Towards expressive mobile robots

Given the increase in robotic systems for the household, it is imperative to design the expressive modes of these systems, that in turn engender likability, animacy, acceptance, trust and adoption. This paper approaches this problem by proposing a design methodology that can be used to abstract archetypal characters across the system, including form factor, user instructions, and interactive modalities. This approach uses Laban Movement Analysis paired with the Kansei Engineering iterative design approach to dissect movement and visual traits of archetypal characters and marry them to features of the robot and user experience. Specifically, these character traits are explored in a product, channel, consumer framework and are realized through tangible interface elements, such as color, animated eyes, and character specific motion profiles. Finally, the use of priming using familiar characters from popular culture as a means to enhance the recognition of character traits is explored. The effectiveness of this methodology is tested in a user-study, where participants play a game of tic-tac-toe with an aerial robot in virtual reality. Results show that users associated traits specific to each character archetype that were consistent with the intended design. This was bolstered in the priming cases, where users rated these traits more strongly. This was followed by the design and construction of a hardware platform that showcases this methodology, for two platforms, a ground robot and an aerial robot. Finally, the use of a performance setting as a tool for priming potential users is explored, outlined in the performance piece, ”Time to Compile”. Interviews with stakeholders were conducted throughout this work and have informed the approach taken and will be briefly outlined in this thesis as well. This methodology serves as a tool to create meaningful design variations to robotic systems using character archetypes, allowing us to design user- specific personality traits and interactive elements

Deep Aramaic: Towards a synthetic data paradigm enabling machine learning in epigraphy

Epigraphy is witnessing a growing integration of artificial intelligence, notably through its subfield of machine learning (ML), especially in tasks like extracting insights from ancient inscriptions. However, scarce labeled data for training ML algorithms severely limits current techniques, especially for ancient scripts like Old Aramaic. Our research pioneers an innovative methodology for generating synthetic training data tailored to Old Aramaic letters. Our pipeline synthesizes photo-realistic Aramaic letter datasets, incorporating textural features, lighting, damage, and augmentations to mimic real-world inscription diversity. Despite minimal real examples, we engineer a dataset of 250 000 training and 25 000 validation images covering the 22 letter classes in the Aramaic alphabet. This comprehensive corpus provides a robust volume of data for training a residual neural network (ResNet) to classify highly degraded Aramaic letters. The ResNet model demonstrates 95% accuracy in classifying real images from the 8th century BCE Hadad statue inscription. Additional experiments validate performance on varying materials and styles, proving effective generalization. Our results validate the model’s capabilities in handling diverse real-world scenarios, proving the viability of our synthetic data approach and avoiding the dependence on scarce training data that has constrained epigraphic analysis. Our innovative framework elevates interpretation accuracy on damaged inscriptions, thus enhancing knowledge extraction from these historical resources

Traces of emergence: an ontological unification of perception, artefact, and process

Objects are part of a complex matrix that contain emergent experiences and meanings. Ernesto Rogers once claimed that if a spoon was examined carefully enough, one could establish how the maker would design a city. While this observation from the great Italian architect may be an over-generalisation, it draws upon an important point – the objects that humans create are reflections of ourselves, our beliefs, our feelings, motivations, and drives. In short, our whole material and emotional culture. The study of design revolves around the dynamics between form, the processes of making and the diverse experiences of object interaction and use – ontologies of artefact emergence that articulate with the complex patterning structures and practices that produce all of material culture. There are two dominant narratives we must consider when examining design as a practice of making. One, as a narrative of form evolution derived principally from a hylomorphic designer-agent ontology1 and the other, as a narrative of making and manufacturing understood through ontologies of matter manipulation. The relationship between the two narratives, this work will argue, presents deep and poorly understood problems with respect to the current taxonomies and ontologies describing advanced manufacturing, limiting the conceptual evolution of design thinking and processes of making and manufacturing. Moreover, this work will argue that pattern and patterning motions is a key meta-concept for understanding design practice that has until this point, received a limited amount of attention. While there are emerging paradigms of research including Industry 4.0 and ‘new materialism’, these have not comprehensively addressed the core disconnect between understanding process and understanding perception. The new materialism mostly explores the making processes of ‘craft’ - which have an important relation to and are indeed antecedents of advanced industrial processes – that do not include the conceptual innovations of advanced process control, CAM for instance. Industry 4.0, while offering interesting insights and innovations in terms of process control does not tend to examine the assumptions that go into forming its conceptual landscape – process ‘optimization’ or defect minimization are for instance seen as by definition, good.Objects are part of a complex matrix that contain emergent experiences and meanings. Ernesto Rogers once claimed that if a spoon was examined carefully enough, one could establish how the maker would design a city. While this observation from the great Italian architect may be an over-generalisation, it draws upon an important point – the objects that humans create are reflections of ourselves, our beliefs, our feelings, motivations, and drives. In short, our whole material and emotional culture. The study of design revolves around the dynamics between form, the processes of making and the diverse experiences of object interaction and use – ontologies of artefact emergence that articulate with the complex patterning structures and practices that produce all of material culture. There are two dominant narratives we must consider when examining design as a practice of making. One, as a narrative of form evolution derived principally from a hylomorphic designer-agent ontology1 and the other, as a narrative of making and manufacturing understood through ontologies of matter manipulation. The relationship between the two narratives, this work will argue, presents deep and poorly understood problems with respect to the current taxonomies and ontologies describing advanced manufacturing, limiting the conceptual evolution of design thinking and processes of making and manufacturing. Moreover, this work will argue that pattern and patterning motions is a key meta-concept for understanding design practice that has until this point, received a limited amount of attention. While there are emerging paradigms of research including Industry 4.0 and ‘new materialism’, these have not comprehensively addressed the core disconnect between understanding process and understanding perception. The new materialism mostly explores the making processes of ‘craft’ - which have an important relation to and are indeed antecedents of advanced industrial processes – that do not include the conceptual innovations of advanced process control, CAM for instance. Industry 4.0, while offering interesting insights and innovations in terms of process control does not tend to examine the assumptions that go into forming its conceptual landscape – process ‘optimization’ or defect minimization are for instance seen as by definition, good

