Developmental Robots - A New Paradigm

It has been proved to be extremely challenging for humans to program a robot to such a sufficient degree that it acts properly in a typical unknown human environment. This is especially true for a humanoid robot due to the very large number of redundant degrees of freedom and a large number of sensors that are required for a humanoid to work safely and effectively in the human environment. How can we address this fundamental problem? Motivated by human mental development from infancy to adulthood, we present a theory, an architecture, and some experimental results showing how to enable a robot to develop its mind automatically, through online, real time interactions with its environment. Humans mentally “raise” the robot through “robot sitting” and “robot schools” instead of task-specific robot programming

DAC-h3: A Proactive Robot Cognitive Architecture to Acquire and Express Knowledge About the World and the Self

This paper introduces a cognitive architecture for a humanoid robot to engage in a proactive, mixed-initiative exploration and manipulation of its environment, where the initiative can originate from both the human and the robot. The framework, based on a biologically-grounded theory of the brain and mind, integrates a reactive interaction engine, a number of state-of-the art perceptual and motor learning algorithms, as well as planning abilities and an autobiographical memory. The architecture as a whole drives the robot behavior to solve the symbol grounding problem, acquire language capabilities, execute goal-oriented behavior, and express a verbal narrative of its own experience in the world. We validate our approach in human-robot interaction experiments with the iCub humanoid robot, showing that the proposed cognitive architecture can be applied in real time within a realistic scenario and that it can be used with naive users

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

Developing a protocol and experimental setup for using a humanoid robot to assist children with autism to develop visual perspective taking skills

Visual Perspective Taking (VPT) is the ability to see the world from another person's perspective, taking into account what they see and how they see it, drawing upon both spatial and social information. Children with autism often find it difficult to understand that other people might have perspectives, viewpoints, beliefs and knowledge that are different from their own, which is a fundamental aspect of VPT. In this research we aimed to develop a methodology to assist children with autism develop their VPT skills using a humanoid robot and present results from our first long-term pilot study. The games we devised were implemented with the Kaspar robot and, to our knowledge, this is the first attempt to improve the VPT skills of children with autism through playing and interacting with a humanoid robot. We describe in detail the standard pre- and post- assessments that we performed with the children in order to measure their progress and also the inclusion criteria derived from the results for future studies in this field. Our findings suggest that some children may benefit from this approach of learning about VPT, which shows that this approach merits further investigation.Peer reviewe

Interaction and Experience in Enactive Intelligence and Humanoid Robotics

We overview how sensorimotor experience can be operationalized for interaction scenarios in which humanoid robots acquire skills and linguistic behaviours via enacting a “form-of-life”’ in interaction games (following Wittgenstein) with humans. The enactive paradigm is introduced which provides a powerful framework for the construction of complex adaptive systems, based on interaction, habit, and experience. Enactive cognitive architectures (following insights of Varela, Thompson and Rosch) that we have developed support social learning and robot ontogeny by harnessing information-theoretic methods and raw uninterpreted sensorimotor experience to scaffold the acquisition of behaviours. The success criterion here is validation by the robot engaging in ongoing human-robot interaction with naive participants who, over the course of iterated interactions, shape the robot’s behavioural and linguistic development. Engagement in such interaction exhibiting aspects of purposeful, habitual recurring structure evidences the developed capability of the humanoid to enact language and interaction games as a successful participant

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

Social Situatedness: Vygotsky and Beyond

The concept of ‘social situatedness’, i.e. the idea that the development of individual intelligence requires a social (and cultural) embedding, has recently received much attention in cognitive science and artificial intelligence research. The work of Lev Vygotsky who put forward this view already in the 1920s has influenced the discussion to some degree, but still remains far from well known. This paper therefore aims to give an overview of his cognitive development theory and discuss its relation to more recent work in primatology and socially situated artificial intelligence, in particular humanoid robotics

Affect Recognition in Autism: a single case study on integrating a humanoid robot in a standard therapy.

Autism Spectrum Disorder (ASD) is a multifaceted developmental disorder that comprises a mixture of social impairments, with deficits in many areas including the theory of mind, imitation, and communication. Moreover, people with autism have difficulty in recognising and understanding emotional expressions. We are currently working on integrating a humanoid robot within the standard clinical treatment offered to children with ASD to support the therapists. In this article, using the A-B-A' single case design, we propose a robot-assisted affect recognition training and to present the results on the child’s progress during the five months of clinical experimentation. In the investigation, we tested the generalization of learning and the long-term maintenance of new skills via the NEPSY-II affection recognition sub-test. The results of this single case study suggest the feasibility and effectiveness of using a humanoid robot to assist with emotion recognition training in children with ASD

A Review of Verbal and Non-Verbal Human-Robot Interactive Communication

In this paper, an overview of human-robot interactive communication is presented, covering verbal as well as non-verbal aspects of human-robot interaction. Following a historical introduction, and motivation towards fluid human-robot communication, ten desiderata are proposed, which provide an organizational axis both of recent as well as of future research on human-robot communication. Then, the ten desiderata are examined in detail, culminating to a unifying discussion, and a forward-looking conclusion