<p>Metoda pro&scaron;irene stvarnosti omogućava prikaz stvarnog sveta dopunjenog<br />virtuelnim objektima i nalazi primenu u prezentaciji virtuelnih 3D modela<br />arhitektonskih objekata. U ovom istraživanju unapređen je konceptualni<br />automatski sistem za prezentaciju trodimenzionalnih modela arhitektonskih<br />objekata metodom pro&scaron;irene stvarnosti. Razvijen je novi algoritam za<br />pravilan prikaz okluzije u sistemima prezentacije arhitektonskih objekata<br />metodom pro&scaron;irene stvarnosti. Delovi ovog sistema su detaljnije razrađeni u<br />cilju re&scaron;avanja određenih problema realističnosti prezentacije 3D modela<br />arhitektonskih objekata.</p> / <p>The method of Augmented Reality enables a real world display,<br />supplemented by virtual structures, and it finds its use in the presentation of<br />virtual 3D models of architectural structures. In this research a conceptual<br />automatic system for the presentation of three-dimensional models of<br />architectural structures using the method of Augmented Reality is improved.<br />Particular parts of this system are elaborated in more detail in order to solve<br />particular problems regarding the realistic displays of the presentation. A<br />new algorithm for correct occlusion handling in the presentation of 3D models<br />of architectural structures by the method of Augmented Reality was<br />developed.</p>

The ability to be flexible will be of great importance to stay competitive as a manufacturing company, and the human operator is a key resource to rapidly respond to changes within manufacturing. Creating a cross-trained workforce where the operators have the ability to rotate between tasks is a strategy to increase the labor flexibility, which in turn can increase the manufacturing flexibility. Equipping the operators with supporting technology has been seen beneficial to become more flexible. Using AR (Augmented Reality) for training has great potential, but few tests have been made in a real industrial environment. Furthermore, there is a lack of involvement of the operators in previous research. This study aims to investigate how AR can be implemented practically at an automotive manufacturing company and, by involving the operator, examine how the AR solution can contribute to increased labor flexibility. To fulfill the aim of the study, the following research question was formulated: • What factors are important to consider when implementing AR technology for increased labor flexibility in a manufacturing company? The research process of this study has included a literature review and a single case study conducted at a production line in an automotive manufacturing company. The design thinking process has been followed during the case study, to be able to always include the operators in the process. In the final phase of the case study, two prototypes were created to evaluate, from the operator’s perspective, how AR can be used at the shop floor. Data was gathered using tools from the design thinking toolbox, including explorative interviews and observations. The study results shows that the preferred AR method for experienced operators is using a hand-held device. Head mounted devices still has barriers to overcome, and more tests are needed to evaluate the user acceptance and risks involved with using head mounted devices in an industrial environment. The thesis has contributed to highlight what factors needs to be considered when implementing AR, by conducting real-life tests at the case company. Implementing AR in an industrial environment is not only buying the right hardware and software. There is a need for a strategy in how the technology should be adapted to the organization. This thesis proposes a start of the implementation journey in using AR to increase labor flexibility by formulating solution targets for further developing of AR technology.

