well considered in the steps of both system development and application in order to yield satisfying results. In this regard, this thesis presents a comprehensive review of the applications of unmanned aerial imagery, where the objective was to determine the challenges that remote-sensing applications of UAV systems currently face. This review also allowed recognizing the specific characteristics and requirements of UAV-PSs, which are mostly ignored or not thoroughly assessed in recent studies. Accordingly, the focus of the first part of this thesis is on exploring the methodological and experimental aspects of implementing a UAV-PS. The developed system was extensively evaluated for precise modeling of an open-pit gravel mine and performing volumetric-change measurements. This application was selected for two main reasons. Firstly, this case study provided a challenging environment for 3D modeling, in terms of scale changes, terrain relief variations as well as structure and texture diversities. Secondly, open-pit-mine monitoring demands high levels of accuracy, which justifies our efforts to improve the developed UAV-PS to its maximum capacities. The hardware of the system consisted of an electric-powered helicopter, a high-resolution digital camera, and an inertial navigation system. The software of the system included the in-house programs specifically designed for camera calibration, platform calibration, system integration, onboard data acquisition, flight planning and ground control point (GCP) detection. The detailed features of the system are discussed in the thesis, and solutions are proposed in order to enhance the system and its photogrammetric outputs. The accuracy of the results was evaluated under various mapping conditions, including direct georeferencing and indirect georeferencing with different numbers, distributions and types of ground control points. Additionally, the effects of imaging configuration and network stability on modeling accuracy were assessed. The second part of this thesis concentrates on improving the techniques of sparse and dense reconstruction. The proposed solutions are alternatives to traditional aerial photogrammetry techniques, properly adapted to specific characteristics of unmanned, low-altitude imagery. Firstly, a method was developed for robust sparse matching and epipolar-geometry estimation. The main achievement of this method was its capacity to handle a very high percentage of outliers (errors among corresponding points) with remarkable computational efficiency (compared to the state-of-the-art techniques). Secondly, a block bundle adjustment (BBA) strategy was proposed based on the integration of intrinsic camera calibration parameters as pseudo-observations to Gauss-Helmert model. The principal advantage of this strategy was controlling the adverse effect of unstable imaging networks and noisy image observations on the accuracy of self-calibration. The sparse implementation of this strategy was also performed, which allowed its application to data sets containing a lot of tie points. Finally, the concepts of intrinsic curves were revisited for dense stereo matching. The proposed technique could achieve a high level of accuracy and efficiency by searching only through a small fraction of the whole disparity search space as well as internally handling occlusions and matching ambiguities. These photogrammetric solutions were extensively tested using synthetic data, close-range images and the images acquired from the gravel-pit mine. Achieving absolute 3D mapping accuracy of 11±7 mm illustrated the success of this system for high-precision modeling of the environment.

