Point cloud registration is a technique to align two sets of points with manifold applications across a range of industries. However, due to a lack of adequate sensing technology, this technique has seldom found applications in the automotive sector up to now. With the advent of solid-state Light Detection and Ranging (LiDAR) sensors that are easily integrable in series production vehicles as means to sense the surrounding environment, this technique can be functional to automate their operations. Maneuvering a vehicle in the proximity of a reference object is one such operation, which can only be performed by accurately estimating its position and orientation relative to the vehicle itself. This project deals with the design and the implementation of an algorithm to accurately locate an aircraft parked on an airfield apron in real time. This is achieved by registering the point cloud model of the plane to the measurement point cloud of the scene produced by the LiDAR sensors on board the vehicle. To this end, the Iterative Closest Point (ICP) algorithm is a well-established approach to register two sets of points without prior knowledge of the correspondences between pairs of points, which, however, is notoriously sensitive towards outliers and computationally expensive with large point clouds. In this work, different variants are presented that improve on the standard ICP algorithm, in terms of accuracy and runtime performance, by leveraging different data structures to index the reference model and outlier rejection strategies. The results show that the implemented algorithms can produce estimates of centimeter precision in milliseconds based only on partial observations of the aircraft, outperforming another established solution tested. / Punktmolnregistrering är en teknik för att anpassa två uppsättningar punkter med mångfaldiga applikationer inom en rad branscher. På grund av bristen på adekvat sensorsteknik har denna teknik hittills sällan används inom automotivesektorn. Med tillkomsten av solid-state LiDAR -sensorer som enkelt kan integreras i serieproduktionsfordon för att kunna känna av den omgivningen, kan denna teknik automatisera verksamheten. Att manövrera ett fordon i närheten av ett referensobjekt är en sådan operation, som bara kan utföras genom att exakt uppskatta dess position och orientering i förhållande till själva fordonet. Detta projekt handlar om design och implementering av en algoritm för att exakt lokalisera ett flygplan parkerat på ett flygfält i realtid. Detta uppnås genom att registrera planetens molnmodell till mätpunktsmolnet på scenen som produceras av LiDAR -sensorerna ombord på fordonet. För detta ändamålet är Iterative Closest Point (ICP) -algoritmen ett väletablerat tillvägagångssätt för att registrera två uppsättningar punkter utan föregående kännedom om överensstämmelserna mellan parpar, vilket dock är notoriskt känsligt för avvikelser och beräknat dyrt med stora punktmoln. I detta arbete presenteras olika varianter som förbättrar standard ICP - algoritmen, när det gäller noggrannhet och runtime performance, genom att utnyttja olika datastrukturer för att indexera referensmodellen och outlier -avvisningsstrategier. Resultaten visar att de implementerade algoritmerna kan producera uppskattningar av centimeters precision i millisekunder baserat endast på partiella observationer av flygplanet, vilket överträffar en annan etablerad lösning som testats.

This thesis concerns the analytical and practical aspects of applying the Closest Point Method to solve elliptic partial differential equations (PDEs) on smooth surfaces and domains with smooth boundaries. A new numerical scheme is proposed to solve surface elliptic PDEs and a novel geometric multigrid solver is constructed to solve the resulting linear system. The method is also applied to coupled bulk-surface problems. A new embedding equation in a narrow band surrounding the surface is formulated so that it agrees with the original surface PDE on the surface and has a unique solution which is constant along the normals to the surface. The embedding equation is then discretized using standard finite difference scheme and barycentric Lagrange interpolation. The resulting scheme has 2nd-order accuracy in practice and is provably 2nd-order convergent for curves without boundary embedded in ℝ². To apply the method to solve elliptic equations on surfaces and domains with boundaries, the "ghost" point approach is adopted to handle Dirichlet, Neumann and Robin boundary conditions. A systematic method is proposed to represent values of ghost points by values of interior points according to boundary conditions. A novel geometric multigrid method based on the closest point representation of the surface is constructed to solve the resulting large sparse linear systems. Multigrid solvers are designed for surfaces with or without boundaries and domains with smooth boundaries. Numerical results indicate that the convergence rate of the multigrid solver stays roughly the same as we refine the mesh, as is desired of a multigrid algorithm. Finally the above methods are combined to solve coupled bulk-surface PDEs with some applications to biology.

