Dissertations / Theses on the topic 'Navigation'

I nästan tre decennier har GPS-koordinater och rutt-instruktioner visats i en top-down 2D-vy. Först i dedikerade navigationssystem, kommersiellt används för körning, till idag med GPS-system tillgängliga i våra smartphones. Det vanligaste sättet att idag visa GPS koordinater är fortfarande i någon form av 2D-vy som visar användaren var den är och vilka vägar / gator som ska tas. Detta har emellertid några problem som vi tror kan lösas med hjälp av Augmented Reality kombinerat med GPS. I denna uppsats beskrivs om och hur en Augmented Reality baserad navigerings vy kan göra det lättare för gående att navigera genom en stad jämfört med en 2D baserad navigering. För att svara på frågan presenterar denna studie en navigationsapplikation som kombinerar de två teknologierna GPS och Augmented Reality som sedan används i ett användartest. Resultaten från användartesterna och frågeformuläret visar att Augmented Reality-baserad navigering används bäst i scenarier där det finns många gator och det är svårt att berätta på en 2D-karta vilken gata du ska ta.<br>For almost three decades GPS coordinates and directions have been displayed with a top-down 2D view. At first in dedicated navigation systems, commercially used for driving, into today having GPS systems available in our everyday smartphones. The most common way to display the coordinates today are still by some sort of 2D view showing the user where it is and what roads/streets to take. This however has some problems that we believe can be solved using Augmented Reality combined with GPS. This paper sets out to answer the question if and how Augmented Reality displayed navigation can make it easier for pedestrians to navigate through a city compared to a 2D displayed navigation. In order to answer the question at hand this study presents a navigation application that combines the two technologies GPS and Augmented Reality which then is used in a user test. The results from the user tests and the questionnaire indicates that Augmented Reality based navigation is best used in scenarios where there are a lot of streets and it is hard to tell on a 2D map which street to take.

In our day to day activity, imagine if you go to a museum, hospital or any kind of huge building. You need to find the best way to get into a specific depart- ment. It might be difficult to find the way even if you have the map of the building in your hand. Indoor positioning systems can be used to locate people or objects inside a building, using radio waves, signals, or other sensory information collected by a smartphone or tablet. Bluetooth Low Energy (BLE) beacons broadcast signals, and bluetooth devices, such as smartphones, can then receive these signals. BLE devices can take Received Signal Strength Indication (RSSI) information together with an algorithm to calculate the location of the user. This is a useful method for indoor environments when using Global Positioning System (GPS) is not an option [1]. In this project I tried to find a better solution for localization and navigation when GPS does not work. The focus of the project is to use communication be- tween smartphones and beacons, for guidance in inside environments, without using GPS. This thesis is about the applications I produced, which can be used for indoor localization and navigation. Using the applications, you can map any building such as university, hospital, museum, big mall etc. To map a building, you upload a map of the building and put waypoints where you placed beacons. Once mapping is done, you can log in to the web admin and put some informa- tion for each beacon. As a user, when outside a nearby mapped building, your phone can get notified (trough bluetooth), and you can download the user app, which includes the map of the building and shows your location. With the user app you can easily find your favorite places in the building and get information about place near you.

This report describes a possible approach to using data fusion to combine vector and raster data to create a three dimensional interactive archipelago. The data is collected by two central governments and consists of real measurements. Vector data are originating from an ENC chart and information from Lantmäteriets web page Digitala Kartbiblioteket. Raster data exists that describes height and orto-photographies from Digitala Kartbiblioteket. OpenSceneGraph has been used to visualize the chart and wxWindows as a base for the user interface. The method used to create the terrain gives a result which at most diverge 0.07 meters from the extracted chart. Places where this error exists are easily detectable.<br>Rapporten beskriver ett möjligt sätt för datafusion mellan vektor och rasterdata för att skapa ett tredimensionellt interaktivt kustlandskap. Datan är insamlad av två olika myndigheter och representerar ett utsnitt av verkliga mätningar. Vektordata utgörs av information som tidigare extraherats från ett ENC sjökort samt information från lantmäteriests webtjänst det Digitala Kartbiblioteket. Rasterdata kommer i form utav höjddata och ortobild från digitala kartbiblioteket. OpenSceneGraph har används för att visualisera sjökortet och wxWindows som bas för användargränssnittet. Den metod som används vid skapandet av terräng ger ett resultat som avviker som mest 0.07 meter från det extraherade sjökortet. Punkter där detta fel uppstår är lätt identifierbara.

Journeying into the information era the need for new technologies used forsending vast amounts of data eciently has risen, as has the possibilities and needfor dierent types of AI-controlled robots. In this project a RC-car was modiedand equipped with a Raspberry PI and laser radar to let it automatically navigatearound a room using UWB transmitters and receivers. A framework for roboticapplications called ROS, Robot Operating System, was used with a large numberof open source packages to ll dierent functions. Custom scripts was created totie everything together, allowing all dierent components in the system to work inunison.

In this thesis, a number of problems are looked at predominately in the area of mobile agent communication protocols. Particularly, with the recent uptake of unstructured, large and dynamic networks there is a demand for cheap, ubiquitous and reliable protocols that will assist in the support of the network through tasks such as information dissemination, information search and retrieval, and network monitoring. One of the exciting new possible solutions to this is in the area of mobile agents where by a team of dedicated agents (physical or purely virtual) act independently or within a team on the network in the goal of solving simple, yet highly valuable, tasks. Independent agents may work within the bounds of their environment and without influence from their colleagues to solve simple or potentially complex tasks. Further, the agents may also act independently but in actuality work as a very complex team with simple underlying principles allowing for large scale networks and problems to be handled autonomously. In this work, two problems are investigated in detail, the Rendezvous Problem and Network Patrolling. In the rendezvous problem, the goal is to identify algorithms that will permit two agents to rendezvous within some known or unknown environment. This problem, while at first can feel trivial, it can be incredibly difficult when it is realised that all agents are expected to be identical at wake-up time, and that methods must be found that allow for the breaking of symmetry. This thesis provides an investigation into a number of models and environments and tries to provide optimal algorithms for allow rendezvous to occur. Secondly in the area of network patrolling, this work investigates the problem where there exists an environment, in which parts of it are viewed as being vital to network integrity and as such must be monitored. When there are less agents than vital regions the challenge of identifying traversal routes that minimise idle time becomes apparent. In this work an algorithm is presented that minimises this in the ring environment. Finally, this work also looks at other problems in distributed computing and provides exploratory foundation work that could provide alternative models for routing problems, distributed processing, community identification, and presents a number of open problems.