As commissioned by Bontouch AB, this project contains the attempt to create an Augmented Reality application for smartphones, where a parcel is visualised in order for a user to get a comprehensive image of the parcel size. The main focus of the project was to create an eectively running en- gine that can process images for computer vision, in order to determine the pose of the smartphone camera. The experi- ment explored the possibilities of using gyroscope measure- ments between input images in order to formulate valid as- sumptions of upcoming images using homographies. These assumptions were meant to unburden the computer vision engine, creating very high performance. The ultimate goal of the engine was to track the motion of a known reference object in the image, with high precision. The proposed method performed adequately, improving reliability of the motion tracking algorithms. The resulting mobile application, run on an iPhone 5S, could perform camera pose estimation at up to 60 times per second, at a video camera feed resolution of 1280x720 pixels. This high performance resulted in a very stable rendition of the parcel. / Som ett uppdrag från Bontouch AB innehåller det här pro- jektet ett försök att skapa en Augmented Reality-applikation för smartphones, där postpaket ska visualiseras för att ge användare en förstärkt bild av paketets storlek. Huvudfo- kus i projektet var att bygga en eektiv motor som kan behandla bilder för datorseende, för att beräkna positionen och riktningen på mobilkameran. Experimentet utforskade möjligheterna för att använda gyroskopdata mellan bilder för att formulera giltiga antaganden hos kommande bilder med hjälp av homografier. Dessa antaganden vad ämna- de att avlasta motorn för datorseende, för att åstadkomma hög prestanda. Målet var att motorn skulle följa rörelsen hos ett givet referensobjekt i bilden, och att göra det med hög precision. Den föreslagna metoden presterade tillräckligt, och för- bättrade pålitligheten hos algoritmerna för att följa objek- tets rörelser. Mobilapplikationen som byggdes, och kördes på iPhone 5S, kunde beräkna kamerans position of riktning upp till 60 gånger per sekund, när videokameran försåg mo- torn med bilder med 1280x720 pixlars upplösning. Den höga prestandan resulterade i en väldigt stabil bild av paketet.

The aim of this thesis is to implement a prototype of a 3D Augmented Reality mobile application. Using 3D is becoming more and more common for professionals as well as users. A good example of that is Google Earth and its 3D view. Implementing a mobile application that takes advantage of 3D and Augmented Reality may be very useful for planning new constructions in both urban and non-urban areas allowing to visualize how the construction will be in the future and how it will interact with its surrounding environment. There is a great potential for such kind of applications. An example could be the modification of a certain area of a city; allowing the inhabitants of that city to preview the project and, hopefully, avoiding unnecessary conflicts related to that project. In non-urban areas this application is also very useful for helping decision making by visualizing, on site, how the project will be and its impact on the environment. In order to preview a future construction there is the need to have a 3D model. Therefore, a 3D format for that model is necessary. Since COLLADA is a 3D standard interexchange format it is used in this thesis. Together with COLLADA, the computer graphics imagery and gaming technology called OpenGL ES 2.0 is used. Using COLLADA and OpenGL ES 2.0 combined with the properties of the views’ layers, the camera input, the sensors in the mobile device and the positioning technologies permit obtaining successful results displaying a 3D object in an Augmented Reality mobile prototype application. Interface elements are implemented as well in order to bring basic usability tools. The results show the advantages of combining technologies in a mobile device and the problems derived from the low accuracy in positioning in such kind of devices. Thus, ideas for improving the positioning accuracy are discussed as well.

It is widely considered that in-store shopping is a repetitive yet vital activity in human life. People are accustomed to making shopping lists on a piece of paper or on their mobile phones, or more commonly, memorizing the list in their minds. However, people tend to forget the items they want to buy if they cannot write them down immediately when they have the shopping demand, let alone keeping the list in their minds. Some work has started to help people resolve this problem, yet most of them are based on smartphones and are focused on riching add-on functions of the shopping list applications instead of allowing real-time recording. Namely, these existing shopping-list systems cannot let people record items and satisfy their information needs while minimizing the intervention to their ongoing activities. In this study, a new Augmented Reality (AR) solution named AR Shopping List was proposed. It is a smart-glasses application that allows users to add items at any time and place and with arbitrary input formats (photos, videos, and voice to text). We conducted semi-structured interviews with twelve participants aged from 20 to 30 by letting them experience the AR Shopping List app themselves on Microsoft HoloLens (1st gen). Our interviews reveal that the AR Shopping List realizes real-time recording, and therefore releases people’s hands from touching a physical device when making a list. It also shows the app’s potential in helping people reduce the opportunity of forgetting something to buy, as well as shopping more targeted. Furthermore, this research sheds light on future designs on smart-glasses applications for assisting people in recording and remembering items, building a new memorizing habit, and further functioning as people’s working memory expansion. / Trots att det är repetitivt att handla i butik så anses det allmänt vara en vital del av vardagen. Det är vanligt förekommande att inköpslistor skrivs ner på ett paper eller på en mobiltelefon, men även att memorera inköpslistor är vanligt förekommande. Att memorera en inköpslista är dock svårt, och det är ofta viktigt att skriva ner varor som behöver införskaffas, så fort behovet att köpa varorna uppstår. Några metoder har tagits fram för att lösa detta problem, men de flesta av dessa metoder är till för att användas på mobiltelefoner och fokuserar främst på att lägga till funktioner för att skapa avancerade inköpslistor, istället för att tillåta skapandet av listor i realtid. Framförallt så kan de existerande systemen för att skapa inköpslistor inte registrera varor och tillfredsställa användarens andra behov, utan att användarens pågående aktiviteter påverkas. I denna studie presenteras en ny lösning kallad AR Shopping List baserad på Augmented Reality (AR). Det är en applikation för smarta glasögon som tillåter användare att lägga till varor när som helst och var som helst, med godtyckligt format (bilder, videor och text genererad med rösten). Vi genomförde semistrukturerade intervjuer där tolv deltagare i åldrarna 20 till 30 år, fick prova på att använda AR Shopping List applikationen på en Microsoft HoloLens (första generationen). Våra intervjuer visar att AR Shopping List kan skapa inköpslistor i realtid, utan att användarna behöver använda en fysisk enhet. De visar även potentialen som applikationen har för att minska antalet tillfällen där varor som behöver köpas in glöms bort, samt potentialen för mer riktade inköp. Dessutom belyser denna rapport designen för framtida applikationer till smarta glasögon för att underlätta skapandet av inköpslistor, bygga upp nya minnesvanor, och för att utöka det aktiva minnet.

