A contribution to the incorporation of sociability and creativity skills to computers and robots

This dissertation contains the research and work completed by the PhD candidate on the incorporation of sociability and creativity skills to computers and robots. Both skills can be directly related with empathy, which is the ability to understand and share the feelings of another. In this form, this research can be contextualized in the framework of recent developments towards the achievement of empathy machines. The first challenge at hands refers to designing pioneering techniques based on the use of social robots to improve user experience interacting with them. In particular, research focus is on eliminating or minimizing pain and anxiety as well as loneliness and stress of long-term hospitalized child patients. This challenge is approached by developing a cloud-based robotics architecture to effectively develop complex tasks related to hospitalized children assistance. More specifically, a multiagent learning system is introduced based on a combination of machine learning and cloud computing using low-cost robots (Innvo labs's Pleo rb). Moreover, a wireless communication system is also developed for the Pleo robot in order to help the health professional who conducts therapy with the child, monitoring, understanding, and controlling Pleo behavior at any moment. As a second challenge, a new formulation of the concept of creativity is proposed in order to empower computers with. Based on previous well established theories from Boden and Wiggins, this thesis redefines the formal mechanism of exploratory and transformational creativity in a way which facilitates the computational implementation of these mechanisms in Creativity Support Systems. The proposed formalization is applied and validated on two real cases: the first, about chocolate designing, in which a novel and flavorful combination of chocolate and fruit is generated. The second case is about the composition of a single voice tune of reel using ABC notation

A contribution to the incorporation of sociability and creativity skills to computers and robots

This dissertation contains the research and work completed by the PhD candidate on the incorporation of sociability and creativity skills to computers and robots. Both skills can be directly related with empathy, which is the ability to understand and share the feelings of another. In this form, this research can be contextualized in the framework of recent developments towards the achievement of empathy machines. The first challenge at hands refers to designing pioneering techniques based on the use of social robots to improve user experience interacting with them. In particular, research focus is on eliminating or minimizing pain and anxiety as well as loneliness and stress of long-term hospitalized child patients. This challenge is approached by developing a cloud-based robotics architecture to effectively develop complex tasks related to hospitalized children assistance. More specifically, a multiagent learning system is introduced based on a combination of machine learning and cloud computing using low-cost robots (Innvo labs's Pleo rb). Moreover, a wireless communication system is also developed for the Pleo robot in order to help the health professional who conducts therapy with the child, monitoring, understanding, and controlling Pleo behavior at any moment. As a second challenge, a new formulation of the concept of creativity is proposed in order to empower computers with. Based on previous well established theories from Boden and Wiggins, this thesis redefines the formal mechanism of exploratory and transformational creativity in a way which facilitates the computational implementation of these mechanisms in Creativity Support Systems. The proposed formalization is applied and validated on two real cases: the first, about chocolate designing, in which a novel and flavorful combination of chocolate and fruit is generated. The second case is about the composition of a single voice tune of reel using ABC notation.Postprint (published version

Developing Kaspar: a humanoid robot for children with Autism

In the late 1990s using robotic technology to assist children with Autistic Spectrum Condition (ASD) emerged as a potentially useful area of research. Since then the field of assistive robotics for children with ASD has grown considerably with many academics trialling different robots and approaches. One such robot is the humanoid robot Kaspar that was originally developed in 2005 and has continually been built upon since, taking advantage of technological developments along the way. A key principle in the development of Kaspar since its creation has been to ensure that all of the advances to the platform are driven by the requirements of the users. In this paper we discuss the development of Kaspar’s design and explain the rationale behind each change to the platform. Designing and building a humanoid robot to interact with and help children with ASD is a multidisciplinary challenge that requires knowledge of the mechanical engineering, electrical engineering, Human–Computer Interaction (HCI), Child–Robot Interaction (CRI) and knowledge of ASD. The Kaspar robot has benefited from the wealth of knowledge accrued over years of experience in robot-assisted therapy for children with ASD. By showing the journey of how the Kaspar robot has developed we aim to assist others in the field develop such technologies further

Information and communication technologies-based interventions for children with autism spectrum conditions: a systematic review of randomized control trials from a positive technology perspective

Information and communication technologies (ICTs) have become more widely used in the past years to help people with autism spectrum conditions (ASC). Serious games embedded into computers or tablets, as well as social robots, are the most employed ICT-related tools that are appealing to and appropriate for autistic children. The goal of ICT applications is to enhance behavioral abnormalities associated with ASC while also creating an interactive link between one person and one computer. Comparatively, to human-based therapy, ICT tools aid to inspire autistic children by providing predictability and regularity of tasks. Regaining social skills is the primary behavioral goal for which ICT tools have been designed and implemented. In the past several years, many studies have been created to show how effective it is at improving targeted behaviors. However, only a small number of researchers have used an RCT approach to evaluate its effectiveness. In this systematic review, we only included RCT studies where ICT technologies were used to help children with ASC in improving their social skills. Only 14 RCT studies satisfied the criteria and 12 described significant improvements, showing how the use of technology in educational contexts produced better improvement in developing several social skill facets with respect to the traditional face-to-face approach. Some studies used interventions and outcome measures focused on the core ASC symptoms, but many others addressed neurocognitive functions directly, like social cognition or emotional regulation, while other more general functions such as language or adaptive behaviors. We propose a classification based on processes and outcome measures to foster future research in this specific area of research. The behavioral intervention mediated by technological tools such as computer-based, tablet, and social robotics, undoubtedly provides a comfortable environment that promotes constant learning for people with ASC. Evidence provided in this review highlights the translational potential of this field of study in primary care practice and educational settings