This report presents the work conducted at Safran Electronics &amp; Defense in the context of my master thesis-internship. Vision-hybridisation with inertial systems has great potential in navigation systems. This master thesis investigates this potential and evaluates it on real data of trajectories for one specific hybridisation: loosely-coupled via an Extended Kalman Filter. The vision hybridisation is developed in order to limit the drift of position of the state-of-the-art GPS-hybridisation when the GPS is not available. This thesis presents hybridisation tests on different trajectories that were either simulated from scratch or reconstructed from real vehicle route (stimulation). Using real data for research work brings technical challenges. Some are presented, as well as the proposed solutions to tackle them.<br>Denna rapport presenterar det arbete som utförs på Safran Electronics &amp; Defense I samband med mitt masterprojekt-praktik. Visionshybridisering med tröghetssystem har stor potential I navigationssystem. Detta examensarbete undersöker denna potential och utvärderar den på reella uppgifter om banor för en specifik hybridisering: Löst kopplat via ett ”Extended Kalman Filter”. Visionshybridiseringen utvecklas för att begränsa driften av positionen för den senaste GPS-hybridiseringen när GPS inte är tillgänglig. Avhandlingen presenterar hybridiseringstester på olika banor som antingen simulerades från början eller rekonstruerades från reell fordonsledning (stimulering). Att använda verkliga data för forskningsarbete innebär tekniska utmaningar. Vissa presenteras, liksom de föreslagna lösningarna för att hantera dem.

This paper deals with study of inertial navigation, global navigation satellite system, and their fusion into the one navigation solution. The first part of the work is to calculate the trajectory from accelerometers and gyroscopes measurements. Navigation equations calculate rotation with quaternions and remove gravity sensed by accelerometers. The equation’s output is in earth centred fixed navigation frame. Then, inertial navigation errors are discussed and focused to the bias correction. Theory about INS/GNSS inte- gration compares different integration architecture. The Kalman filter is used to obtain navigation solution for attitude, velocity and position with advantages of both systems.

<p>In this paper we examine the need of navigational aids when designing interfaces for e-newspapers </p><p>– newspapers presented on a digital paper built on E-Ink technology. By reviewing literature on </p><p>navigation, and by handling input from both newspaper designers and potential e-newspaper </p><p>adopters, we have suggested a number of navigational aids for the future e-newspaper. Our </p><p>suggestions have been tested through a prototype using a modification of the Cooperative </p><p>Usability Testing model (CUT) on a total of fifteen potential users. The results show that most </p><p>users prefer a linear organization of the e-newspaper. To render a sense of depth in this flat </p><p>medium, page-numbering is essential. Several different interaction possibilities will also be </p><p>needed to ease the navigation and our suggestions include a blend of page-turning and hyper </p><p>linking, combined with an index to give the user a better overview of the content.</p>

Indoor navigation for autonomous vehicles and robots is an area of research and development with great promises for both current and future applications. Examples include robots assisting humans in indoor tasks, and industrial applications such as warehouse management using autonomous robots [Jensen, 2001]. This project examines the possibilities and limitations of navigating an autonomous vehicle in an enclosed area with the aid of visual recognition software and distancing sensors. The navigation works by using two sets of references: the distance and the relative angle to a point of origin that in this project is a visual reference attached to a flat and visually clean background. The autonomous vehicle is constructed with open source hardware and utilizes already available visual recognition software and all control software is written in Python 2.7. The scope of the project limits the navigation of the robot on a flat surface with no obstacles and with access to a nearby flat wall with a visual reference. A demonstrator was built and empirically tested for its navigational accuracy. The positional accuracy was found to have a mean deviation of ± 1 and ± 4.5 centimeters for the x and y-axis respectively.<br>Navigering och lokalisering inomhus är ett hett forskningsområde både inom vetenskapen och ingenjörstillämpningar. Exempel på system som kan förbättras med sådan teknik är robotar som assisterar människor i hemmet samt automatisering av industrirobotar som är fria att röra sig över golvytor [Jensen, 2001]. Detta kandidatexamensprojekt undersöker möjligheterna och begränsningarna av navigering inomhus för en autonom robot med hjälp av färg-igenkännande bildbehandling och avståndssensorer. Navigeringen sker med hjälp av två riktmärken: en visuell referens monterad på en plan vägg och avståndet mellan robot och vägg. Robotens interna styrelektronik, sensorer samt mjukvara är alla open source. Bredden av projektet begränsas av villkoren att navigationen sker på en plan yta utan hinder samt tillgång till en plan vägg med en visuell referens. Slutgiltiga systemets navigationssäkerhet kontrollerades och mättes empiriskt och uppskattades till att ha en medelavvikelse på ± 1 cm och ± 4.6 cm för x respektive y-axeln.