Now a days where technological advancements are growing at a rapid pace, it has become a common norm for all the manufacturing companies to be abreast with these advancements for being competitive in market. This thesis deals with development of one such common norm for one of the products (Roof rack component) for company Thule. The main aim of the thesis is to curtail the products lead time to market and this was achieved by using an artificial intelligence technique i.e., Case-based reasoning (CBR). Roof rack component which is mounted on car roof is mainly constituted by two parts foot pad and bracket, this thesis main interest was concerned with only brackets and its geometry. This thesis is based on contemplating the already implemented concepts in this context, designer requirements and exploring better solutions. The methods of implementation adopted here was using CBR concept which is based on indexing , retrieve, adapt, review, retain and employing these concepts in form of an algorithm. The concept for developing the algorithm was based on Iterative closest point (ICP) approach which emphasise on assigning lower weight to pairs with greater point to point distance. The results portrayed are with respect to geometry and also with respect to application interface developed, which both together provides us a better solution.

The Iterative Closest Point (ICP) algorithm is one of the most commonly used range image processing methods. However, slow operational speeds and high input band-widths limit the use of ICP in high-speed real-time applications. This thesis presents and examines a novel hardware implementation of a high-speed ICP object tracking system that uses stereo vision disparities as input. Although software ICP trackers already exist, this innovative hardware tracker utilizes the efficiencies of custom hardware processing, thus enabling faster high-speed real-time tracking. A custom hardware design has been implemented in an FPGA to handle the inherent bottlenecks that result from the large input and processing band-widths of the range data. The hardware ICP design consists of four stages: Pre-filter, Transform, Nearest Neighbor, and Transform Recovery. This custom hardware has been implemented and tested on various objects, using both software simulation and hardware tests. Results indicate that the tracker is able to successfully track free-form objects at over 200 frames-per-second along arbitrary paths. Tracking errors are low, in spite of substantial noisy stereo input. The tracker is able to track stationary paths within 0.42mm and 1.42degs, linear paths within 1.57mm and 2.80degs, and rotational paths within 0.39degs axis error. With further degraded data by occlusion, the tracker is able to handle 60% occlusion before a slow decline in performance. The high-speed hardware implementation (that uses 16 parallel nearest neighbor circuits), is more then five times faster than the software K-D tree implementation. This tracker has been designed as the hardware component of ‘FastTrack’, a high frame rate, stereo vision tracking system, that will provide a known object’s pose in real-time at 200 frames per second. This hardware ICP tracker is compact, lightweight, has low power requirements, and is integratable with the stereo sensor and stereo extraction components of the FastTrack’ system on a single FPGA platform. High-speed object tracking is useful for many innovative applications, including advanced spaced-based robotics. Because of this project’s success, the ‘FastTrack’ system will be able to aid in performing in-orbit, automated, remote satellite recovery for maintenance. / Thesis (Master, Electrical & Computer Engineering) -- Queen's University, 2008-07-15 22:50:30.369

During orthopaedic surgery, preoperative CT scans can be aligned to the patient to assist the guidance of surgical instruments and the placement of implants. Registration (i.e. alignment) can be accomplished in many ways: by registering implanted fiducial markers, by touching a probe to the bone surface, or by aligning intraoperative two dimensional flouro images with the the three dimensional CT data. These approaches have problems: They require exposure of the bone, subject the patient and surgeons to ionizing radiation, or do both. Ultrasound can also be used to register a preoperative CT scan to the patient. The ultrasound probe is tracked as it passes over the patient and the ultrasound images are aligned to the CT data. This method eliminates the problems of bone exposure and ionizing radiation, but is computationally more difficult because the ultrasound images contain incomplete and unclear bone surfaces. In this work, we compare three methods to register a set of ultrasound images to a CT scan: Iterated Closest Point, Mutual Information and a novel method Points-to-Image. The average Target Registration Error and speed of each method is presented along with a brief summary of their strengths and weaknesses. / Thesis (Master, Computing) -- Queen's University, 2009-01-22 04:21:22.569