<p>When humans delegate tasks---whether to human workers or robots---they do so either to trade money for time, or to leverage additional knowledge and capabilities. For complex tasks, however, describing the work to be done requires substantial effort, which reduces the benefit to the requester who delegates tasks. On one hand, human workers---e.g., crowd workers, friends or colleagues on social network, factory workers---have diverse knowledge and level of commitment, making it difficult to achieve joint efforts towards the requester's goal. In contrast, robots and machines have clearly defined capabilities and full commitment, but the requester lacks an efficient way to coordinate them for flexible workflows. </p><p> </p><p> This dissertation presents a series of workflows and systems to enable efficient work transfer to human workers or robots. First, I present BlueSky, a system that can automatically coordinate hundreds of crowd workers to enumerate ideas for a given topic. The latent structure of the idea enumeration task is decomposed into a three-step workflow to guide the crowd workers. Second, I present CoStory, a system that requests alternative designs from friends or colleagues by decomposing the design task into hierarchical chunks. Third, I present AdapTutAR, a system that delegates machine operation tasks to workers through adaptive Augmented Reality tutorials. Finally, I present Vipo, a system that allows requesters to customize tasks for robots and smart machines through spatial-visual programming. This dissertation demonstrates that decomposing latent task structure enables task delegation in an on-demand, scalable, and distributed way.</p>

Crowdsourcing has become a popular choice for tackling problems that neither computers nor humans alone can solve with adequate speed, cost, and quality. However, instructing crowds to execute tasks in the manner expected by the requesters is challenging. It depends on not only requesters’ task design abilities but also workers’ understanding of the tasks. Task design bridges the communication gap between workers and requesters, which consists of instructions, payment, time limit on task, and the interface for workers to work on. It remains an underdeveloped but important topic that needs further exploration for improving crowdsourcing experience. My research studies task delivery from requesters to crowd workers. The goal is to improve the communication between the two and, in turn, increase accuracy of results and decrease variability due to differing interpretations and perspectives. Specifically, this dissertation presents a series of studies to show that high-quality results can be obtained from human workers through improved task design, by 1) designing incentives to recruit workers with the appropriate skills for given tasks, 2) designing unambiguous instructions to clearly express task requirements, 3) choosing the correct strategy to communicate the requisite task knowledge with workers, and 4) enhancing requesters’ ability to rapidly prototype Augmented Reality (AR) instructions. This dissertation demonstrates that crowdsourcing quality is improved when the tasks are communicated using mediums and structures that align with workers’ preference and utility