An Inertial Navigation System (INS) can individually produce the navigation data, i.e.position, velocity, of the aircraft without any help or aid. However, a large number of errors are ntroduced by sensors causing to an unacceptable drift in the output. Because of this reason, external aids are used to correct INS. Using these aids an integrated navigation structure is developed. In an integrated navigation system, INS output is used to alculate current navigation states<br>aid is used to supply external measurements and dierent algorithms are used to provide the most probable corrections to the state estimate using all data. One of the integrated navigation approaches is Terrain Aided Navigation (TAN). Terrain Aided Navigation is a technique to estimate the position of a moving vehicle by comparing the measured terrain profile under the vehicle to a stored map, DTED. This thesis describes the theoretical aspects implementation of a simulation environment, simulations of the implemented Kalman Filtering TAN algorithms with developed INS model. In order to perform the study, first a thorough survey of the literature on TAN navigation algorithms is performed. Then, we have developed a dynamics simulation environment. A flight profile generator is designed. Since, the main issue of this work is to correct INS, an Strapdown INS model developed using Matlab INS Toolbox. Therefore, to model a Strapdown INS, mathematical equations of INS system are derived and they are linearized to form linear error model. In addition, a radar altimeter simulator is also developed that provides measurement to the error dynamics. Then, a Kalman filter structure is designed and implemented using Matlab. The simulations are done with dierent linearization approaches using Kalman filter structure. Finally, the performance of the implemented algorithms are evaluated.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 1987.<br>MICROFICHE COPY AVAILABLE IN ARCHIVES AND SCIENCE<br>Bibliography: leaves 219-225.<br>by Shahriar Negahdaripour.<br>Ph.D.

The purpose of this study was to investigate novel methods on an unmanned sailing boat, which enables it to sail fully autonomously, navigate safely, and perform long-term missions. The author used robotic sailing boat prototypes for field experiments as his main research method. Two robotic sailing boats have been developed especially for this purpose. A compact software model of a sailing boat's behaviour allowed for further evaluation of routing and obstacle avoidance methods in a computer simulation. The results of real-world experiments and computer simulations are validated against each other. It has been demonstrated that autonomous boat sailing is possible by the effective combination of appropriate new and novel techniques that will allow autonomous sailing boats to create appropriate routes, to react properly on obstacles and to carry out sailing manoeuvres by controlling rudder and sails. Novel methods for weather routing, collision avoidance, and autonomous manoeuvre execution have been proposed and successfully demonstrated. The combination of these techniques in a layered hybrid subsumption architecture make robotic sailing boats a promising tool for many applications, especially in ocean observation.

Mobile robots that encounter people on a regular basis must react to them in some way. While traditional robot control algorithms treat all unexpected sensor readings as objects to be avoided, we argue that robots that operate around people should react socially to those people, following the same social conventions that people use around each other. This thesis presents our COMPANION framework: a Constraint-Optimizing Method for Person–Acceptable NavigatION. COMPANION is a generalized framework for representing social conventions as components of a constraint optimization problem, which is used for path planning and navigation. Social conventions, such as personal space and tending to the right, are described as mathematical cost functions that can be used by an optimal path planner. These social conventions are combined with more traditional constraints, such as minimizing distance, in a flexible way, so that additional constraints can be added easily. We present a set of constraints that specify the social task of traveling around people. We explore the implementation of this task first in simulation, where we demonstrate a robot’s behavior in a wide variety of scenarios. We also detail how a robot’s behavior can be changed by using different relative weights between the constraints or by using constraints representing different sociocultural conventions. We then explore the specific case of passing a person in a hallway, using the robot Grace. Through a user study, we show that people interpret the robot’s behavior according to human social norms, and also that people ascribe different personalities to the robot depending on its level of social behavior. In addition, we present an extension of the COMPANION framework that is able to represent joint tasks between the robot and a person. We identify the constraints necessary to represent the task of having a robot escort a person while traveling side-by-side. In simulation, we show the capability of this representation to produce behaviors such as speeding up or slowing down to travel together around corners, as well as complex maneuvers to travel through narrow chokepoints and return to a side-by-side formation. Finally, we present a newly designed robot, Companion, that is intended as a platform for general social human–robot research. Companion is a holonomic robot, able to move sideways without turning first, which we believe is an important social capability. We detail the design and capabilities of this new platform. As a whole, this thesis demonstrates both a need for, and an implementation and evaluation of, robots that navigate around people according to social norms.

In the case of one car following another to a destination, it is very effective at getting the second vehicle to the destination quickly; however, the driver of the second car may not learn the route. Yet, for individuals, such as firefighters, law enforcement, and military personnel, it is imperative that a route be learned quickly and accurately and that an awareness of the situation is maintained while they traverse the given route. This leads to three questions, (a) will navigation aids affect initial route navigation; (b) will navigation aids affect retention; and (c) will navigation aids affect situation awareness while en route? The hypotheses of this study were that navigation aids would significantly increase the speed at which a person can initially navigate a route, but the use of the aids would significantly decrease the retention of the route navigated. The findings of this study support the hypotheses. The results suggest that participants that followed a confederate and participants that were given verbal directions were quicker and made fewer errors than participants that reviewed a map or initially figured the route out on their own (control group). The study also showed that as the participants navigated the route for a second time with no navigational assistance, the ones that reviewed a map or that were in the control group outperformed participants that initially had a confederate to follow or were given verbal directions their first time through. Finally, no real effects were found on the participants' situation awareness during the retention portion of the study.<br>Ph.D.<br>Other<br>Engineering and Computer Science<br>Modeling and Simulation

Approved for public release, distribution is unlimited<br>This thesis investigates land navigators' performance differences in land navigation when different navigation aids are used. The question that this thesis attempts to answer is whether the use of Global Positioning System (GPS) in land navigation results in a performance dependency, and, if so, whether that dependency adversely affects performance. To address these questions an experiment was conducted to see if the use of GPS makes map and compass training obsolete. The participants were divided into two training groups; map + compass navigation and GPS navigation. The experiment studied human performance differences, human error, and transfer of training while participants navigated using only GPS in the first part, and map + compass in the second part of the experiment. The results suggested that map +compass training is always preferable. A map +compass native land navigator outperforms a GPS native land navigator when GPS is not accessible. This evidence suggests that a military land navigator, in particular, should know both navigation techniques and should be able to switch from one to the other without any hesitation.

