Robots and virtual agents grow rapidly in behavioural sophistication and complexity. They become better learners and teachers, cooperators and communicators, workers and companions. These artefacts – whose behaviours are not always readily understood by human intuition nor comprehensibly explained in terms of mechanism – will have to interact socially. Moving beyond artificial rational systems to artificial social systems means having to engage with fundamental questions about agenthood, sociality, intelligence, and the relationship between mind and body. It also means having to revise our theories about these things in the course of continuously assessing the social sufficiency of existing artificial social agents. The present thesis presents an empirical study investigating the social influence of physical versus virtual embodiment on people's decisions in the context of a bargaining task. The results indicate that agent embodiment did not affect the social influence of the agent or the extent to which it was perceived as a social actor. However, participants' perception of the agent as a social actor did influence their decisions. This suggests that experimental results from studies comparing different robot embodiments should not be over-generalised beyond the particular task domain in which the studied interactions took place.

Tato práce se zaměřuje na použitelnost brýlí Microsoft HoloLens pro rozšířenou realitu v prototypu pracoviště pro spolupráci člověka s robotem - "ARTable". Použití brýlí je demonstrováno vytvořeným uživatelským rozhraním, které pomáhá uživatelům lépe a rychleji porozumět systému ARTable. Umožňuje prostorově vizualizovat naučené programy, aniž by bylo nutné spouštět samotného robota. Uživatel je veden 3D animací jednotlivých programů a hlasem zařízení, což mu pomůže získat jasnou představu o tom, co by se stalo, pokud by program spustil přímo na robotovi. Implementované řešení také umožňuje interaktivně provést uživatele celým procesem programování robota. Použití brýlí umožňuje mimo jiné zobrazit cenné prostorové informace, například vidění robota, tedy zvýraznit ty objekty, které jsou robotem detekovány.

<div>Intelligent machines, and more broadly, intelligent systems, are becoming increasingly common in the everyday lives of humans. Nonetheless, despite significant advancements in automation, human supervision and intervention are still essential in almost all sectors, ranging from manufacturing and transportation to disaster-management and healthcare. These intelligent machines<i> interact and collaborate</i> with humans in a way that demands a greater level of trust between human and machine. While a lack of trust can lead to a human's disuse of automation, over-trust can result in a human trusting a faulty autonomous system which could have negative consequences for the human. Therefore, human trust should be <i>calibrated </i>to optimize these human-machine interactions. This calibration can be achieved by designing human-aware automation that can infer human behavior and respond accordingly in real-time.</div><div><br></div><div>In this dissertation, I present a probabilistic framework to model and calibrate a human's trust and workload dynamics during his/her interaction with an intelligent decision-aid system. More specifically, I develop multiple quantitative models of human trust, ranging from a classical state-space model to a classification model based on machine learning techniques. Both models are parameterized using data collected through human-subject experiments. Thereafter, I present a probabilistic dynamic model to capture the dynamics of human trust along with human workload. This model is used to synthesize optimal control policies aimed at improving context-specific performance objectives that vary automation transparency based on human state estimation. I also analyze the coupled interactions between human trust and workload to strengthen the model framework. Finally, I validate the optimal control policies using closed-loop human subject experiments. The proposed framework provides a foundation toward widespread design and implementation of real-time adaptive automation based on human states for use in human-machine interactions.</div>

In der vorliegenden Dissertation wurde ein datengetriebenes Verfahren zum maschinellen Lernen von Mensch-Roboter Interaktionen auf Basis von Mensch-Mensch Demonstrationen entwickelt. Während einer Trainingsphase werden Bewegungen zweier Interakteure mittels Motion Capture erfasst und in einem Zwei-Personen Interaktionsmodell gelernt. Zur Laufzeit wird das Modell sowohl zur Erkennung von Bewegungen des menschlichen Interaktionspartners als auch zur Generierung angepasster Roboterbewegungen eingesetzt. Die Leistungsfähigkeit des Ansatzes wird in drei komplexen Anwendungen evaluiert, die jeweils kontinuierliche Bewegungskoordination zwischen Mensch und Roboter erfordern. Das Ergebnis der Dissertation ist ein Lernverfahren, das intuitive, zielgerichtete und sichere Kollaboration mit Robotern ermöglicht.