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

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

Designing companions, designing tools : social robots, developers, and the elderly in Japan

Ce mémoire de maîtrise trace la généalogie d’un robot social, de sa conception à ses différentes utilisations et la manière dont les utilisateurs interagissent avec. A partir d’un terrain de six mois dans une start-up et deux maisons de retraite au Japon, j’interroge la création de Pepper, un robot social crée par la compagnie japonais SoftBank. Pepper a été créé de façon à être humanoïde mais pas trop, ainsi que perçu comme adorable et charmant. Par la suite, je décris comment Pepper et d’autres robots sociaux sont utilisés, à la fois par des développeurs, mais aussi par des personnes âgées, et je souligne une tension existante entre leur utilisation comme des compagnons et des outils. En me basant sur l’anthropologie ontologique et la phénoménologie, j’examine la construction du robot comme une entité avec laquelle il est possible d’interagir, notamment à cause de sa conception en tant qu’acteur social, ontologiquement ambigu, et qui peut exprimer de l’affect. En m’intéressant aux interactions multimodales, et en particulier le toucher, je classifie trois fonctions remplies par l’interaction : découverte, contrôle, et l’expression de l’affect. Par la suite, je questionne ces actes d’agir vers et s’ils peuvent être compris comme une interaction, puisqu’ils n’impliquent pas que le robot soit engagé. J’argumente qu’une interaction est un échange de sens entre des agents engagés et incarnés. Il y a effectivement parfois un échange de sens entre le robot et son utilisateur, et le robot est un artefact incarné. Cependant, seule l’impression d’intersubjectivité est nécessaire à l’interaction, plutôt que sa réelle présence.This master’s thesis traces a genealogy of a social robot through its conception to its various uses and the ways users interact with it. Drawing on six months of fieldwork in a start-up and two nursing homes in Japan, I first investigate the genesis of a social robot created by SoftBank, a Japanese multinational telecommunications company. This social robot is quite humanlike, made to be cute and have an adorable personality. While developers constitute one of the user populations, this robot, along with several others, is also used by elderly residents in nursing homes. By analyzing the uses of these populations, I underline the tension between the social robot as a companion and a tool. Drawing on ontological anthropology and phenomenology I look at how the robot is constructed as an entity that can be interacted with, through its conception as an ontologically ambiguous, social actor, that can express affect. Looking at multimodal interaction, and especially touch, I then classify three functions they fulfill: discovery, control, and the expression of affect, before questioning whether this acting towards the robot that does not imply acting from the robot, can be considered a form of interaction. I argue that interaction is the exchange of meaning between embodied, engaged participants. Meaning can be exchanged between robots and humans and the robot can be seen as embodied, but only the appearance of intersubjectivity is enough, rather than its actual presence

Investigating Human Perceptions of Trust and Social Cues in Robots for Safe Human-Robot Interaction in Human-oriented Environments

As robots increasingly take part in daily living activities, humans will have to interact with them in domestic and other human-oriented environments. This thesis envisages a future where autonomous robots could be used as home companions to assist and collaborate with their human partners in unstructured environments without the support of any roboticist or expert. To realise such a vision, it is important to identify which factors (e.g. trust, participants’ personalities and background etc.) that influence people to accept robots’ as companions and trust the robots to look after their well-being. I am particularly interested in the possibility of robots using social behaviours and natural communications as a repair mechanism to positively influence humans’ sense of trust and companionship towards the robots. The main reason being that trust can change over time due to different factors (e.g. perceived erroneous robot behaviours). In this thesis, I provide guidelines for a robot to regain human trust by adopting certain human-like behaviours. I can expect that domestic robots will exhibit occasional mechanical, programming or functional errors, as occurs with any other electrical consumer devices. For example, these might include software errors, dropping objects due to gripper malfunctions, picking up the wrong object or showing faulty navigational skills due to unclear camera images or noisy laser scanner data respectively. It is therefore important for a domestic robot to have acceptable interactive behaviour when exhibiting and recovering from an error situation. In this context, several open questions need to be addressed regarding both individuals’ perceptions of the errors and robots, and the effects of these on people’s trust in robots. As a first step, I investigated how the severity of the consequences and the timing of a robot’s different types of erroneous behaviours during an interaction may have different impact on users’ attitudes towards a domestic robot. I concluded that there is a correlation between the magnitude of an error performed by the robot and the corresponding loss of trust of the human in the robot. In particular, people’s trust was strongly affected by robot errors that had severe consequences. This led us to investigate whether people’s awareness of robots’ functionalities may affect their trust in a robot. I found that people’s acceptance and trust in the robot may be affected by their knowledge of the robot’s capabilities and its limitations differently according the participants’ age and the robot’s embodiment. In order to deploy robots in the wild, strategies for mitigating and re-gaining people’s trust in robots in case of errors needs to be implemented. In the following three studies, I assessed if a robot with awareness of human social conventions would increase people’s trust in the robot. My findings showed that people almost blindly trusted a social and a non-social robot in scenarios with non-severe error consequences. In contrast, people that interacted with a social robot did not trust its suggestions in a scenario with a higher risk outcome. Finally, I investigated the effects of robots’ errors on people’s trust of a robot over time. The findings showed that participants’ judgement of a robot is formed during the first stage of their interaction. Therefore, people are more inclined to lose trust in a robot if it makes big errors at the beginning of the interaction. The findings from the Human-Robot Interaction experiments presented in this thesis will contribute to an advanced understanding of the trust dynamics between humans and robots for a long-lasting and successful collaboration