Psychology<br>Ph.D.<br>Navigation proficiency - the ability to find and recall new and familiar locations - varies widely among individuals (e.g., Schinazi, Epstein, Nardi, Newcombe, & Shipley, 2013; Weisberg, Schinazi, Newcombe, Shipley, & Epstein, 2014). The cognitive processes that support effective navigation have been theoretically sketched out (e.g., Wolbers & Hegarty, 2010), but how do those processes contribute to aspects of and individual differences in navigation behavior? Using a virtual environment to assess navigation proficiency (Weisberg et al., 2014), we conducted two studies to investigate whether individual differences in navigating meaningfully relate to memory capacity (Study1) and navigation strategy (Study 2). Results from Study 1 suggest that working memory capacity may limit some participants' ability to build accurate cognitive maps. Using a virtual environment paradigm based on the rodent T-maze (Marchette, Bakker, & Shelton, 2011), Study 2 shows that good navigators do not prefer to use a place-based strategy over a response-based strategy, but there was an interaction between strategy selection and goals found. Good navigators who used a place-based strategy found more goals than good navigators who used a response-based strategy; the opposite was true for bad navigators. Emerging from this set of studies is a richer picture of how individual differences in cognitive traits (i.e., working memory capacity), and strategy choice relate to navigation proficiency.<br>Temple University--Theses

The most common application of hypertext today is found on the World Wide Web, with the numbers of sites and potential users increasing continually. Hypertext systems are characterized by hyperlinks that allow users nonsequential access to the documents contained within them. Because users are not constrained to read through these documents in a linear manner, new problems may arise not found in traditional paper versions. These problems are generally characterized by a sense of being &quot;lost&quot; within a hypertext system. The user may not know exactly where they are or how to get where they want to be. They have lost many of the visual cues that indicate position found in ordinary texts like books. Navigational aids or overview maps have been suggested as a means to help counteract this problem. These navigational aids can take a standard table-of-contents and extend it dynamically or provide a completely new paradigm of browsing. To that extent, many new varieties of maps (including three-dimensional ones) have been developed but not thoroughly studied. As well, it may be theorized that users of differing cognitive abilities may be helped or hindered by such devices. An empirical study was performed to investigate the effect of multidimensional maps. Three different navigational aids were examined which varied the way pages are displayed along one, two or three dimensions. Two hypertext systems were also where one was roughly twice the size of the other. The participants were given a search task twice to examine performance on page revisits. Finally, three cognitive tests were given to view the effects of individual differences. These included a spatial ability, verbal ability and visual memory test. The results indicated that no performance differences existed between the different navigational aids. However, a significant interaction was present between the maps and the type of Web site; smaller Web sites benefited from the 3D navigational aid. It is theorized that an observed effect for hypertext system was due to site complexity as opposed to size. The results from the cognitive ability measures were mixed. People with low verbal ability scores took longer to locate answers. People with high spatial ability scores found more answers and had scores that were less sensitive to the type of navigational aid used. No significant differences were discovered between people of high and low visual memory abilities.<br>Master of Science

<p>The standard way for both ground and aerial vehicles to navigate is to use anInertial Navigation System, INS, containing an Inertial Measurement Unit, IMU,measuring the acceleration and angular rate, and a GPS measuring the position.The IMU provides high dynamic measurements of the acceleration and the angularrate, which the INS integrates to velocity, position and attitude, respectively.While being completely impossible to jam, the dead-reckoned estimates will driftaway, i.e., the errors are unbounded. In conjunction with a GPS, providing lowdynamic updates with bounded errors, a highly dynamic system without any driftis attained. The weakness of this system is its integrity, since the GPS is easilyjammed with simple equipment and powered only by a small standard battery.When the GPS is jammed this system falls back into the behavior of the INS withunbounded errors. To counter this integrity problem a camera can be used aseither a back up to the GPS or as its replacement. The camera provides imageswhich are then matched versus a reference, e.g., a map or an aerial photo, to getsimilar estimates as the GPS would provide. The camera can of course also bejammed by blocking the view of the camera with smoke. Bad visibility can alsooccur due to bad weather, but a camera based navigation system will definitelybe more robust than one using GPS.This thesis presents two ways to fuse the measurements from the camera and theIMU, both of them utilizing the Harris corner detector to find point correspondencesbetween the camera image and an aerial photo. The systems are evaluatedby simulated data mimicking both a low and a high accuracy IMU and a camerataking snapshots of the aerial photo. Results show that for the simulated cameraimages the implemented corner detector works fine and that the overall result iscomparable to using a GPS.</p><br><p>Standardsättet för både flygande och markgående fordon att navigera är att användaett tröghetsnavigeringssystem, innehållande en IMU som mäter acceleration ochvinkelhastighet, tillsammans med GPS. IMU:n tillhandahåller högfrekventa mätningarav acceleration och vinkelhastighet som integreras till hastighet, positionoch attityd. Ett sådant system är omöjligt att störa, men lider av att de dödräknadestorheterna hastighet, position och attityd, med tiden, kommer att driva ivägifrån de sanna värdena. Tillsammans med GPS, som ger lågfrekventa mätningarav positionen, erhålls ett system med god dynamik och utan drift. Svagheten i ettvvisådant system är dess integritet, då GPS enkelt kan störas med enkel och billigutrustning. För att lösa integritetsproblemet kan en kamera användas, antingensom stöd eller som ersättare till GPS. Kameran tar bilder som matchas gentemoten referens ex. en karta eller ett ortofoto. Det ger liknande mätningar som de GPSger. Ett kamerabaserat system kan visserligen också störas genom att blockerasynfältet för kameran med exempelvis rök. Dålig sikt kan också uppkomma pågrund av dåligt väder eller dimma, men ett kamerabaserat system kommer definitivtatt vara robustare än ett som använder GPS.Det här examensarbetet presenterar två sätt att fusionera mätningar från etttröghetssystem och en kamera. Gemensamt för båda är att en hörndetektor, Harriscorner detector, används för att hitta korresponderande punkter mellan kamerabildernaoch ett ortofoto. Systemen utvärderas på simulerat data. Resultatenvisar att för simulerade data så fungerar den implementerade hörndetektorn ochatt prestanda i nivå med ett GPS-baserat system uppnås.</p>