Bientôt, les robots ne travailleront plus de manière isolée mais avec nous. Ils entrent peu à peu dans notre vie de tous les jours pour coopérer, assister, aider, servir, apprendre, enseigner ou même jouer avec l'homme. Dans ce contexte, nous considérons que ce ne doit pas être à l'homme de s'adapter au robot. Au contraire, le robot doit être capable d'intégrer, dans ses stratégies de planification et de décision, différents facteurs d'effort et de confort et de prendre en compte les préférences et désirs de l'homme ainsi que les normes sociales de son environnement. Tout en respectant les principes de sécurité réglementaire, le robot doit se comporter, naviguer, manipuler, communiquer et apprendre d'une manière qui soit pertinente, acceptée et compréhensible par l'homme. Cette thèse explore et définit les ingrédients clés nécessaires au robot pour développer une telle intelligence socio-cognitive. Elle définit également un cadre pour l'interaction homme-robot permettant de s'attaquer à ces challenges dans le but de rendre le robot socialement intelligent / Robots will no longer be working isolated from us. They are entering into our day-to-day life to cooperate, assist, help, serve, learn, teach and play with us. In this context, it is important that because of the presence of robots, the human should not be on compromising side. To achieve this, beyond the basic safety requirements, robots should take into account various factors ranging from human’s effort, comfort, preferences, desire, to social norms, in their various planning and decision making strategies. They should behave, navigate, manipulate, interact and learn in a way, which is expected, accepted, and understandable by us, the human. This thesis begins by exploring and identifying the basic yet key ingredients of such socio-cognitive intelligence. Then we develop generic frameworks and concepts from HRI perspective to address these additional challenges, and to elevate the robots capabilities towards being socially intelligent

Indiana University-Purdue University Indianapolis (IUPUI) / There have been many endeavors to design humanoid robots that have human characteristics such as dexterity, autonomy and intelligence. Humanoid robots are intended to cooperate with humans and perform useful work that humans can perform. The main advantage of humanoid robots over other machines is that they are flexible and multi-purpose. In this thesis, a human-like robotic arm is designed and used in a task which is typically performed by humans, namely, catching a ball. The robotic arm was designed to closely resemble a human arm, based on anthropometric studies. A rigid multibody dynamics software was used to create a virtual model of the robotic arm, perform experiments, and collect data. The inverse kinematics of the robotic arm was solved using a Newton-Raphson numerical method with a numerically calculated Jacobian. The system was validated by testing its ability to find a kinematic solution for the catch position and successfully catch the ball within the robot's workspace. The tests were conducted by throwing the ball such that its path intersects different target points within the robot's workspace. The method used for determining the catch location consists of finding the intersection of the ball's trajectory with a virtual catch plane. The hand orientation was set so that the normal vector to the palm of the hand is parallel to the trajectory of the ball at the intersection point and a vector perpendicular to this normal vector remains in a constant orientation during the catch. It was found that this catch orientation approach was reliable within a 0.35 x 0.4 meter window in the robot's workspace. For all tests within this window, the robotic arm successfully caught and dropped the ball in a bin. Also, for the tests within this window, the maximum position and orientation (Euler angle) tracking errors were 13.6 mm and 4.3 degrees, respectively. The average position and orientation tracking errors were 3.5 mm and 0.3 degrees, respectively. The work presented in this study can be applied to humanoid robots in industrial assembly lines and hazardous environment recovery tasks, amongst other applications.

There is abundant anecdotal evidence substantiating Mori’s initial observation of the "uncanny valley", a point at which human response to non-human entities drops sharply with respect to comfort (Mori, 1970), and the construct itself has a long-standing history in both Robotics and Psychology. Currently, many fields such as design, training, entertainment, and education make use of heuristic approaches to accommodate the anticipated needs of the user/consumer/audience in certain important aspects. This is due to the lack of empirical substantiation or, in some cases, the impossibility of rigorous quantification; one such area is with respect to the user’s experience of uncanniness, a feeling of "eeriness" or "wrongness" when interacting with artefacts or environments. Uncanniness, however, continues to be defined and measured in a largely subjective way, and often after the fact; an experience or product’s uncanny features are pointed out after the item has been markedly avoided or complained about by the general public. These studies are among the first seeking to determine a constellation of personality traits and physiological responses that incline the user to have a more frequent or profound "uncanny" reaction when presented with stimuli meeting the criteria for a level of "eeriness". In study 1, 395 adults were asked to categorize 200 images as uncanny, neutral, pleasant, or other. In Study 2, physiological and eye-tracking data was collected from twenty two adults as they viewed uncanny, neutral and pleasant images culled from study 1. This research identifies components of the uncanny valley related to subjective assessment, personality factors (using the HEXACO and Anthropomorphic Tendencies Scale), and biophysical measures, and found that traits unique to Emotionality on the HEXACO inventory, compounded with a form of anthropomorphism demonstrates a level of relationship to the subjective experience of uncanny stimuli. There is evidence that HEXACO type and forms of anthropomorphic perception mediates the biophysical iv expression and the subjective perception of the stimuli. In keeping with psychological hypotheses, stimuli to which the participants had greatest response centered on death, the threat of death, or mismatched/absent facial features.

