Towards dialogic epistemology: the problem of the text

This article considers epistemological implications of Bakhtin’s dialogism. Bakhtin urged scholars in the human sciences to treat a text as having a voice of its own, to be attuned to its creativity and originality, and to resist conflating one’s image of the author with the actual person who has produced the text. Importing his ideas into the social sciences creates a site of tensions at the disciplines’ boundaries. Yet his characterisation of dialogue applies also to qualitative researchers’ interactions with nonfiction material. Bakhtin contended that a text as an utterance is a unique unrepeatable event; and that a voice is immanent in how the text itself operates: its placement in a dialogical sequence (answerability), its plan (purpose) and the realisation of the plan. Attention to these dynamics could constitute a formative step in the epistemic process of qualitative research, as concrete examples illustrate. A concept of a ‘dialogic triangle’ (utterance, response and their interrelation) is proposed

A Study of Non-Linguistic Utterances for Social Human-Robot Interaction

The world of animation has painted an inspiring image of what the robots of the future could be. Taking the robots R2D2 and C3PO from the Star Wars films as representative examples, these robots are portrayed as being more than just machines, rather, they are presented as intelligent and capable social peers, exhibiting many of the traits that people have also. These robots have the ability to interact with people, understand us, and even relate to us in very personal ways through a wide repertoire of social cues. As robotic technologies continue to make their way into society at large, there is a growing trend toward making social robots. The field of Human-Robot Interaction concerns itself with studying, developing and realising these socially capable machines, equipping them with a very rich variety of capabilities that allow them to interact with people in natural and intuitive ways, ranging from the use of natural language, body language and facial gestures, to more unique ways such as expression through colours and abstract sounds. This thesis studies the use of abstract, expressive sounds, like those used iconically by the robot R2D2. These are termed Non-Linguistic Utterances (NLUs) and are a means of communication which has a rich history in film and animation. However, very little is understood about how such expressive sounds may be utilised by social robots, and how people respond to these. This work presents a series of experiments aimed at understanding how NLUs can be utilised by a social robot in order to convey affective meaning to people both young and old, and what factors impact on the production and perception of NLUs. Firstly, it is shown that not all robots should use NLUs. The morphology of the robot matters. People perceive NLUs differently across different robots, and not always in a desired manner. Next it is shown that people readily project affective meaning onto NLUs though not in a coherent manner. Furthermore, people's affective inferences are not subtle, rather they are drawn to well established, basic affect prototypes. Moreover, it is shown that the valence of the situation in which an NLU is made, overrides the initial valence of the NLU itself: situational context biases how people perceive utterances made by a robot, and through this, coherence between people in their affective inferences is found to increase. Finally, it is uncovered that NLUs are best not used as a replacement to natural language (as they are by R2D2), rather, people show a preference for them being used alongside natural language where they can play a supportive role by providing essential social cues

Sequence-learning in a self-referential closed-loop behavioural system

This thesis focuses on the problem of "autonomous agents". It is assumed that such agents want to be in a desired state which can be assessed by the agent itself when it observes the consequences of its own actions. Therefore the feedback from the motor output via the environment to the sensor input is an essential component of such a system. As a consequence an agent is defined in this thesis as a self-referential system which operates within a closed sensor- mot or-sensor feedback loop. The generic situation is that the agent is always prone to unpredictable disturbances which arrive from the outside, i.e. from its environment. These disturbances cause a deviation from the desired state (for example the organism is attacked unexpectedly or the temperature in the environment changes, ...). The simplest mechanism for managing such disturbances in an organism is to employ a reflex loop which essentially establishes reactive behaviour. Reflex loops are directly related to closed loop feedback controllers. Thus, they are robust and they do not need a built-in model of the control situation. However, reflexes have one main disadvantage, namely that they always occur "too late"; i.e., only after a (for example, unpleasant) reflex eliciting sensor event has occurred. This defines an objective problem for the organism. This thesis provides a solution to this problem which is called Isotropic Sequence Order (ISO-) learning. The problem is solved by correlating the primary reflex and a predictive sensor input: the result is that the system learns the temporal relation between the primary reflex and the earlier sensor input and creates a new predictive reflex. This (new) predictive reflex does not have the disadvantage of the primary reflex, namely of always being too late. As a consequence the agent is able to maintain its desired input-state all the time. In terms of engineering this means that ISO learning solves the inverse controller problem for the reflex, which is mathematically proven in this thesis. Summarising, this means that the organism starts as a reactive system and learning turns the system into a pro-active system. It will be demonstrated by a real robot experiment that ISO learning can successfully learn to solve the classical obstacle avoidance task without external intervention (like rewards). In this experiment the robot has to correlate a reflex (retraction after collision) with signals of range finders (turn before the collision). After successful learning the robot generates a turning reaction before it bumps into an obstacle. Additionally it will be shown that the learning goal of "reflex avoidance" can also, paradoxically, be used to solve an attraction task