Over the last years researchers proposed numerous indoor localisation and navigation systems. However, solutions that use WiFi or Radio Frequency Identification require infrastructure to be deployed in the navigation area and infrastructureless techniques, e.g. the ones based on mobile cell ID or dead reckoning suffer from large accuracy errors. In this Thesis, we present a novel approach of infrastructure-less indoor navigation system based on computer vision Structure from Motion techniques. We implemented a prototype localisation and navigation system which can build a navigation map using area photos as input and accurately locate a user in the map. In our client-server architecture based system, a client is a mobile application, which allows a user to locate her or his position by simply taking a photo. The server handles map creation, localisation queries and pathnding. After the implementation, we evaluated the localisation accuracy and latency of the system by benchmarking navigation queries and the model creation algorithm. The system is capable of successfully navigating in Aalto University computer science department library. We were able to achieve an average error of 0.26 metres for successfully localised photos. In the Thesis, we also present challenges that we solved to adapt computer vision techniques for localisation purposes. Finally we observe the possible future work topics to adapt the system to a wide use.<br>Forskare har de senaste åren framfört olika inomhusnavigations- och lokaliseringssystem. Dock kräver lösningar som använder WiFi eller radiofrekvens identifikation en utbyggdnad av stödjande infrastruktur i navigationsområdena. Även teknikerna som används lider av precisionsfel. I det här examensarbetet redovisar vi en ny taktik för inomhusnavigation som använder sig av datorvisualiserings Structure from Motion-tekniker. Vi implementerade en navigationssystemsprototyp som använder bilder för att bygga en navigationskarta och kartlägga användarens position. I vårt klient-server baserat system är en klient en mobilapplikation som tillåter användaren att hitta sin position genom att ta en bild. På server-sidan hanteras kartor, lokaliseringsförfrågor och mättningar av förfrågorna och algoritmerna som används. Systemet har lyckats navigera genom Aalto Universitets datorvetenskapsbiblioteket. Vi lyckades uppnå en felmarginal pa 0.26 meter för lyckade lokaliseringsbilder. I arbetet redovisar vi utmaningar som vi har löst för att anpassa datorvisualiseringstekniker for lokalisering. Vi har även diskuterat potentialla framtida implementationer for att utvidga systemet.

The trackball metaphor is exploited in many applications where volumetric data needs to be explored. Although it provides an intuitive way to inspect the overall structure of objects of interest, an in-detail inspection can be tedious - or when cavities occur even impossible. Therefore we propose a context-aware navigation technique for the exploration of volumetric data. While navigation techniques for polygonal data require information about the rendered geometry, this strategy is not sufficient in the area of volume rendering. Since rendering parameters, e.g., the transfer function, have a strong influence on the visualized structures, they also affect the features to be explored. To compensate this effect we propose a novel image-based navigation approach for volumetric data. While being intuitive to use, the proposed technique allows the user to perform complex navigation tasks, in particular to get an overview as well as to perform an in-detail inspection without any navigation mode switches. The technique can be easily integrated into raycasting based volume renderers, needs no extra data structures and is independent of the data set as well as the rendering parameters. We will discuss the underlying concepts, explain how to enable the navigation at interactive frame rates using OpenCL, and evaluate its usability as well as its performance.

Approved for public release; distribution is unlimited<br>This study investigated the automated satellite image navigation method (Auto-Avian) developed and tested by Spaulding (1990) at the Naval Postgraduate School. The Auto-Avian method replaced the manual procedure of selecting Ground Control Points (GCPs) with an autocorrelation process that utilizes the World Vector Shoreline (WVS) provided by the Defense Mapping Agency (DMA) as a "string" of GCPs to rectify satellite images. The automatic cross-correlation of binary references (WVS) and search (image) windows eliminated the subjective error associated with the manual selection of GCPs and produced accuracies comparable to the manual method. This study expanded the scope of Spaulding's (1990) research. The worldwide application of the Auto-Avian method was demonstrated in three world regions (eastern North Pacific Ocean, eastern North Atlantic Ocean, and Persian Gulf). Using five case studies, the performance of the Auto-Avian method on "less than optimum" images (i.e., islands, coastlines affected by lateral distortion and/or cloud cover) was investigated. The result indicated that utilizing the Auto-Avian method on these "less than optimum images" could achieve navigational accuracies approaching those obtained by Spaulding (1990).

We have designed and demonstrated a new class of medical navigation methods that use the fingerprint-like biometrically distinct ultrasound echo patterns produced by different locations in tissue. As an example of this new biometric navigation approach, we have constructed and tested a system that uses ultrasound data to achieve prospective motion compensation in MRI, especially for respiratory motion during interventional MRI procedures in moving organs such as the liver. The ultrasound measurements are collated with geometrical information from MRI during a training stage to form a mapping table that relates ultrasound measurements to positions. During prospective correction, the system makes frequent ultrasound measurements and uses the map to determine the corresponding position. Results in motorized linear motion phantoms and freely breathing animals indicate that the system performs well. Apparent motion is reduced by up to 97.8%, and motion artifacts are reduced or eliminated in 2D Spoiled Gradient-Echo images. The motion compensation is sufficient to permit MRI thermometry of focused ultrasound heating during respiratory-like motion, with results similar to those obtained in the absence of motion. This new technique may have applications for MRI thermometry and other dynamic imaging in the abdomen during free breathing. We have also extended this technique to situations in which external position information during training is unavailable or incomplete, by extending the concept of Simultaneous Localization and Mapping to include determining the topology of a dense motion path through a gaussian random field. In the course of these investigations, we have also developed modified forms of referenceless MRI thermometry and Kalman filtering, specially adapted to optimize accuracy under our experimental conditions.