Towards Proactive Context-aware Computing and Systems

A primary goal of context-aware systems is delivering the right information at the right place and right time to users in order to enable them to make effective decisions and improve their quality of life. There are three key requirements for achieving this goal: determining what information is relevant, personalizing it based on the users’ context (location, preferences, behavioral history etc.), and delivering it to them in a timely manner without an explicit request from them. These requirements create a paradigm that we term as “Proactive Context-aware Computing”. Most of the existing context-aware systems fulfill only a subset of these requirements. Many of these systems focus only on personalization of the requested information based on users’ current context. Moreover, they are often designed for specific domains. In addition, most of the existing systems are reactive - the users request for some information and the system delivers it to them. These systems are not proactive i.e. they cannot anticipate users’ intent and behavior and act proactively without an explicit request from them. In order to overcome these limitations, we need to conduct a deeper analysis and enhance our understanding of context-aware systems that are generic, universal, proactive and applicable to a wide variety of domains. To support this dissertation, we explore several directions. Clearly the most significant sources of information about users today are smartphones. A large amount of users’ context can be acquired through them and they can be used as an effective means to deliver information to users. In addition, social media such as Facebook, Flickr and Foursquare provide a rich and powerful platform to mine users’ interests, preferences and behavioral history. We employ the ubiquity of smartphones and the wealth of information available from social media to address the challenge of building proactive context-aware systems. We have implemented and evaluated a few approaches, including some as part of the Rover framework, to achieve the paradigm of Proactive Context-aware Computing. Rover is a context-aware research platform which has been evolving for the last 6 years. Since location is one of the most important context for users, we have developed ‘Locus’, an indoor localization, tracking and navigation system for multi-story buildings. Other important dimensions of users’ context include the activities that they are engaged in. To this end, we have developed ‘SenseMe’, a system that leverages the smartphone and its multiple sensors in order to perform multidimensional context and activity recognition for users. As part of the ‘SenseMe’ project, we also conducted an exploratory study of privacy, trust, risks and other concerns of users with smart phone based personal sensing systems and applications. To determine what information would be relevant to users’ situations, we have developed ‘TellMe’ - a system that employs a new, flexible and scalable approach based on Natural Language Processing techniques to perform bootstrapped discovery and ranking of relevant information in context-aware systems. In order to personalize the relevant information, we have also developed an algorithm and system for mining a broad range of users’ preferences from their social network profiles and activities. For recommending new information to the users based on their past behavior and context history (such as visited locations, activities and time), we have developed a recommender system and approach for performing multi-dimensional collaborative recommendations using tensor factorization. For timely delivery of personalized and relevant information, it is essential to anticipate and predict users’ behavior. To this end, we have developed a unified infrastructure, within the Rover framework, and implemented several novel approaches and algorithms that employ various contextual features and state of the art machine learning techniques for building diverse behavioral models of users. Examples of generated models include classifying users’ semantic places and mobility states, predicting their availability for accepting calls on smartphones and inferring their device charging behavior. Finally, to enable proactivity in context-aware systems, we have also developed a planning framework based on HTN planning. Together, these works provide a major push in the direction of proactive context-aware computing.

Sistema de realidade aumentada no procedimento cirúrgico de remoção de pedras nos rins

A inovação tecnológica e as facilidades que gera tem tido um impacto crescente em diversas área, inclusivamente na medicina. A rápida evolução por parte de algumas tecnologias, como é o caso da Realidade Aumentada (RA), criam excelentes oportunidades, nomeadamente para intervenções cirúrgicas laparoscópicas, que apresentam especialmente problemas ao nível da exposição do doente a radiação. O presente documento detalha todo o processo de investigação e desenvolvimento realizado com a pretensão de criar um sistema de navegação por RA que auxilie o procedimento cirúrgico laparoscópico de remoção de pedras nos rins. Com este objetivo em perspetiva, e numa parceria com a empresa ECmedica LTD, foram desenvolvidos quatro protótipo funcionais. Com o intuito de compreender as melhores práticas de sistemas de input, interface e sistema de registo a aplicar, estes integraram aspetos inovadores tais como a utilização de uma sonda ultra-som, como substituta do raioX, e um registo feito através de sensores magnéticos. Apoiados numa metodologia de design centrado no utilizador e em instrumentos de análise como entrevistas e observação natural, os protótipos foram testados, obtendo respostas esclarecedoras relativamente ao objetivos dos protótipos. Foi observado que a RA é vista pelos médicos como uma solução com potencial, com as soluções apresentadas ao nível de inputs, interface e registo a serem bem recebidas. A projeção bidimensional oferecida pela imagem ultra-som foi encarada como insuficientes, sendo sugerida a sua substituição por um aumento tridimensional capaz de facilitar a correta inserção da agulha.

Aportaciones de la cirugía guiada por ordenador y navegación en oncología de cabeza y cuello: una revisión bibliográfica sistemática y actualización

