Accessible Integration of Physiological Adaptation in Human-Robot Interaction

Technological advancements in creating and commercializing novel unobtrusive wearable physiological sensors have generated new opportunities to develop adaptive human-robot interaction (HRI). Detecting complex human states such as engagement and stress when interacting with social agents could bring numerous advantages to creating meaningful interactive experiences. Bodily signals have classically been used for post-interaction analysis in HRI. Despite this, real-time measurements of autonomic responses have been used in other research domains to develop physiologically adaptive systems with great success; increasing user-experience, task performance, and reducing cognitive workload. This thesis presents the HRI Physio Lib, a conceptual framework, and open-source software library to facilitate the development of physiologically adaptive HRI scenarios. Both the framework and architecture of the library are described in-depth, along with descriptions of additional software tools that were developed to make the inclusion of physiological signals easier for robotics frameworks. The framework is structured around four main components for designing physiologically adaptive experimental scenarios: signal acquisition, processing and analysis; social robot and communication; and scenario and adaptation. Open-source software tools have been developed to assist in the individual creation of each described component. To showcase our framework and test the software library, we developed, as a proof-of-concept, a simple scenario revolving around a physiologically aware exercise coach, that modulates the speed and intensity of the activity to promote an effective cardiorespiratory exercise. We employed the socially assistive QT robot for our exercise scenario, as it provides a comprehensive ROS interface, making prototyping of behavioral responses fast and simple. Our exercise routine was designed following guidelines by the American College of Sports Medicine. We describe our physiologically adaptive algorithm and propose an alternative second one with stochastic elements. Finally, a discussion about other HRI domains where the addition of a physiologically adaptive mechanism could result in novel advances in interaction quality is provided as future extensions for this work. From the literature, we identified improving engagement, providing deeper social connections, health care scenarios, and also applications for self-driving vehicles as promising avenues for future research where a physiologically adaptive social robot could improve user experience

An ambient agent model for reading companion robot

Reading is essentially a problem-solving task. Based on what is read, like problem solving, it requires effort, planning, self-monitoring, strategy selection, and reflection. Also, as readers are trying to solve difficult problems, reading materials become more complex, thus demands more effort and challenges cognition. To address this issue, companion robots can be deployed to assist readers in solving difficult reading tasks by making reading process more enjoyable and meaningful. These robots require an ambient agent model, monitoring of a reader’s cognitive demand as it could consist of more complex tasks and dynamic interactions between human and environment. Current cognitive load models are not developed in a form to have reasoning qualities and not integrated into companion robots. Thus, this study has been conducted to develop an ambient agent model of cognitive load and reading performance to be integrated into a reading companion robot. The research activities were based on Design Science Research Process, Agent-Based Modelling, and Ambient Agent Framework. The proposed model was evaluated through a series of verification and validation approaches. The verification process includes equilibria evaluation and automated trace analysis approaches to ensure the model exhibits realistic behaviours and in accordance to related empirical data and literature. On the other hand, validation process that involved human experiment proved that a reading companion robot was able to reduce cognitive load during demanding reading tasks. Moreover, experiments results indicated that the integration of an ambient agent model into a reading companion robot enabled the robot to be perceived as a social, intelligent, useful, and motivational digital side-kick. The study contribution makes it feasible for new endeavours that aim at designing ambient applications based on human’s physical and cognitive process as an ambient agent model of cognitive load and reading performance was developed. Furthermore, it also helps in designing more realistic reading companion robots in the future

Autonomous Decision-Making based on Biological Adaptive Processes for Intelligent Social Robots