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004.<br>Includes bibliographical references (p. 53-54).<br>In this thesis we propose a vision-based robot navigation system that constructs a high level topological representation of the world. A robot using this system learns to recognize rooms and spaces by building a hidden Markov model of the environment. Motion planning is performed by doing bidirectional heuristic search with a discrete set of actions that account for the robot's nonholonomic constraints. The intent of this project is to create a system that allows a robot to be able to explore and to navigate in a wide variety of environments in a way that facilitates goal-oriented tasks.<br>by Daniel R. Roth.<br>M.Eng.

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2018.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 155-164).<br>Network navigation is a promising paradigm for enabling location-awareness in dynamic wireless networks. A wireless navigation network consists of agents (mobile with unknown locations) and anchors (possibly mobile with known locations). An agent can estimate its locations based on inter- and intra-node measurements, as well as prior knowledge. In the presence of limited wireless resources, only a subset rather than all of the node pairs can perform inter-node measurements at a time. The procedure of selecting node pairs at different time instants for inter-node measurements, referred to as network scheduling, affects the time evolution of agents' localization errors. The key to achieve high navigation accuracy and efficient channel usage is to maximize the benefit from agents' inter-node measurements. Therefore, it is critical to design scheduling algorithms that decide for each agent with whom and when to perform inter-node measurements. This thesis introduces situation-aware scheduling that exploits network states to adaptively schedule agents' inter-node measurements. In particular, an analytical framework is developed to determine the effects of scheduling strategies and network settings on the localization error evolution. Furthermore, efficient and distributed situation-aware scheduling algorithms tailored for wireless navigation networks are designed, leading to high navigation accuracy and efficient channel usage. The first part of the thesis develops an analytical framework to determine the localization error evolution as a function of scheduling algorithms and network settings. In particular, both sufficient and necessary conditions for the boundedness of the error evolution are provided. Furthermore, opportunistic and random situation-aware scheduling strategies are proposed, and bounds on the corresponding time-averaged network localization errors are derived. These strategies are proved to be optimal in terms of the error scaling with the number of agents. Finally, the navigation accuracy is shown to be improved by sharing the wireless resources among multiple measurement pairs instead of allocating all the resources to a single pair at a time. The second part of the thesis designs efficient slotted and unslotted situation-aware scheduling algorithms tailored for wireless navigation networks based on the analytical results from the first part. The algorithm parameters, such as access probabilities and access rates, are optimized based on bounds for the time-averaged network localization error (NLE). The proposed algorithms lead to significant performance improvement compared with scheduling algorithms from wireless communication networks. The third part of the thesis develops a framework for the design of random-access-based distributed and asynchronous scheduling algorithms for wireless navigation networks, in which the channel access probabilities are optimized based on the evolution of agents' localization errors. The proposed algorithm achieves higher navigation accuracy and more efficient channel usage than the commonly used carrier sensing multiple access (CSMA) algorithm from wireless communication networks, at the cost of minimal communication overhead and computational complexity. The performance improvement is shown via numerical and experimental results. The contributions of this thesis provide a framework for the analysis and design of scheduling algorithms for wireless navigation networks, leading to high-accuracy, efficient, and flexible network navigation.<br>by Tianheng Wang.<br>Ph. D.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2003.<br>Includes bibliographical references (p. 175-185).<br>Deep-sea archaeology, an emerging application of autonomous underwater vehicle (AUV) technology, requires precise navigation and guidance. As science requirements and engineering capabilities converge, navigating in the sensor-limited ocean remains a fundamental challenge. Despite the logistical cost, the standards of archaeological survey necessitate using fixed acoustic transponders - an instrumented navigation environment. This thesis focuses on the problems particular to operating precisely within such an environment by developing a design method and a navigation algorithm. Responsible documentation, through remote sensing images, distinguishes archaeology from salvage, and fine-resolution imaging demands precision navigation. This thesis presents a design process for making component and algorithm level tradeoffs to achieve system-level performance satisfying the archaeological standard. A specification connects the functional requirements of archaeological survey with the design parameters of precision navigation. Tools based on estimation fundamentals - the Cram6r-Rao lower bound and the extended Kalman filter - predict the system-level precision of candidate designs. Non-dimensional performance metrics generalize the analysis results. Analyzing a variety of factors and levels articulates the key tradeoffs: sensor selection, acoustic beacon configuration, algorithm selection, etc. The abstract analysis is made concrete by designing a survey and navigation system for an expedition to image the USS Monitor. Hypothesis grid (Hgrid) is both a representation of the sensed environment and an algorithm for building the representation. Range observations measuring the line-of-sight distance between two acoustic transducers are subject to multipath errors and spurious returns.<br>The quality of this measurement is dependent on the location of the estimator. Hgrids characterize the measurement quality by generating a priori association probabilities - the belief that subsequent measurements will correspond to the direct-path, a multipath, or an outlier - as a function of the estimated location. The algorithm has three main components: the mixed-density sensor model using Gaussian and uniform probability distributions, the measurement classification and multipath model identification using expectation-maximization (EM), and the grid-based spatial representation. Application to data from an autonomous benthic explorer (ABE) dive illustrates the algorithm and shows the feasibility of the approach.<br>by Brian Steven Bingham.<br>Ph.D.