Medical imaging has become the key to access inside human body for the purpose of diagnosis and treatment planning. In order to understand the effectiveness of planned treatment following the diagnosis, treated body part may have to be monitored several times during a period of time. Information gained from successive imaging of body part provides guidance to next step of treatment. Comparison of images or datasets taken at different times requires registration of these images or datasets since the same conditions may not be provided at all times. Accurate segmentation of the body part under treatment is needed while comparing medical images to achieve quantitative and qualitative measurements. This segmentation task enables two dimensional and three dimensional visualizations of the region which also aid in directing the planning strategy. In this thesis, several segmentation algorithms are investigated and a hybrid segmentation algorithm is developed in order to segment bone tissue out of head CT slices for orthodontic treatment planning. Using the developed segmentation algorithm, three dimensional visualizations of segmented bone tissue out of head CT slices of two patients are obtained. Visualizations are obtained using the MATLAB Computer software&amp / #8217 / s visualization library. Besides these, methods are developed for automatic registration of twodimensional and three-dimensional CT images taken at different time periods. These methods are applied to real and synthetic data. Algorithms and methods used in this thesis are also implemented in MATLAB computer program.

This work is focused on creating 3D maps of indoor enviroment using Microsoft Kinect sensor. The first part shows the description of Microsoft Kinect sensor, the methods for acquisition and processing of depth data and their registration using different algorithms. The second part shows application of algorithms for map registration and final 3D maps of indoor enviroment.

This dissertation explores the interaction of syntax and morphology in the morpholog- ical realization of AGREE-relations. I present two case studies of derivational interactions of AGREE-processes where the morphological realization of the later processes are affected by the earlier ones. The two cases studied differ in the way probes and goals interact. The first part of the dissertation explores restrictions on clitic combinations where two goals vie for the features of one probe. The second part discusses the reverse situation, where two probes are agreeing with the same goal. The first configuration arises in restrictions on clitic combinations where v can AGREE with an indirect object and a direct object one at a time (Anagnostopoulou 2003, 2005b, Béjar and Rezác 2003). These configurations give rise to a form of competition: the sec- ond argument will fail to AGREE in any features that it shares with the first. I show that this form of competition extends from restrictions involving local person arguments, where it has been used so far, to restrictions involving third person and plural, which have so far been treated as morphological. Whereas the restrictions on local person lead to ungrammaticality, those on third person and plural result in impoverished morphological realization. I argue that this difference indicates a different role of AGREE for local person vs. third person and plural. Recent work as shown that local person has special syntactic licensing needs (e.g. Béjar and Rezác 2003, Baker 2008, Preminger 2011b). Third person and plural on the other hand, I argue, are syntactically wellformed on their own, but require AGREE to be visible to lexical insertion at PF. Failure to AGREE will lead to absence of morphological realization or ungrammaticality as a function of the features involved. Once restrictions on third person arguments are treated as syntactic, much of the variation across languages in their morphological realization follows from differences in the PF-inventory. The second situation, two probes AGREEING with the same goal, arises in agreement with objects in Hindi-Urdu. The second part of the dissertation discusses two asymmetries in agreement of T with subjects and objects in conjunction structures. While T-agreement with objects shows sensitivity to linear order (i.a. closest conjunct agreement), T-agreement with subjects does not. I argue that the differences follow from the activity of the goal at the time of agreement. While subjects are syntactically active at the time T probes them, objects are not, because they have already been assigned case by v. As a consequence, the syntactic relation between T and an object cannot value the T's probe in the syntax. Non- syntactic effects like the relevance of linear order affect agreement exactly when valuation cannot be achieved in the syntax. Both case studies lead to the proposal that syntactically wellformed derivations can be ruled out at PF by failure of lexical insertion. This can happen in two ways. The discus- sion of restrictions on clitic combinations will lead to the conclusion that some languages allow the syntax to generate wellformed structures that contain nodes with so few features that PF cannot insert an exponent for them. The discussion of agreement in Hindi-Urdu will lead to the proposal that the grammar can generate feature bundles with inconsistent features that cannot be spelled out in one form. Overall, PF does both less and more than is often assumed. The restrictions on third person and plural discussed in the first part are traditionally considered to be the result of morphological operations that change the feature content of clitics (Bonet 1991, 1993, 1995, Grimshaw 1997, Noyer 1997). The proposal here reduces the role of PF in these restrictions to spelling out syntactic structures that have reduced feature content as the result of syntactic interactions. Similarly, the proposal about Hindi-Urdu tightly delimits the space where non-syntactic effects on agreement arise. At the same time, PF can rule out syntactically wellformed structures, which is not typically assumed to be possible.

