How does an infant acquire the ability of joint attention?: A Constructive Approach

This study argues how a human infant acquires the ability of joint attention through interactions with its caregiver from the viewpoint of a constructive approach. This paper presents a constructive model by which a robot acquires a sensorimotor coordination for joint attention based on visual attention and learning with self-evaluation. Since visual attention does not always correspond to joint attention, the robot may have incorrect learning situations for joint attention as well as correct ones. However, the robot is expected to statistically lose the data of the incorrect ones as outliers through the learning, and consequently acquires the appropriate sensorimotor coordination for joint attention even if the environment is not controlled nor the caregiver provides any task evaluation. The experimental results suggest that the proposed model could explain the developmental mechanism of the infant’s joint attention because the learning process of the robot’s joint attention can be regarded as equivalent to the developmental process of the infant’s one

Towards a Theory Grounded Theory of Language

In this paper, we build upon the idea of theory grounding and propose one specific form of theory grounding, a theory of language. Theory grounding is the idea that we can imbue our embodied artificially intelligent systems with theories by modeling the way humans, and specifically young children, develop skills with theories. Modeling theory development promises to increase the conceptual and behavioral flexibility of these systems. An example of theory development in children is the social understanding referred to as “theory of mind.” Language is a natural task for theory grounding because it is vital in symbolic skills and apparently necessary in developing theories. Word learning, and specifically developing a concept of words, is proposed as the first step in a theory grounded theory of language

Humanoid Theory Grounding

In this paper we consider the importance of using a humanoid physical form for a certain proposed kind of robotics, that of theory grounding. Theory grounding involves grounding the theory skills and knowledge of an embodied artificially intelligent (AI) system by developing theory skills and knowledge from the bottom up. Theory grounding can potentially occur in a variety of domains, and the particular domain considered here is that of language. Language is taken to be another “problem space” in which a system can explore and discover solutions. We argue that because theory grounding necessitates robots experiencing domain information, certain behavioral-form aspects, such as abilities to socially smile, point, follow gaze, and generate manual gestures, are necessary for robots grounding a humanoid theory of language

Ongoing Emergence: A Core Concept in Epigenetic Robotics

We propose ongoing emergence as a core concept in epigenetic robotics. Ongoing emergence refers to the continuous development and integration of new skills and is exhibited when six criteria are satisfied: (1) continuous skill acquisition, (2) incorporation of new skills with existing skills, (3) autonomous development of values and goals, (4) bootstrapping of initial skills, (5) stability of skills, and (6) reproducibility. In this paper we: (a) provide a conceptual synthesis of ongoing emergence based on previous theorizing, (b) review current research in epigenetic robotics in light of ongoing emergence, (c) provide prototypical examples of ongoing emergence from infant development, and (d) outline computational issues relevant to creating robots exhibiting ongoing emergence

A Study of three Interfaces allowing Non-expert Users to Teach New Visual Objects to a Robot and their Impact on Learning Efficiency

International audienceWe developed three interfaces to allow non-expert users to teach name for new visual objects and compare them through user's studies in term of learning efficiency

Dynamic Facial Expression of Emotion Made Easy

Facial emotion expression for virtual characters is used in a wide variety of areas. Often, the primary reason to use emotion expression is not to study emotion expression generation per se, but to use emotion expression in an application or research project. What is then needed is an easy to use and flexible, but also validated mechanism to do so. In this report we present such a mechanism. It enables developers to build virtual characters with dynamic affective facial expressions. The mechanism is based on Facial Action Coding. It is easy to implement, and code is available for download. To show the validity of the expressions generated with the mechanism we tested the recognition accuracy for 6 basic emotions (joy, anger, sadness, surprise, disgust, fear) and 4 blend emotions (enthusiastic, furious, frustrated, and evil). Additionally we investigated the effect of VC distance (z-coordinate), the effect of the VC's face morphology (male vs. female), the effect of a lateral versus a frontal presentation of the expression, and the effect of intensity of the expression. Participants (n=19, Western and Asian subjects) rated the intensity of each expression for each condition (within subject setup) in a non forced choice manner. All of the basic emotions were uniquely perceived as such. Further, the blends and confusion details of basic emotions are compatible with findings in psychology

Emerging Linguistic Functions in Early Infancy

This paper presents results from experimental studies on early language acquisition in infants and attempts to interpret the experimental results within the framework of the Ecological Theory of Language Acquisition (ETLA) recently proposed by (Lacerda et al., 2004a). From this perspective, the infant’s first steps in the acquisition of the ambient language are seen as a consequence of the infant’s general capacity to represent sensory input and the infant’s interaction with other actors in its immediate ecological environment. On the basis of available experimental evidence, it will be argued that ETLA offers a productive alternative to traditional descriptive views of the language acquisition process by presenting an operative model of how early linguistic function may emerge through interaction

Robot ajedrecista: sistema mecatrónico aplicado a la toma de decisiones

Este trabajo presenta un sistema mecatrónico compuesto por un brazo robótico que juega ajedrez de forma autónoma. El sistema se basa en un robot manipulador de tipo industrial, un sistema de visión artificial, y un motor de juego basado en software libre. La robótica aplicada a juegos interactivos constituye un excelente problema para explorar la colaboración humana-robot, ya que presenta una estructura cuya complejidad puede ser gradualmente incrementada. Por lo tanto, este desarrollo debe entenderse como una primera aplicación exitosa de un sistema mecatrónico de toma de decisiones factible de migrar a otros usos y contextos.Sociedad Argentina de Informática e Investigación Operativa (SADIO

Robot ajedrecista: sistema mecatrónico aplicado a la toma de decisiones

Este trabajo presenta un sistema mecatrónico compuesto por un brazo robótico que juega ajedrez de forma autónoma. El sistema se basa en un robot manipulador de tipo industrial, un sistema de visión artificial, y un motor de juego basado en software libre. La robótica aplicada a juegos interactivos constituye un excelente problema para explorar la colaboración humana-robot, ya que presenta una estructura cuya complejidad puede ser gradualmente incrementada. Por lo tanto, este desarrollo debe entenderse como una primera aplicación exitosa de un sistema mecatrónico de toma de decisiones factible de migrar a otros usos y contextos.Sociedad Argentina de Informática e Investigación Operativa (SADIO

Exploring the use of a handheld device in language teaching human-robot interaction

International audienceIn this paper, we are exploring a human-robot in- terface allowing non-expert users to easily and intu- itively teach new words to a robot. Many challenges may be addressed before achieving such behavior as joint attention, naming, categorization and search- ing. Instead of using direct interactions (such as gesture and voice recognition) which are not robust enough in unconstrained environments, we use here a handheld device as a mediator between the user and the robot. The device allows us, among other things, to display the robot's camera visual feed- back as well as interacting through user's gestures on the touchscreen. Thus, users are able to draw the robot's attention toward locations, to select a particular ob ject in the field of view of the robot, to name it and with our “active-searching” system to find it again later. An exploratory study has been carried out in order to get some early users opinions, which tend to show that users easily use the interface during robust interaction sessions