Les remarquables capacités de navigation des insectes nous prouvent à quel point ces " mini-cerveaux " peuvent produire des comportements admirablement robustes et efficaces dans des environnements complexes. En effet, être capable de naviguer de façon efficace et autonome dans un environnement parfois hostile (désert, forêt tropicale) sollicite l'intervention de nombreux processus cognitifs impliquant l'extraction, la mémorisation et le traitement de l'information spatiale préalables à une prise de décision locomotrice orientée dans l'espace. Lors de leurs excursions hors du nid, les insectes tels que les abeilles, guêpes ou fourmis, se fient à un processus d'intégration du trajet, mais également à des indices visuels qui leur permettent de mémoriser des routes et de retrouver certains sites alimentaires familiers et leur nid. L'étude des mécanismes d'intégration du trajet a fait l'objet de nombreux travaux, par contre, nos connaissances à propos de l'utilisation d'indices visuels sont beaucoup plus limitées et proviennent principalement d'études menées dans des environnements artificiellement simplifiés, dont les conclusions sont parfois difficilement transposables aux conditions naturelles. Cette thèse propose une approche intégrative, combinant 1- des études de terrains et de laboratoire conduites sur deux espèces de fourmis spécialistes de la navigation visuelle (Melophorus bagoti et Gigantiops destructor) et 2- des analyses de photos panoramiques prisent aux endroits où les fourmis naviguent qui permettent de quantifier objectivement l'information visuelle accessible à l'insecte. Les résultats convergents obtenus sur le terrain et au laboratoire permettent de montrer que, chez ces deux espèces, les fourmis ne fragmentent pas leur monde visuel en multiples objets indépendants, et donc ne mémorisent pas de 'repères visuels' ou de balises particuliers comme le ferait un être humain. En fait, l'efficacité de leur navigation émergerait de l'utilisation de paramètres visuels étendus sur l'ensemble de leur champ visuel panoramique, incluant repères proximaux comme distaux, sans les individualiser. Contre-intuitivement, de telles images panoramiques, même à basse résolution, fournissent une information spatiale précise et non ambiguë dans les environnements naturels. Plutôt qu'une focalisation sur des repères isolés, l'utilisation de vues dans leur globalité semble être plus efficace pour représenter la complexité des scènes naturelles et être mieux adaptée à la basse résolution du système visuel des insectes. Les photos panoramiques enregistrées peuvent également servir à l'élaboration de modèles navigationnels. Les prédictions de ces modèles sont ici directement comparées au comportement des fourmis, permettant ainsi de tester et d'améliorer les différentes hypothèses envisagées. Cette approche m'a conduit à la conclusion selon laquelle les fourmis utilisent leurs vues panoramiques de façons différentes suivant qu'elles se déplacent en terrain familier ou non. Par exemple, aligner son corps de manière à ce que la vue perçue reproduise au mieux l'information mémorisée est une stratégie très efficace pour naviguer le long d'une route bien connue ; mais n'est d'aucune efficacité si l'insecte se retrouve en territoire nouveau, écarté du chemin familier. Dans ces cas critiques, les fourmis semblent recourir à une seconde stratégie qui consiste à se déplacer vers les régions présentant une ligne d'horizon plus basse que celle mémorisée, ce qui généralement conduit vers le terrain familier. Afin de choisir parmi ces deux différentes stratégies, les fourmis semblent tout simplement se fier au degré de familiarisation avec le panorama perçu. Cette thèse soulève aussi la question de la nature de l'information visuelle mémorisée par les insectes. Le modèle du " snapshot " qui prédomine dans la littérature suppose que les fourmis mémorisent une séquence d'instantanés photographiques placés à différents points le long de leurs routes. A l'inverse, les résultats obtenus dans le présent travail montrent que l'information visuelle mémorisée au bout d'une route (15 mètres) modifie l'information mémorisée à l'autre extrémité de cette même route, ce qui suggère que la connaissance visuelle de l'ensemble de la route soit compactée en une seule et même représentation mémorisée. Cette hypothèse s'accorde aussi avec d'autres de nos résultats montrant que la mémoire visuelle ne s'acquiert pas instantanément, mais se développe et s'affine avec l'expérience répétée. Lorsqu'une fourmi navigue le long de sa route, ses récepteurs visuels sont stimulés de façon continue par une scène évoluant doucement et régulièrement au fur et à mesure du déplacement. Mémoriser un pattern général de stimulations, plutôt qu'une série de " snapshots " indépendants et très ressemblants les uns aux autres, constitue une hypothèse parcimonieuse. Cette hypothèse s'applique en outre particulièrement bien aux modèles en réseaux de neurones, suggérant sa pertinence biologique. Dans l'ensemble, cette thèse s'intéresse à la nature des perceptions et de la mémoire visuelle des fourmis, ainsi qu'à la manière dont elles sont intégrées et traitées afin de produire une réponse navigationnelle appropriée. Nos résultats sont aussi discutés dans le cadre de la cognition comparée. Insectes comme vertébrés ont résolu le même problème qui consiste à naviguer de façon efficace sur terre. A la lumière de la théorie de l'évolution de Darwin, il n'y a 'a priori' aucune raison de penser qu'il existe une forme de transition brutale entre les mécanismes cognitifs des différentes espèces animales. Le fossé marqué entre insectes et vertébrés au sein des sciences cognitives pourrait bien être dû à des approches différentes plutôt qu'à de vraies différences ontologiques. Historiquement, l'étude de la navigation de l'insecte a suivi une approche de type 'bottom-up' qui recherche comment des comportements apparemment complexes peuvent découler de mécanismes simples. Ces solutions parcimonieuses, comme celles explorées dans cette thèse, peuvent fournir de remarquables hypothèses de base pour expliquer la navigation chez d'autres espèces animales aux cerveaux et comportements apparemment plus complexes, contribuant ainsi à une véritable cognition comparée<br>Navigating efficiently in the outside world requires many cognitive abilities like extracting, memorising, and processing information. The remarkable navigational abilities of insects are an existence proof of how small brains can produce exquisitely efficient, robust behaviour in complex environments. During their foraging trips, insects, like ants or bees, are known to rely on both path integration and learnt visual cues to recapitulate a route or reach familiar places like the nest. The strategy of path integration is well understood, but much less is known about how insects acquire and use visual information. Field studies give good descriptions of visually guided routes, but our understanding of the underlying mechanisms comes mainly from simplified laboratory conditions using artificial, geometrically simple landmarks. My thesis proposes an integrative approach that combines 1- field and lab experiments on two visually guided ant species (Melophorus bagoti and Gigantiops destructor) and 2- an analysis of panoramic pictures recorded along the animal's route. The use of panoramic pictures allows an objective quantification of the visual information available to the animal. Results from both species, in the lab and the field, converged, showing that ants do not segregate their visual world into objects, such as landmarks or discrete features, as a human observers might assume. Instead, efficient navigation seems to arise from the use of cues widespread on the ants' panoramic visual field, encompassing both proximal and distal objects together. Such relatively unprocessed panoramic views, even at low resolution, provide remarkably unambiguous spatial information in natural environment. Using such a simple but efficient panoramic visual input, rather than focusing on isolated landmarks, seems an appropriate strategy to cope with the complexity of natural scenes and the poor resolution of insects' eyes. Also, panoramic pictures can serve as a basis for running analytical models of navigation. The predictions of these models can be directly compared with the actual behaviour of real ants, allowing the iterative tuning and testing of different hypotheses. This integrative approach led me to the conclusion that ants do not rely on a single navigational technique, but might switch between strategies according to whether they are on or off their familiar terrain. For example, ants can recapitulate robustly a familiar route by simply aligning their body in a way that the current view matches best their memory. However, this strategy becomes ineffective when displaced away from the familiar route. In such a case, ants appear to head instead towards the regions where the skyline appears lower than the height recorded in their memory, which generally leads them closer to a familiar location. How ants choose between strategies at a given time might be simply based on the degree of familiarity of the panoramic scene currently perceived. Finally, this thesis raises questions about the nature of ant memories. Past studies proposed that ants memorise a succession of discrete 2D 'snapshots' of their surroundings. Contrastingly, results obtained here show that knowledge from the end of a foraging route (15 m) impacts strongly on the behaviour at the beginning of the route, suggesting that the visual knowledge of a whole foraging route may be compacted into a single holistic memory. Accordingly, repetitive training on the exact same route clearly affects the ants' behaviour, suggesting that the memorised information is processed and not 'obtained at once'. While navigating along their familiar route, ants' visual system is continually stimulated by a slowly evolving scene, and learning a general pattern of stimulation rather than storing independent but very similar snapshots appears a reasonable hypothesis to explain navigation on a natural scale; such learning works remarkably well with neural networks. Nonetheless, what the precise nature of ants' visual memories is and how elaborated they are remain wide open question. Overall, my thesis tackles the nature of ants' perception and memory as well as how both are processed together to output an appropriate navigational response. These results are discussed in the light of comparative cognition. Both vertebrates and insects have resolved the same problem of navigating efficiently in the world. In light of Darwin's theory of evolution, there is no a priori reason to think that there is a clear division between cognitive mechanisms of different species. The actual gap between insect and vertebrate cognitive sciences may result more from different approaches rather than real differences. Research on insect navigation has been approached with a bottom-up philosophy, one that examines how simple mechanisms can produce seemingly complex behaviour. Such parsimonious solutions, like the ones explored in the present thesis, can provide useful baseline hypotheses for navigation in other larger-brained animals, and thus contribute to a more truly comparative cognition