<p>In the current manufacturing industry, static work instructions (WI) are still widely used for manufacturing assembly training and they lack the dynamic information that interactive work instructions can offer. Augmented Reality (AR) training systems are receiving increasing interest in the scientific community, but there is a limited amount of research done on the long-term effect of the AR training systems compared with static training systems. This thesis study was done to investigate if interactive WIs such as AR WIs and 3D PDF WIs have an advantage on training efficiency and knowledge sustainability compared to static paper WIs. Within an experiment, it was observed that there are no differences between the three training methods when it comes to training efficiency, but AR WI proved to be more effective in sustaining the user’s long-term recall precision than paper WI.</p>

Augmented Reality (AR) and Virtual Reality (VR) provide powerful, natural, and robust ways to interact with digital content, across a number of different domains. AR and VR, collectively known as Extended Reality (XR), can facilitate the execution of surgical procedures, aid in maintenance and repair of mechanical equipment, provide novel visualization paradigms for data analysis, and even empower new ways to experience video games. These experiences are built on rich, complex real-time interactive systems (RISs) that require the integration of numerous components supporting everything from rendering of virtual content to tracking of objects and people in the real world. There are decades of research on the development of robust RISs, utilizing different software engineering modalities, which facilitate the creation of these systems. While in the past, developers would frequently write all of the components and the “logical glue” themselves (often built with graphics suites such as OpenGL and DirectX), with the the rise of popular 3D game creation engines, such as Unity and Unreal, new development modalities have begun to emerge. While the underlying game engines provide a significantly easier pipeline to integrate different subsystems of AR/VR applications, there are a number of development questions that arise when considering how interaction, visualization, rendering, and application logic should interact, as developers are often left to create the “logical glue” on their own, leading to software components with low reusability. As the needs of users of these systems increase and become more complex, and as the software and hardware technology improves and becomes more sophisticated, the underlying subsystems must also evolve to help meet these needs. In this work, I present a new software design pattern, the Relay & Responder (R&R) pattern, that attempts to address the concerns found with many traditional object-oriented approaches in XR systems. The R&R pattern simplifies the design of these systems by separating logical components from the communication infrastructure that connects them, while minimizing coupling and facilitating the creation of logical hierarchies that can improve XR application design and module reuse. Additionally, I explore how this pattern can, across a number of different research development efforts, aid in the creation of powerful and rich XR RISs. I first present related work in XR system design and introduce the R&R pattern. Then I discuss how XR development can be eased by utilizing modular building blocks and present the Mercury Messaging framework, which implements the R&R pattern. Next I delve into three new XR systems that explore complex XR RIS designs (including user study management modules) using the pattern and framework. I then address the creation of multi-user, networked XR RISs using R&R and Mercury. Finally I end with a discussion on additional considerations, advantages, and limitations of the pattern and framework, in addition to prospective future work that will help improve both.

As Covid-19 has been a long-lasting worldwide pandemic, more companies wish to find a solution in collaborative Augmented Reality (AR). That makes AR a growing technology that allows users to observe a virtual object in the real world in real-time. The virtual object can interact with real-world objects to fully augment the user’s reality. This paper's first aim is to evaluate whether a remote or aphysically co-located AR space is most efficient. The second aim concerns whether AR planes or AR tags will increase efficiency in the virtual environment. The third is to evaluate whether having a supervisor on a desktop with a mouse and keyboard and a screen or holding a phone connected to the same AR space is most efficient. The paper’s experiment’s focus will be to measure efficiency by fetching quantifiable data from the application while the pair of subjects complete the task of building a pyramid with cubes. Three paired t-tests have been done, one for each of the different test requirements. Co-located have been tested against remote, AR tag against AR plane, and 2D against 3D. The null hypothesis for these three tests is that there is no difference. A survey was done to collect qualitative data to determine which configuration was preferred. It was shown that co-located, 2D supervising, and AR planes were perceived as the best configuration. The results of the paired t-tests show that the difference between co-located and remote is significant with a 99% accuracy. At the same time, the two other tests have an insignificant difference, even with a 95% accuracy.