Automated generation of geometrically-precise and semantically-informed virtual geographic environnements populated with spatially-reasoning agents

La Géo-Simulation Multi-Agent (GSMA) est un paradigme de modélisation et de simulation de phénomènes dynamiques dans une variété de domaines d'applications tels que le domaine du transport, le domaine des télécommunications, le domaine environnemental, etc. La GSMA est utilisée pour étudier et analyser des phénomènes qui mettent en jeu un grand nombre d'acteurs simulés (implémentés par des agents) qui évoluent et interagissent avec une représentation explicite de l'espace qu'on appelle Environnement Géographique Virtuel (EGV). Afin de pouvoir interagir avec son environnement géographique qui peut être dynamique, complexe et étendu (à grande échelle), un agent doit d'abord disposer d'une représentation détaillée de ce dernier. Les EGV classiques se limitent généralement à une représentation géométrique du monde réel laissant de côté les informations topologiques et sémantiques qui le caractérisent. Ceci a pour conséquence d'une part de produire des simulations multi-agents non plausibles, et, d'autre part, de réduire les capacités de raisonnement spatial des agents situés. La planification de chemin est un exemple typique de raisonnement spatial dont un agent pourrait avoir besoin dans une GSMA. Les approches classiques de planification de chemin se limitent à calculer un chemin qui lie deux positions situées dans l'espace et qui soit sans obstacle. Ces approches ne prennent pas en compte les caractéristiques de l'environnement (topologiques et sémantiques), ni celles des agents (types et capacités). Les agents situés ne possèdent donc pas de moyens leur permettant d'acquérir les connaissances nécessaires sur l'environnement virtuel pour pouvoir prendre une décision spatiale informée. Pour répondre à ces limites, nous proposons une nouvelle approche pour générer automatiquement des Environnements Géographiques Virtuels Informés (EGVI) en utilisant les données fournies par les Systèmes d'Information Géographique (SIG) enrichies par des informations sémantiques pour produire des GSMA précises et plus réalistes. De plus, nous présentons un algorithme de planification hiérarchique de chemin qui tire avantage de la description enrichie et optimisée de l'EGVI pour fournir aux agents un chemin qui tient compte à la fois des caractéristiques de leur environnement virtuel et de leurs types et capacités. Finalement, nous proposons une approche pour la gestion des connaissances sur l'environnement virtuel qui vise à supporter la prise de décision informée et le raisonnement spatial des agents situés

DYNAMIC VISUALIZATIONS: Developing a Framework for Crowd-Based Simulations

Since its conception in the 1960s, digital computation has experienced both exponential growth in power and reduction in cost. This has allowed the production of relatively cheap electronics, which are now integrated ubiquitously in daily life. With so much computational data and an ever-increasing accessibility to intelligent objects, the potential for integrating such technologies within architectural systems becomes increasingly viable. Today, dynamic architecture is already emerging across the world; it is inevitable that one day computation will be fully integrated within the infrastructures of our cities. However, as these new forms of dynamic architecture becomes increasingly commonplace, the standard static medium of architectural visualization is no longer satisfactory for representing and visualizing these dynamic spaces, let alone the human interactions within them. Occupancy within a space is already inherently dynamic and becomes even more so with the introduction of these new forms of architecture. This in turn challenges our conventional means of visualizing spaces both in design and communication. To fully represent dynamic architecture, the visualization must be dynamic as well. As such, current single image rendering methods within most existing architectural design pipelines becomes inadequate in portraying both the architectural dynamics of the space, as well as the interaction and influences these dynamics will have with the occupants. This thesis aims to mitigate these shortcomings in architectural visualization by investigating the creation of a crowd simulation tool to facilitate a foundation for a visualization framework that can be continuously built upon based on project needs, which answers the question of how one can utilize current technologies to not only better represent responsive architecture but also to optimize existing visualization methodologies. By using an interdisciplinary approach that brings together architecture, computer science, and game design, it becomes possible to establish a more powerful, flexible, and efficient workflow in creating architectural visualizations. Part One will establish a foundation to this thesis by looking at the state of the current world, its buildings in the sense of dynamic, and the current state of visualization technologies that are being utilized both within architectural design as well as outside of it. Part Two will investigate complex systems and simulation models, as well as investigating ways of integrating them with human behaviors to establish a methodology for creating a working crowd simulation system. Part Three will take the methodology developed within Part Two and integrate it within modern game engines, with the intent of creating an architectural visualization pipeline that can utilize the game engine for both crowd analytics as well as visualization. Part Four will look at some of the various spatial typologies that can be visualized with this tool. Finally, Part Five will speculate on various future directions to improve this tool beyond the current scope of this thesis

