While the accessibility and technology behind industrial robots is improving as well as becomingless expensive, the installation and conguration of industrial robot cells still proves tobe an expensive venture, especially for small and mid-sized companies. It is therefore of greatinterest to simulate robot cell installations, both for verication of system functionality as wellas for demonstration purposes for clients.However, the construction and conguration of a simulated robot cell is a time-consumingprocess and requires expertise that is often only found in engineers who are experienced withsoftware programming and spacial kinematics. If the process were to be simplied it would bringgreat advantages not only concerning the more ecient use of the time of software engineers butalso in marketing applications.As this paper will show, the use of Virtual Reality (VR) in simulating, displaying andcontrolling robots is a well investigated subject. It has been shown that VR can be used to showrobot simulation in more detail and to specify path movement in task programming. This paperfocuses upon nding and evaluating an intuitive Human Robot Interface (HRI) for interactingwith simulated robots using virtual reality.An HRI is proposed and evaluated, using the Oculus Rift Head Mounted Display (HMD)to display a 3-dimensional (3D) VR environment of a Robot Cell in ABB RobotStudio. Usingmarker-based tracking enabled by ARToolkit, the user's position in real world coordinates isforwarded to the virtual world, along with the position and orientation of a hand-held tool thatallows the user to manipulate the robot targets that are part of the simulated robots program.The system as an HRI was successful in giving the user a strong sense of immersion andgiving them a much better understanding of the robot cell and the positions of the dened robottargets. All participants were also able to dene robot targets much faster with the proposedinterface than when using the standard RobotStudio tools. Results show that the performance ofthe tracking system is adequate with regards to latency and accuracy for updating user positionand hand-held tool when using a video capture resolution of 640x480.

Recent advancements in mobile phone technology have al- lowed mobile augmented reality (MAR) to become feasible. Today’s mobile phones have enough computing power to dis- play augmented reality content and new frameworks make MAR development more accessible. It is no surprise that one of the most popular areas of applications are city tours as this has been a target field since the early days of aug- mented reality (AR) [8]. Without altering the appearance of the city, virtual content can be placed to bring hidden information, such as the city’s history, closer to tourists. The most common choice of the tracking method for this type of application is location-based tracking. Relying only on the GPS signal and sensors like the accelerometer and the gyroscope, the position of the phone is tracked. The location of the digital content in the real world is given by geospatial coordinates. Unfortunately, the accuracy of the sensors is insu⇥cient for accurate placement. Furthermore, the technology’s main advantage over other techniques, such as marker-based tracking, is that the application does not require any change in the city environment. In contrast to that, the other leading technique, marker-based tracking, is a computer vision technology that requires visual clues to work. Marker images would have to be placed in the city for the marker-based tracking technology to function. How- ever, location-based tracking can cause erratic behaviour of the virtual objects, which decreases the quality of the ex- perience. This paper compares location-based and marker- based tracking to show the user experience strengths and weaknesses of both methods to provide design guidelines for choosing the most suitable tracking technology when de- veloping an outdoor walking application. In order to un- cover the strengths and weaknesses, one experimental proto- types for each tracking technology has been developed. The analysis of the results of a controlled user study highlights the comparative strengths and weaknesses of each technol- ogy, location-based and marker-based tracking. The mea- sured user experience di⇤erences demonstrate that for scenes where AR application designers and city o⇥cials are lead- ing to incorporate visual markers, visual-based tracking will outperform location-based tracking. / En jämförande studie av spårningsmetoder för en utomhusapplikation för guidade stadsresor genom AR på mobiltelefoner. Nya tekniska framsteg för mobiltelefoner har gjort Mobile Augmented Reality (MAR) genomförbart. Dagens mobiltelefoner har tillräcklig beräknings-förmåga för att visa Augmented Reality (AR) innehåll och nya frameworks gör MAR- utveckling mer tillgänglig. Det är ingen överraskning att ett av de mest populära användningsområdena är stadsresor eftersom det har varit ett fokus sedan de första dagarna av AR. Utan att ändra utseendet av staden kan virtuellt innehåll placeras för att föra gömd information, till exempel stadens historia, närmare turisterna. Det vanligaste