For effective Human-Robot Interactions, robots have to achieve the same level of understanding as humans in every aspect. Humans are highly versatile, able to switch between frames of reference and consider multiple perspectives efficiently. Additionally, humans help and care for each other in the hope of contributing to a better society. When we talk about interacting with robots, the uncertainty around how to collaborate with them has become an emerging topic in the past few years. To bring social robots into humans’ lives, researchers need to understand the conditions and implications of robots’ actions on human responses and perceptions of robots. This project aims at understanding the link between a robot taking a human’s perspective and the human’s exhibition of prosocial behaviour toward the robot. To test our hypotheses, we have designed an activity where the participant picks an object from an array of objects in front of them, after listening to the robot’s descriptions of that object. Divided into three between-subject conditions, the robot took different perspectives to address the objects in each condition. After completing the tasks, participants could either help the robot collect speech data or move on with filling the final questionnaire and finishing the experiment. Our findings show that the participants were significantly more likely to help the robot when the robot took their perspective (human-centred) compared to both the control condition (object-centred) and when the robot did not take their perspective (robot-centred). Additionally, the results show that when the robot’s descriptions of an object were ambiguous, in the first instruction, 96% of the participants perceived the robot’s first instruction using an egocentric perspective. However, when the robot made such ambiguous instructions again later, participants perceived the instructions based on the mental model developed about the robot for that condition. / Robotar måste, i alla avseenden, uppnå samma nivå av förståelse som människor, i syfte till att skapa ett effektivt samspel. Människor är versatila, kan växla mellan olika referensramar och beakta flera perspektiv på ett effektivt sätt. Dessutom hjälper dem och även tar hand om varandra i hopp om att bidra till ett bättre samhälle. När man talar om att interagera med robotar har osäkerheten kring samarbetet blivit ett framväxande ämne under de senaste åren. För att få in sociala robotar i människors liv måste forskarna förstå förutsättningar för och konsekvenser av robotars handlingar gentemot människors reaktioner och uppfattningar om dem. Detta projekt syftar därför till att förstå kopplingen mellan en robot som intar en människas perspektiv samt människans uppvisande av prosocialt beteende gentemot roboten. För att testa hypotesen har en aktivitet designats där en robot ger instruktioner till en deltagare att välja ett visst föremål som den beskriver, utifrån en rad med olika objekt. Med tanke på att deltagarna endast tilldelas ett villkor av tre möjliga, tog roboten olika perspektiv för att adressera objektet i varje betingelse. Efter den slutförda uppgiften kunde deltagarna antingen hjälpa roboten att samla in tal-data eller gå vidare med att fylla i ett sista frågeformulär och avsluta experimentet. Resultatet visar på att deltagarna var mer benägna att hjälpa roboten när den tog deras perspektiv (människokoncentrerad) i jämförelse med både kontrollvillkoren (objektcentrerad) och när roboten inte tog deras perspektiv (robotcentrerad). Dessutom visar även resultatet att robotens beskrivning av ett objekt var tvetydliga. I den första instruktionen upplevde 96% av deltagarna att robotens instruktion hade ett egocentriskt perspektiv. När roboten gjorde ytterligare sådana tvetydliga instruktioner, När roboten gjorde ytterligare sådana tvetydliga instruktioner, uppfattades instruktionerna däremot utifrån den mentala modellen som utvecklades om roboten för just det villkoret.