Mención Internacional en el título de doctorThe unceasing development of autonomous robots in many different scenarios drives a new revolution to improve our quality of life. Recent advances in human-robot interaction and machine learning extend robots to social scenarios, where these systems pretend to assist humans in diverse tasks. Thus, social robots are nowadays becoming real in many applications like education, healthcare, entertainment, or assistance. Complex environments demand that social robots present adaptive mechanisms to overcome different situations and successfully execute their tasks. Thus, considering the previous ideas, making autonomous and appropriate decisions is essential to exhibit reasonable behaviour and operate well in dynamic scenarios. Decision-making systems provide artificial agents with the capacity of making decisions about how to behave depending on input information from the environment. In the last decades, human decision-making has served researchers as an inspiration to endow robots with similar deliberation. Especially in social robotics, where people expect to interact with machines with human-like capabilities, biologically inspired decisionmaking systems have demonstrated great potential and interest. Thereby, it is expected that these systems will continue providing a solid biological background and improve the naturalness of the human-robot interaction, usability, and the acceptance of social robots in the following years. This thesis presents a decision-making system for social robots acting in healthcare, entertainment, and assistance with autonomous behaviour. The system’s goal is to provide robots with natural and fluid human-robot interaction during the realisation of their tasks. The decision-making system integrates into an already existing software architecture with different modules that manage human-robot interaction, perception, or expressiveness. Inside this architecture, the decision-making system decides which behaviour the robot has to execute after evaluating information received from different modules in the architecture. These modules provide structured data about planned activities, perceptions, and artificial biological processes that evolve with time that are the basis for natural behaviour. The natural behaviour of the robot comes from the evolution of biological variables that emulate biological processes occurring in humans. We also propose a Motivational model, a module that emulates biological processes in humans for generating an artificial physiological and psychological state that influences the robot’s decision-making. These processes emulate the natural biological rhythms of the human organism to produce biologically inspired decisions that improve the naturalness exhibited by the robot during human-robot interactions. The robot’s decisions also depend on what the robot perceives from the environment, planned events listed in the robot’s agenda, and the unique features of the user interacting with the robot. The robot’s decisions depend on many internal and external factors that influence how the robot behaves. Users are the most critical stimuli the robot perceives since they are the cornerstone of interaction. Social robots have to focus on assisting people in their daily tasks, considering that each person has different features and preferences. Thus, a robot devised for social interaction has to adapt its decisions to people that aim at interacting with it. The first step towards adapting to different users is identifying the user it interacts with. Then, it has to gather as much information as possible and personalise the interaction. The information about each user has to be actively updated if necessary since outdated information may lead the user to refuse the robot. Considering these facts, this work tackles the user adaptation in three different ways. • The robot incorporates user profiling methods to continuously gather information from the user using direct and indirect feedback methods. • The robot has a Preference Learning System that predicts and adjusts the user’s preferences to the robot’s activities during the interaction. • An Action-based Learning System grounded on Reinforcement Learning is introduced as the origin of motivated behaviour. The functionalities mentioned above define the inputs received by the decisionmaking system for adapting its behaviour. Our decision-making system has been designed for being integrated into different robotic platforms due to its flexibility and modularity. Finally, we carried out several experiments to evaluate the architecture’s functionalities during real human-robot interaction scenarios. In these experiments, we assessed: • How to endow social robots with adaptive affective mechanisms to overcome interaction limitations. • Active user profiling using face recognition and human-robot interaction. • A Preference Learning System we designed to predict and adapt the user preferences towards the robot’s entertainment activities for adapting the interaction. • A Behaviour-based Reinforcement Learning System that allows the robot to learn the effects of its actions to behave appropriately in each situation. • The biologically inspired robot behaviour using emulated biological processes and how the robot creates social bonds with each user. • The robot’s expressiveness in affect (emotion and mood) and autonomic functions such as heart rate or blinking frequency.Programa de Doctorado en Ingeniería Eléctrica, Electrónica y Automática por la Universidad Carlos III de MadridPresidente: Richard J. Duro Fernández.- Secretaria: Concepción Alicia Monje Micharet.- Vocal: Silvia Ross

Humanoid Robots

For many years, the human being has been trying, in all ways, to recreate the complex mechanisms that form the human body. Such task is extremely complicated and the results are not totally satisfactory. However, with increasing technological advances based on theoretical and experimental researches, man gets, in a way, to copy or to imitate some systems of the human body. These researches not only intended to create humanoid robots, great part of them constituting autonomous systems, but also, in some way, to offer a higher knowledge of the systems that form the human body, objectifying possible applications in the technology of rehabilitation of human beings, gathering in a whole studies related not only to Robotics, but also to Biomechanics, Biomimmetics, Cybernetics, among other areas. This book presents a series of researches inspired by this ideal, carried through by various researchers worldwide, looking for to analyze and to discuss diverse subjects related to humanoid robots. The presented contributions explore aspects about robotic hands, learning, language, vision and locomotion