Robotics in Germany and Japan

This book comprehends an intercultural and interdisciplinary framework including current research fields like Roboethics, Hermeneutics of Technologies, Technology Assessment, Robotics in Japanese Popular Culture and Music Robots. Contributions on cultural interrelations, technical visions and essays are rounding out the content of this book

Biologically inspired computational structures and processes for autonomous agents and robots

Recent years have seen a proliferation of intelligent agent applications: from robots for space exploration to software agents for information filtering and electronic commerce on the Internet. Although the scope of these agent applications have blossomed tremendously since the advent of compact, affordable computing (and the recent emergence of the World Wide Web), the design of such agents for specific applications remains a daunting engineering problem;Rather than approach the design of artificial agents from a purely engineering standpoint, this dissertation views animals as biological agents, and considers artificial analogs of biological structures and processes in the design of effective agent behaviors. In particular, it explores behaviors generated by artificial neural structures appropriately shaped by the processes of evolution and spatial learning;The first part of this dissertation deals with the evolution of artificial neural controllers for a box-pushing robot task. We show that evolution discovers high fitness structures using little domain-specific knowledge, even in feedback-impoverished environments. Through a careful analysis of the evolved designs we also show how evolution exploits the environmental constraints and properties to produce designs of superior adaptive value. By modifying the task constraints in controlled ways, we also show the ability of evolution to quickly adapt to these changes and exploit them to obtain significant performance gains. We also use evolution to design the sensory systems of the box-pushing robots, particularly the number, placement, and ranges of their sensors. We find that evolution automatically discards unnecessary sensors retaining only the ones that appear to significantly affect the performance of the robot. This optimization of design across multiple dimensions (performance, number of sensors, size of neural controller, etc.) is implicitly achieved by the evolutionary algorithm without any external pressure (e.g., penalty on the use of more sensors or neurocontroller units). When used in the design of robots with limited battery capacities , evolution produces energy-efficient robot designs that use minimal numbers of components and yet perform reasonably well. The performance as well as the complexity of robot designs increase when the robots have access to a spatial learning mechanism that allows them to learn, remember, and navigate to power sources in the environment;The second part of this dissertation develops a computational characterization of the hippocampal formation which is known to play a significant role in animal spatial learning. The model is based on neuroscientific and behavioral data, and learns place maps based on interactions of sensory and dead-reckoning information streams. Using an estimation mechanism known as Kalman filtering, the model explicitly deals with uncertainties in the two information streams, allowing the robot to effectively learn and localize even in the presence sensing and motion errors. Additionally, the model has mechanisms to handle perceptual aliasing problems (where multiple places in the environment appear sensorily identical), incrementally learn and integrate local place maps, and learn and remember multiple goal locations in the environment. We show a number of properties of this spatial learning model including computational replication of several behavioral experiments performed with rodents. Not only does this model make significant contributions to robot localization, but also offers a number of predictions and suggestions that can be validated (or refuted) through systematic neurobiological and behavioral experiments with animals