Designing Sound for Social Robots: Advancing Professional Practice through Design Principles

Sound is one of the core modalities social robots can use to communicate with the humans around them in rich, engaging, and effective ways. While a robot's auditory communication happens predominantly through speech, a growing body of work demonstrates the various ways non-verbal robot sound can affect humans, and researchers have begun to formulate design recommendations that encourage using the medium to its full potential. However, formal strategies for successful robot sound design have so far not emerged, current frameworks and principles are largely untested and no effort has been made to survey creative robot sound design practice. In this dissertation, I combine creative practice, expert interviews, and human-robot interaction studies to advance our understanding of how designers can best ideate, create, and implement robot sound. In a first step, I map out a design space that combines established sound design frameworks with insights from interviews with robot sound design experts. I then systematically traverse this space across three robot sound design explorations, investigating (i) the effect of artificial movement sound on how robots are perceived, (ii) the benefits of applying compositional theory to robot sound design, and (iii) the role and potential of spatially distributed robot sound. Finally, I implement the designs from prior chapters into humanoid robot Diamandini, and deploy it as a case study. Based on a synthesis of the data collection and design practice conducted across the thesis, I argue that the creation of robot sound is best guided by four design perspectives: fiction (sound as a means to convey a narrative), composition (sound as its own separate listening experience), plasticity (sound as something that can vary and adapt over time), and space (spatial distribution of sound as a separate communication channel). The conclusion of the thesis presents these four perspectives and proposes eleven design principles across them which are supported by detailed examples. This work contributes an extensive body of design principles, process models, and techniques providing researchers and designers with new tools to enrich the way robots communicate with humans

Cultivating the Erratic: Architectural representation and materialisation after the digital turn

This thesis investigates representation and materialisation in contemporary architectural design. Due to cultural and technological shifts, the act of design is no longer squarely located in the abstract realms of drawings or digital geometries. Computer aided manufacturing, physics simulation, and 3d-scanning offer alternative possibilities for design by incorporating the often-erratic qualities of extant objects and materials. These developments call for architects to intervene in and theorise technological transfers between representation and material reality that might otherwise become matters of mere expediency. Spanning in scope from design to technology to theory, the thesis is developed through a combination of analytical enquiry and design driven research. The design works included, Erratic and Completions, explore materialisation and representation against a critical review of key concepts associated with the ‘digital turn’ in architecture during the 1990s and 2000s. The thesis interrogates how those concepts have been developed and challenged in the decades after this turn. Key to the analysis is a critical enquiry about the nature of architectural representation and the significance of theoretical frameworks gleaned from other areas of enquiry, including materialist and post-digital thinking. The implications of the design work are explored by positioning physics simulation and 3d-scanning as means of representation through an interlacing of thinking from such frameworks with detailed accounts of technical apparatuses involved in conception and production.Overall, the thesis aims to build a new position for architectural conception and production. It argues that the means of representation that facilitate architectural design have agency, and that simulation and scanning offer a contemporary context in which the effects of such agencies can be productively observed. This opens a disciplinary discussion on issues of projection, translation, and codification and their role in shaping the architectural imagination. The discussion also extends beyond such architectural concerns and into political critique, as practices, technicalities, and histories of representation condition how we view the world, how we operate in it, and might even modify how we view ourselves

The supernatural guilt trip does not take us far enough

Belief in souls is only one component of supernatural thinking in which individuals infer the presence of invisible mechanisms that explain events as paranormal rather than natural. We believe it is important to place greater emphasis on the prevalence of supernatural beliefs across other domains, if only to counter simplistic divisions between rationality and irrationality recently aligned with the contentious science/religion debate

Engineering Background Knowledge for Social Robots

Social robots are embodied agents that continuously perform knowledge-intensive tasks involving several kinds of information coming from different heterogeneous sources. Providing a framework for engineering robots' knowledge raises several problems like identifying sources of information and modeling solutions suitable for robots' activities, integrating knowledge coming from different sources, evolving this knowledge with information learned during robots' activities, grounding perceptions on robots' knowledge, assessing robots' knowledge with respect humans' one and so on. In this thesis we investigated feasibility and benefits of engineering background knowledge of Social Robots with a framework based on Semantic Web technologies and Linked Data. This research has been supported and guided by a case study that provided a proof of concept through a prototype tested in a real socially assistive context