Robotics 2010

Without a doubt, robotics has made an incredible progress over the last decades. The vision of developing, designing and creating technical systems that help humans to achieve hard and complex tasks, has intelligently led to an incredible variety of solutions. There are barely technical fields that could exhibit more interdisciplinary interconnections like robotics. This fact is generated by highly complex challenges imposed by robotic systems, especially the requirement on intelligent and autonomous operation. This book tries to give an insight into the evolutionary process that takes place in robotics. It provides articles covering a wide range of this exciting area. The progress of technical challenges and concepts may illuminate the relationship between developments that seem to be completely different at first sight. The robotics remains an exciting scientific and engineering field. The community looks optimistically ahead and also looks forward for the future challenges and new development

The Social and Behavioral Influences of Interactions with Virtual Dogs as Embodied Agents in Augmented and Virtual Reality

Intelligent virtual agents (IVAs) have been researched for years and recently many of these IVAs have become commercialized and widely used by many individuals as intelligent personal assistants. The majority of these IVAs are anthropomorphic, and many are developed to resemble real humans entirely. However, real humans do not interact only with other humans in the real world, and many benefit from interactions with non-human entities. A prime example is human interactions with animals, such as dogs. Humans and dogs share a historical bond that goes back thousands of years. In the past 30 years, there has been a great deal of research to understand the effects of human-dog interaction, with research findings pointing towards the physical, mental, and social benefits to humans when interacting with dogs. However, limitations such as allergies, stress on dogs, and hygiene issues restrict some needy individuals from receiving such benefits. More recently, advances in augmented and virtual reality technology provide opportunities for realizing virtual dogs and animals, allowing for their three-dimensional presence in the users\u27 real physical environment or while users are immersed in virtual worlds. In this dissertation, I utilize the findings from human-dog interaction research and conduct a systematic literature review on embodied IVAs to define a research scope to understand virtual dogs\u27 social and behavioral influences in augmented and virtual reality. I present the findings of this systematic literature review that informed the creation of the research scope and four human-subjects studies. Through these user studies, I found that virtual dogs bring about a sense of comfort and companionship for users in different contexts. In addition, their responsiveness plays an important role in enhancing users\u27 quality of experience, and they can be effectively utilized as attention guidance mechanisms and social priming stimuli

Children's perception and interpretation of robots and robot behaviour

The world of robotics, like that of all technology is changing rapidly (Melson, et al., 2009). As part of an inter-disciplinary project investigating the emergence of artificial culture in robot societies, this study set out to examine children’s perception of robots and interpretation of robot behaviour. This thesis is situated in an interdisciplinary field of human–robot interactions, drawing on research from the disciplines of sociology and psychology as well as the fields of engineering and ethics. The study was divided into four phases: phase one involved children from two primary schools drawing a picture and writing a story about their robot. In phase two, children observed e-puck robots interacting. Children were asked questions regarding the function and purpose of the robots’ actions. Phase three entailed data collection at a public event: Manchester Science Festival. Three activities at the festival: ‘XRay Art Under Your Skin’, ‘Swarm Robots’ and ‘Build-a-Bugbot’ formed the focus of this phase. In the first activity, children were asked to draw the components of a robot and were then asked questions about their drawings. During the second exercise, children’s comments were noted as they watched e-puck robot demonstrations. In the third exercise, children were shown images and asked whether these images were a robot or a ‘no-bot’. They were then prompted to provide explanations for their answers. Phase 4 of the research involved children identifying patterns of behaviour amongst e-pucks. This phase of the project was undertaken as a pilot for the ‘open science’ approach to research to be used by the wider project within which this PhD was nested. Consistent with existing literature, children endowed robots with animate and inanimate characteristics holding multiple understandings of robots simultaneously. The notion of control appeared to be important in children’s conception of animacy. The results indicated children’s perceptions of the location of the locus of control plays an important role in whether they view robots as autonomous agents or controllable entities. The ways in which children perceive robots and robot behaviour, in particular the ways in which children give meaning to robots and robot behaviour will potentially come to characterise a particular generation. Therefore, research should not only concentrate on the impact of these technologies on children but should focus on capturing children’s perceptions and viewpoints to better understand the impact of the changing technological world on the lives of children