valet av spårningsmetod för dessa AR- applikationer är platsbaserad spårning. Genom endast förlitande på GPS-signaloch sensorer som accelerometern och gyroskop spåras positionen och rotationenav telefonen, och platsen av det digitala innehållet i den verkliga världen ges av geospatiala koordinater. Tyvärr är noggrannheten hos sensorerna ej tillräcklig för korrekt placering. Teknikens största fördel jämfört med andra tekniker, till exempel markörbaserad spårning, är att applikationen inte kräver förändringar i stadsmiljön. I kontrast till det är den andra ledande tekniken,markörbaserad spårning, en datasynteknik som kräver visuella indikationer för att fungera. Markörbilder skulle behöva placeras i staden för att den markörbaserade spårtekniken ska fungera. Emellertid kan platsbaserad spårning orsaka oregelbundet beteende hos de virtuella objekten, vilket minskar kvaliteten på upplevelsen. I denna rapport jämförs platsbaserad och markörbaserad spårning för att visa styrkor och svageter med användarupplevelsen i båda metoderna. Detta görs i syfte av att ge designriktlinjer för att välja den mest lämpliga spårningstekniken för utveckling av en utomhusapplikation. För att finna dessa styrkor och svagheter implementerades en experimentell prototyp för varje spårningsteknik. Analysen av användarstudieren framhäver de motsvarande styrkorna och svagheterna hos platsbaserad och markörbaserad spårning. De mättaskillnaderna inom användarupplevelsen visar att för scener där AR-applikationsdesigners och stadens tjänstemän är villiga att införa visuella markörer så är markörbaserad spårning bättre än platsbaserad spårning.

Augmented Reality är ett brett fält med många olika användningsområden. Det hargjorts flera studier om hur AR kan hjälpa oss att lösa olika arbetsuppgifter på ett effektivare sätt samt att det ingjuter självsäkerhet hos användaren som utför en uppgiftmed hjälp av AR. AR har även letat sig in i tillverkningsindustrin som gör det möjligtför ingenjörer att följa en arbetsprocess med hjälp av AR.Kretskort som är en del av ett system som gör det möjligt för oss att exempelvis ha tillgång till datorer och mobiltelefoner och behöver ibland felsökas. Elektronikingenjörerbehöver ibland identifiera testpunkter och komponenter i den krets på kretskortet somska felsökas. Detta kan underlättas med AR. I denna studie kommer ett experimentatt genomförs för att se om kretskort kan lämpa sig väl som ett Marker-based target.Marker-based target är en bild som möjliggör objektspårning för exempelvis en Head-mounted display, i detta fall en HoloLens. Här efter kommer Marker-based target attbenämnas som mönsterbaserad bild.Experimentet kommer att genomföras med en testgrupp om 10 personer där samtliga kommer att få testa att använda en HoloLens i syftet att lokalisera komponentereller testpunkter på ett kretskort. Detta kommer sedan att jämföras med en traditionell metod genom att identifiera samma komponenter eller testpunkter med en PDF.Testpersonerna kommer även att få svara på en enkät som tittar på om denna metodlämpar sig för att identifiera komponenter med hjälp av AR. En applikation kommeratt skapas som möjliggör att implementera metoden och att testpersonerna kommerkunna använda ett gränssnitt i lokaliseringsprocessen. Resultatet visar att med HoloLensen i jämförelse med traditionella metoden är nästan likvärdig tidsmässigt för attlokalisera komponenter men att vanan av användandet av HoloLensen hade inflytandepå resultatet. / Augmented Reality is an broad field with many different areas of applications. Therehave been several studies on how AR can help us solve various tasks in a more efficientway and that it instills self-confidence in the user who performs a task with the help of AR. AR has also found its way into the manufacturing industry, which enables engineers to follow a work process with the help of AR. For example circuit boards that arepart of a system that makes it possible for us to have access to computers and mobilephones, does sometimes need to undergo troubleshooting process by engineers duringmanufacture.Electronics engineers sometimes need to identify test points and components on thecircuit board that needs troubleshooting. AR can help in this process. In this study, anexperiment will be conducted to see if circuit boards can be well suited as a marker-based target. Marker-based target is an image that enables object tracking for examplewith a Head-mounted display, in this case a HoloLens.The experiment will be conducted with a test group of 10 people where all will beallowed to test a HoloLens in order to locate components or test points on a circuitboard. This method will then be compared to a traditional method by identifying thesame components or test points with a PDF. The test persons will also have to answer aquestionnaire that looks at whether this method is suitable for identifying componentsusing AR. An application will be created that implements the method and that the testpersons will be able to use in the localization process. The results show that the traditional method in comparison with the HoloLens is equivalent for locating components,but the habit of using HoloLens had an influence on the result.