A presente dissertação versa a teoria geral da determinação da lei aplicável no Direito Internacional Privado, sob a ótica de parâmetros cosmopolitas colhidos em outras ciências humanas, em perspectiva interdisciplinar. Analisam-se vários estudos recentes sobre o cosmopolitismo, bem como suas origens remotas, de modo a propor possíveis relações do tema com o método conflitual do Direito Internacional Privado. No capítulo I, empreende-se estudo histórico, retornando às origens do cosmopolitismo (filosofias grega e romana), passando pelo cosmopolitismo de Kant, no séc. XVIII, para então, finalmente, examinar os cosmopolitismos contemporâneos. Quanto a estes, procede-se à uma taxionomia e se exploram algumas proposições teóricas de especial utilidade para a determinação da lei aplicável. No capítulo II, busca-se transpor o cosmopolitismo do plano das demais ciências humanas para o plano da teoria jurídica em particular. Analisa-se, primeiro, o que implica a ideia de cosmopolitização do direito e, após, a relação entre o cosmopolitismo e o Direito Internacional Privado em específico. Dá-se especial atenção à aplicação da ideia de justiça cosmopolita no contexto da determinação da lei aplicável. No capítulo III, trata-se dos três grandes métodos de determinação da lei aplicável (multilateralismo, unilateralismo e materialismo), em perspectivas histórica e crítica. Conclui-se que a adoção do multilateralismo enquanto estrutura principal de determinação da lei aplicável, flexibilizado pelo princípio da proximidade, atende mais à imparcialidade cosmopolita que os outros dois métodos. No capítulo IV, propõe-se uma visão cosmopolita do princípio da ordem pública, concentrando-se em duas importantes evoluções teóricas mais recentes: as noções de ordem pública de proximidade e de ordem pública verdadeiramente internacional. Procede-se, ademais, a exame crítico da aplicação da exceção da ordem pública, no que se refere à lei aplicável, na jurisprudência brasileira recente. Ao fim do estudo, as principais conclusões são enumeradas. / This dissertation addresses international choice of law, through the lens of cosmopolitan standards collected from other humanities, undertaking an interdisciplinary approach. Many recent studies on cosmopolitanism are examined, as well as its remote origins, so as to propose links between choice of law and cosmopolitanism. In chapter I, a historical study is undertaken, going back to the origins of cosmopolitanism (Greek and Roman philosophers), dealing moreover with Kants cosmopolitanism (18th century) and contemporary cosmopolitanisms. Accordingly, a division into categories is proposed and some theoretical notions of special importance to choice of law are tackled. In chapter II, cosmopolitan concepts are applied to legal theory. First, consequences are drawn from the idea of cosmopolitanizing law. Afterwards, the relation between Conflict of Laws and cosmopolitanism is addressed. The focus is on the application of the idea of cosmopolitan justice to choice of law. In chapter III, the three existing choice of law methods are addressed (multilateralism, unilateralism and substantialism), historically and critically. It is concluded that the adoption of multilateralism as a general framework, flexibilized by the principe de proximité, is a better option in terms of cosmopolitan impartiality than the other two methods. In chapter IV, a cosmopolitan vision of public policy is proposed, focusing upon two important theories recently conceived: the notions of ordre public de proximité and of truly international public policy. Also, a critical address of the recent application of the public policy exception by Brazilian courts (within the choice of law context) is made. At the end, the main conclusions are enumerated.