Introducción: El objetivo de este trabajo es hacer una revisión y actualización de la literatura sobre la aportación de la planificación quirúrgica y de la navegación en el manejo de la enfermedad oncológica de cabeza y cuello, para valorar y determinar sus aplicaciones actuales. Material y métodos: Se realiza una búsqueda electrónica empleando los términos craniomaxillofacial tumors, head and neck cancer, navigation system, computer-assisted surgery y oral cancer. Resultados: El número de artículos encontrados en la revisión de la literatura ha sido de 16, publicados entre los años 1991 y 2014. Entre ellos no hay ninguna revisión sistemática, hay 5 artículos de revisión, 6 series de casos y 5 casos clínicos. Solo 10 artículos aportan información completa en relación con la enfermedad oncológica manejada con tecnología de navegación quirúrgica. Actualmente las aplicaciones de la navegación en oncología de cabeza y cuello pueden enumerarse en las siguientes áreas: biopsia guiada, resección y reconstrucción de tumores, monitorización del volumen del tumor, control de márgenes de resección quirúrgica basados en TC, RMN o PET y sistema de comunicación interdisciplinar. Conclusiones: Actualmente hay un número escaso de publicaciones sobre las aplicaciones de la navegación quirúrgica en el novedoso ámbito de la oncología de cabeza y cuello. A pesar de la ausencia de revisiones sistemáticas, parece tener un futuro prometedor por la valiosa aportación que hace para el manejo de tumores de cabeza y cuello, como proporcionar precisión anatómica, precisión diagnóstica y seguridad quirúrgica, siendo de gran utilidad en el tratamiento oncológico multidisciplinar.

Persistent navigation and mapping using a biologically inspired SLAM system

The challenge of persistent navigation and mapping is to develop an autonomous robot system that can simultaneously localize, map and navigate over the lifetime of the robot with little or no human intervention. Most solutions to the simultaneous localization and mapping (SLAM) problem aim to produce highly accurate maps of areas that are assumed to be static. In contrast, solutions for persistent navigation and mapping must produce reliable goal-directed navigation outcomes in an environment that is assumed to be in constant flux. We investigate the persistent navigation and mapping problem in the context of an autonomous robot that performs mock deliveries in a working office environment over a two-week period. The solution was based on the biologically inspired visual SLAM system, RatSLAM. RatSLAM performed SLAM continuously while interacting with global and local navigation systems, and a task selection module that selected between exploration, delivery, and recharging modes. The robot performed 1,143 delivery tasks to 11 different locations with only one delivery failure (from which it recovered), traveled a total distance of more than 40 km over 37 hours of active operation, and recharged autonomously a total of 23 times.

Low-Cost vision-based AUV guidance system for reef navigation

Ensuring the long term viability of reef environments requires essential monitoring of many aspects of these ecosystems. However, the sheer size of these unstructured environments (for example Australia’s Great Barrier Reef pose a number of challenges for current monitoring platforms which are typically remote operated and required significant resources and infrastructure. Therefore, a primary objective of the CSIRO robotic reef monitoring project is to develop and deploy a large number of AUV teams to perform broadscale reef surveying. In order to achieve this, the platforms must be cheap, even possibly disposable. This paper presents the results of a preliminary investigation into the performance of a low-cost sensor suite and associated processing techniques for vision and inertial-based navigation within a highly unstructured reef environment.

Pipeline Architecture and Parallel Computation-Based Real-Time Stereovision Tracking System for Surgical Navigation

This paper studies the development of a real-time stereovision system to track multiple infrared markers attached to a surgical instrument. Multiple stages of pipeline in field-programmable gate array (FPGA) are developed to recognize the targets in both left and right image planes and to give each target a unique label. The pipeline architecture includes a smoothing filter, an adaptive threshold module, a connected component labeling operation, and a centroid extraction process. A parallel distortion correction method is proposed and implemented in a dual-core DSP. A suitable kinematic model is established for the moving targets, and a novel set of parallel and interactive computation mechanisms is proposed to position and track the targets, which are carried out by a cross-computation method in a dual-core DSP. The proposed tracking system can track the 3-D coordinate, velocity, and acceleration of four infrared markers with a delay of 9.18 ms. Furthermore, it is capable of tracking a maximum of 110 infrared markers without frame dropping at a frame rate of 60 f/s. The accuracy of the proposed system can reach the scale of 0.37 mm RMS along the x- and y-directions and 0.45 mm RMS along the depth direction (the depth is from 0.8 to 0.45 m). The performance of the proposed system can meet the requirements of applications such as surgical navigation, which needs high real time and accuracy capability.