A virtual environment is a set of surroundings that appears to exist to a user through sensory stimuli provided by a computer. By virtual environment, we mean to include environments supporting the full range from VR to pure reality. A necessity for virtual environments is knowledge of the location of objects in the environment. This is referred to as the tracking problem, which points to the need for accurate and precise tracking in virtual environments. Marker-based tracking is a technique which employs fiduciary marks to determine the pose of a tracked object. A collection of markers arranged in a rigid configuration is called a tracking probe. The performance of marker-based tracking systems depends upon the fidelity of the pose estimates provided by tracking probes. The realization that tracking performance is linked to probe performance necessitates investigation into the design of tracking probes for proponents of marker-based tracking. The challenges involved with probe design include prediction of the accuracy and precision of a tracking probe, the creation of arbitrarily-shaped tracking probes, and the assessment of the newly created probes. To address these issues, we present a pioneer framework for designing conformal tracking probes. Conformal in this work means to adapt to the shape of the tracked objects and to the environmental constraints. As part of the framework, the accuracy in position and orientation of a given probe may be predicted given the system noise. The framework is a methodology for designing tracking probes based upon performance goals and environmental constraints. After presenting the conformal tracking framework, the elements used for completing the steps of the framework are discussed. We start with the application of optimization methods for determining the probe geometry. Two overall methods for mapping markers on tracking probes are presented, the Intermediary Algorithm and the Viewpoints Algorithm. Next, we examine the method used for pose estimation and present a mathematical model of error propagation used for predicting probe performance in pose estimation. The model uses a first-order error propagation, perturbing the simulated marker locations with Gaussian noise. The marker locations with error are then traced through the pose estimation process and the effects of the noise are analyzed. Moreover, the effects of changing the probe size or the number of markers are discussed. Finally, the conformal tracking framework is validated experimentally. The assessment methods are divided into simulation and post-fabrication methods. Under simulation, we discuss testing of the performance of each probe design. Then, post-fabrication assessment is performed, including accuracy measurements in orientation and position. The framework is validated with four tracking probes. The first probe is a six-marker planar probe. The predicted accuracy of the probe was 0.06 deg and the measured accuracy was 0.083 plus/minus 0.015 deg. The second probe was a pair of concentric, planar tracking probes mounted together. The smaller probe had a predicted accuracy of 0.206 deg and a measured accuracy of 0.282 plus/minus 0.03 deg. The larger probe had a predicted accuracy of 0.039 deg and a measured accuracy of 0.017 plus/minus 0.02 deg. The third tracking probe was a semi-spherical head tracking probe. The predicted accuracy in orientation and position was 0.54 plus/minus 0.24 deg and 0.24 plus/minus 0.1 mm, respectively. The experimental accuracy in orientation and position was 0.60 plus/minus 0.03 deg and 0.225 plus/minus 0.05 mm, respectively. The last probe was an integrated, head-mounted display probe, created using the conformal design process. The predicted accuracy of this probe was 0.032 plus/minus 0.02 degrees in orientation and 0.14 plus/minus 0.08 mm in position. The measured accuracy of the probe was 0.028 plus/minus 0.01 degrees in orientation and 0.11 plus/minus 0.01 mm in position. These results constitute an order of magnitude improvement over current marker-based tracking probes in orientation, indicating the benefits of a conformal tracking approach. Also, this result translates to a predicted positional overlay error of a virtual object presented at 1m of less than 0.5 mm, which is well above reported overlay performance in virtual environments.