In der vorliegenden Arbeit wird eine Vorgehensweise entwickelt, um Verbesserungspotentiale in produzierenden kleinen und mittelständischen Unternehmen (KMU) durch den Einsatz von Mensch-Roboter-Kooperation (MRK) zu identifizieren. Die Herausforderung in der Anwendung besteht dabei in der Entwicklung von objektiven Bewertungsverfahren, um die Auswirkungen möglicher Realisierungsvarianten ökonomisch, sozial, ökologisch und technisch-technologisch zu beurteilen. Bislang gibt es nur unzureichende Ansätze, um Potentiale der neuen Technologie ganzheitlich zu bewerten. Da sich KMU durch eine hohe Bedeutung des operativen Geschäftes auszeichnen, wird ein flexibler Ansatz benötigt, der an die jeweilige Situation des Unternehmens angepasst werden kann. Entsprechend der firmenindividuellen Zielstellung werden geeignete Arbeitsplätze für den Einsatz von MRK identifiziert und deren Potentiale in verschiedenen Realisierungsvarianten bewertet. Die entwickelte Vorgehensweise wird anhand von Fallstudien mit drei produzierenden Unternehmen aus unterschiedlichen Branchen verifiziert und iterativ verbessert.:Bibliografische Beschreibung Zusammenfassung Abstract Vorwort Inhaltsverzeichnis Abbildungsverzeichnis Tabellenverzeichnis Abkürzungsverzeichnis Variablenverzeichnis 1. Einleitung: Motivation und Problemstellung 2. Stand der Wissenschaft und Technik 3. Abgeleitete Forschungsfrage und Zielsetzung der Arbeit 4. Entwicklung Zieldefinition und Metamodell zur Potentialbewertung von MRK 5. Entwicklung flexibler Modelle gemäß Metamodell 6. Verifizierung der entwickelten flexiblen Modelle anhand von Fallstudien 7. Bewertung der Forschungsergebnisse 8. Zusammenfassung 9. Ausblick Quellennachweise Anhang / In the thesis, a methodology is developed to identify improvement potentials in manufacturing small and medium-sized enterprises (SMEs) through the use of human-robot-interaction (HRI). The challenge in the application is the development of objective evaluation criteria to assess the effects of possible implementation variants economically, socially, ecologically and technically-technologically. So far, there are only insufficient approaches to evaluate potentials of the new technology holistically. Since SMEs are characterized by a high importance of the operational business, a flexible approach is needed, which can be adapted to the respective situation of the company. According to the company's individual objectives, suitable workplaces for the use of HRI are identified and their potentials are evaluated in different realization variants. The developed approach will be verified and iteratively improved by means of three case studies with manufacturing companies from different industries.:Bibliografische Beschreibung Zusammenfassung Abstract Vorwort Inhaltsverzeichnis Abbildungsverzeichnis Tabellenverzeichnis Abkürzungsverzeichnis Variablenverzeichnis 1. Einleitung: Motivation und Problemstellung 2. Stand der Wissenschaft und Technik 3. Abgeleitete Forschungsfrage und Zielsetzung der Arbeit 4. Entwicklung Zieldefinition und Metamodell zur Potentialbewertung von MRK 5. Entwicklung flexibler Modelle gemäß Metamodell 6. Verifizierung der entwickelten flexiblen Modelle anhand von Fallstudien 7. Bewertung der Forschungsergebnisse 8. Zusammenfassung 9. Ausblick Quellennachweise Anhang

The fast technology development for military unmanned ground vehicles (UGVs) has led to a considerable demand to explore the soldier’s role in an interactive UGV system. This thesis explores how to design interactive systems for UGVs for infantry soldiers in the Swedish Armed Force. This was done through a user-centered design approach in three steps; (1) identifying the design drivers of the targeted military context through qualitative observations and user interviews, (2) using the design drivers to investigate concepts for controlling the UGV, and (3) create and evaluate a prototype of an interactive UGV system design. Results from interviews indicated that design drivers depend on the physical and psychological context of the intended soldiers. In addition, exploring the different concepts showed that early conceptual designs helped the user express their needs of a non-existing system. Furthermore, the results indicate that an interactive UGV system does not necessarily need to be at the highest level of autonomy in order to be useful for the soldiers on the field. The final prototype of an interactive UGV system was evaluated using a demonstration video, a Technology Acceptance Model (TAM), and semi-structured user interviews. Results from this evaluation suggested that the soldiers see the potential usefulness of an interactive UGV system but are not entirely convinced. In conclusion, this thesis argues that in order to design an interactive UGV system, the most critical aspect is the soldiers’ acceptance of the new system. Moreover, for soldiers to accept the concept of military UGVs, it is necessary to understand the context of use and the needs of the soldiers. This is done by involving the soldiers already in the conceptual design process and then throughout the development phases.