This thesis describes all the necessary parts needed to build a complete system for autonomous indoor mapping in 3D. The robotic platform used is a two-wheeled Segway, operating in a planar environment. This, together with wheel odometers, an Inertial Measurement Unit (IMU), two Microsoft Kinects and a laptop comprise the backbone of the system, which can be divided into three parts: The localization and mapping part, which fundamentally is a SLAM (simultaneous localization and mapping) algorithm implemented using the registration technique Iterative Closest Point (ICP). Along with the map being in 3D, it also designed to handle the mapping of dynamic scenes, something absent from the standard SLAM design. The planning used by the system is twofold. First, the path planning - finding a path from the current position to a destination - and second, the target planning - determining where to go next given the current state of the map and the robot. The third part of the system is the control and collision systems, which while they have not received much focus, are very necessary for a fully autonomous system. Contributions made by this thesis include: The 3D map framework Octomap is extended to handle the mapping of dynamic scenes; A new method for target planning, based on image processing is presented; A calibration procedure for the robot is derived that gives a full six degree of freedom pose for each Kinect. Results show that our calibration procedure produces an accurate pose for each Kinect, which is crucial for a functioning system. The dynamic mapping is shown to outperform the standard occupancy grid in fundamental situations that arise when mapping dynamic scenes. Additionally, the results indicate that the target planning algorithm provides a fast and easy way to plan new target destinations. Finally, the entire system’s autonomous mapping capabilities are evaluated together, producing promising results. However, it also highlights some problems that limit the system’s performance such as the inaccuracy and short range of the Kinects or noise added and reinforced by the multiple subsystems / Detta exjobb beskriver delarna som krävs för att för bygga ett komplett system som autonomt kartlägger inomhusmiljöer i tre dimensioner. Robotplattformen är en Segway, som är kapabel att röra sig i ett plan. Segwayn, tillsammans med en tröghetssensor, två Microsoft Kinects och en bärbar dator utgör grunden till systemet, som kan delas i tre delar: En lokaliserings- och karteringsdel, som i grunden är en SLAM-algoritm (simultan lokalisering och kartläggning)  baserad på registreringsmetoden Iterative Closest Point (ICP). Kartan som byggs upp är i tre dimensioner och ska dessutom hantera kartläggningen av dynamiska miljöer, något som orginalforumleringen av SLAM problemet inte klarar av. En automatisk planeringsdel, som består av två delar. Dels ruttplanering som går ut på att hitta en väg från sin nuvarande position till det valda målet och dels målplanering som innebär att välja ett mål att åka till givet den nuvarande kartan och robotens nuvarande position. Systemets tredje del är regler- och kollisionssystemen. Dessa system har inte varit i fokus i detta arbete, men de är ändå högst nödvändiga för att ett autonomt system skall fungera. Detta examensarbete bidrar med följande: Octomap, ett ramverk för kartläggningen i 3D, har utökats för att hantera kartläggningen av dynamiska miljöer; En ny metod för målplanering, baserad på bildbehandling läggs fram; En kalibreringsprocedur för roboten är framtagen som ger den fullständiga posen i förhållande till roboten för varje Kinect. Resultaten visar att vår kalibreringsprocedur ger en nogrann pose for för varje Kinect, vilket är avgörande för att systemet ska fungera. Metoden för kartläggningen av dynamiska miljöer visas prestera bra i grundläggande situationer som uppstår vid kartläggning av dynamiska miljöer. Vidare visas att målplaneringsalgoritmen ger ett snabbt och enkelt sätt att planera mål att åka till. Slutligen utvärderas hela systemets autonoma kartläggningsförmåga, som ger lovande resultat. Dock lyfter resultat även fram problem som begränsar systemets prestanda, till exempel Kinectens onoggranhet och korta räckvidd samt brus som läggs till och förstärks av de olika subsystemen.