La navigation par satellite prend un virage très important ces dernières années, d'une part par l'arrivée imminente du système Européen GALILEO qui viendra compléter le GPS Américain, mais aussi et surtout par le succès grand public qu'il connaît aujourd'hui. Ce succès est dû en partie aux avancées technologiques au niveau récepteur, qui, tout en autorisant une miniaturisation de plus en plus avancée, en permettent une utilisation dans des environnements de plus en plus difficiles. L'objectif aujourd'hui est de préparer l'utilisation de ce genre de signal dans une optique bas coût dans un milieu urbain automobile pour des applications critiques d'un point de vue sécurité (ce que ne permet pas les techniques d'hybridation classiques). L'amélioration des technologies (réduction de taille des capteurs type MEMS ou Gyroscope) ne peut, à elle seule, atteindre l'objectif d'obtenir une position dont nous pouvons être sûrs si nous utilisons les algorithmes classiques de localisation et d'hybridation. En effet ces techniques permettent d'avoir une position sans cependant permettre d'en quantifier le niveau de confiance. La faisabilité de ces applications repose d'une part sur une recherche approfondie d'axes d'amélioration des algorithmes de localisation, mais aussi et conjointement, sur la possibilité, via les capteurs externes de maintenir un niveau de confiance élevé et quantifié dans la position même en absence de signal satellitaire<br>Satellite navigation has acquired an increased importance during these last years, on the one hand due to the imminent appearance of the European GALILEO system that will complement the American GPS, and on the other hand due to the great success it has encountered in the commercial civil market. An important part of this success is based on the technological development at the receiver level that has rendered satellite navigation possible even in difficult environments. Today's objective is to prepare the utilisation of this kind of signals for land vehicle applications demanding high precision positioning. One of the main challenges within this research domain, which cannot be addressed by classical coupling techniques, is related to the system capability to provide reliable position estimations. The enhancement in dead-reckoning technologies (i.e. size reduction of MEMS-based sensors or gyroscopes) cannot all by itself reach the necessary confidence levels if exploited with classical localization and integration algorithms. Indeed, these techniques provide a position estimation whose reliability or confidence level it is very difficult to quantify. The feasibility of these applications relies not only on an extensive research to enhance the navigation algorithm performances in harsh scenarios, but also and in parallel, on the possibility to maintain, thanks to the presence of additional sensors, a high confidence level on the position estimation even in the absence of satellite navigation signals

Thesis (M.S. in Hydrographic Science)--Naval Postgraduate School, September 1990.<br>Thesis Advisor(s): Wash, C. H. Second Reader: Schnebele, K. J. "September 1990." Description based on title screen as viewed on December 22, 2009. DTIC Descriptor(s): Radiometers, Navigation Reference, Interactions, Accuracy, Theses, Identification, Navigation, Images, Searching, Navigation Satellites, Artificial Satellites, Windows, Vector Analysis, Operators(Personnel), Earth(Planet), Birds, Matching, Automatic Pilots, Shores, Position(Location), Global. DTIC Identifier(s): Satellite Navigation, Program Listings. Author(s) subject terms: Image navigation, binary correlation, automatic landmarking. Includes bibliographical references (p. 78-81). Also available in print.