Distributed Control for Collective Behaviour in Micro-unmanned Aerial Vehicles

Full version unavailable due to 3rd party copyright restrictions.The work presented herein focuses on the design of distributed autonomous controllers for collective behaviour of Micro-unmanned Aerial Vehicles (MAVs). Two alternative approaches to this topic are introduced: one based upon the Evolutionary Robotics (ER) paradigm, the other one upon flocking principles. Three computer simulators have been developed in order to carry out the required experiments, all of them having their focus on the modelling of fixed-wing aircraft flight dynamics. The employment of fixed-wing aircraft rather than the omni-directional robots typically employed in collective robotics significantly increases the complexity of the challenges that an autonomous controller has to face. This is mostly due to the strict motion constraints associated with fixed-wing platforms, that require a high degree of accuracy by the controller. Concerning the ER approach, the experimental setups elaborated have resulted in controllers that have been evolved in simulation with the following capabilities: (1) navigation across unknown environments, (2) obstacle avoidance, (3) tracking of a moving target, and (4) execution of cooperative and coordinated behaviours based on implicit communication strategies. The design methodology based upon flocking principles has involved tests on computer simulations and subsequent experimentation on real-world robotic platforms. A customised implementation of Reynolds’ flocking algorithm has been developed and successfully validated through flight tests performed with the swinglet MAV. It has been notably demonstrated how the Evolutionary Robotics approach could be successfully extended to the domain of fixed-wing aerial robotics, which has never received a great deal of attention in the past. The investigations performed have also shown that complex and real physics-based computer simulators are not a compulsory requirement when approaching the domain of aerial robotics, as long as proper autopilot systems (taking care of the ”reality gap” issue) are used on the real robots.EOARD (European Office of Aerospace Research & Development), euCognitio

Animating the Ethical Demand:Exploring user dispositions in industry innovation cases through animation-based sketching

This paper addresses the challenge of attaining ethical user stances during the design process of products and services and proposes animation-based sketching as a design method, which supports elaborating and examining different ethical stances towards the user. The discussion is qualified by an empirical study of Responsible Research and Innovation (RRI) in a Triple Helix constellation. Using a three-week long innovation workshop, UCrAc, involving 16 Danish companies and organisations and 142 students as empirical data, we discuss how animation-based sketching can explore not yet existing user dispositions, as well as create an incentive for ethical conduct in development and innovation processes. The ethical fulcrum evolves around Løgstrup's Ethical Demand and his notion of spontaneous life manifestations. From this, three ethical stances are developed; apathy, sympathy and empathy. By exploring both apathetic and sympathetic views, the ethical reflections are more nuanced as a result of actually seeing the user experience simulated through different user dispositions. Exploring the three ethical stances by visualising real use cases with the technologies simulated as already being implemented makes the life manifestations of the users in context visible. We present and discuss how animation-based sketching can support the elaboration and examination of different ethical stances towards the user in the product and service development process. Finally we present a framework for creating narrative representations of emerging technology use cases, which invite to reflection upon the ethics of the user experience.</jats:p

Social Robotics and the Good Life: The Normative Side of Forming Emotional Bonds With Robots

Robots as social companions in close proximity to humans have a strong potential of becoming more and more prevalent in the coming years, especially in the realms of elder day care, child rearing, and education. As human beings, we have the fascinating ability to emotionally bond with various counterparts, not exclusively with other human beings, but also with animals, plants, and sometimes even objects. Therefore, we need to answer the fundamental ethical questions that concern human-robot-interactions per se, and we need to address how we conceive of "good lives", as more and more of the aspects of our daily lives will be interwoven with social robots

Almost Like Being There: Embodiment, Social Presence, and Engagement Using Telepresence Robots in Blended Courses

As students’ online learning opportunities continue to increase in higher education, students are choosing not to come back to campus in-person for a variety of personal, health, safety, and financial reasons. The growing use of video conferencing technology during the COVID-19 pandemic allowed classes to continue, but students reported a sense of disconnectedness and lack of engagement with their classes. Telepresence robots may be an alternative to video conferencing that can provide learning experiences closer to the in-person experience, which also provides a stronger sense of embodiment, social presence, and engagement in the classroom. This study explored the use of telepresence robots in four undergraduate, humanities, blended learning courses. Sixty-nine students, 43 in-person and 26 remote students, were surveyed using the Telepresence and Engagement Measurement Scale (TEMS) and provided written feedback about their experience. The TEMS measured embodiment, social presence, psychological involvement, and three indicators of engagement: behavioral, affective, and cognitive. Embodiment and social presence were positively correlated as were embodiment and behavioral engagement. There was no significant difference between the two groups’ perceptions of social presence but there was a significant difference between groups’ perceptions of engagement. Qualitative data and effect sizes greater than 0.80 supported the reliability and validity of the TEMS instrument as a measurement instrument for future study of blended learning environments using remote tools such as telepresence robots. Provided that technological issues such as connectivity and audio and video quality are addressed, telepresence robots can be a useful tool to help students feel more embodied and socially present in today’s blended learning classrooms