What Does it Take to be a Social Agent?

The aim of this paper is to present a philosophically inspired list of minimal requirements for social agency that may serve as a guideline for social robotics. Such a list does not aim at detailing the cognitive processes behind sociality but at providing an implementation-free characterization of the capacities and skills associated with sociality. We employ the notion of intentional stance as a methodological ground to study intentional agency and extend it into a social stance that takes into account social features of behavior. We discuss the basic requirements of sociality and different ways to understand them, and suggest some potential benefits of understanding them in an instrumentalist way in the context of social robotics.The aim of this paper is to present a philosophically inspired list of minimal requirements for social agency that may serve as a guideline for social robotics. Such a list does not aim at detailing the cognitive processes behind sociality but at providing an implementation-free characterization of the capacities and skills associated with sociality. We employ the notion of intentional stance as a methodological ground to study intentional agency and extend it into a social stance that takes into account social features of behavior. We discuss the basic requirements of sociality and different ways to understand them, and suggest some potential benefits of understanding them in an instrumentalist way in the context of social robotics.Peer reviewe

Rackham: An Interactive Robot-Guide

International audienceRackham is an interactive robot-guide that has been used in several places and exhibitions. This paper presents its design and reports on results that have been obtained after its deployment in a permanent exhibition. The project is conducted so as to incrementally enhance the robot functional and decisional capabilities based on the observation of the interaction between the public and the robot. Besides robustness and efficiency in the robot navigation abilities in a dynamic environment, our focus was to develop and test a methodology to integrate human-robot interaction abilities in a systematic way. We first present the robot and some of its key design issues. Then, we discuss a number of lessons that we have drawn from its use in interaction with the public and how that will serve to refine our design choices and to enhance robot efficiency and acceptability

Artificial Cognition for Social Human-Robot Interaction: An Implementation

© 2017 The Authors Human–Robot Interaction challenges Artificial Intelligence in many regards: dynamic, partially unknown environments that were not originally designed for robots; a broad variety of situations with rich semantics to understand and interpret; physical interactions with humans that requires fine, low-latency yet socially acceptable control strategies; natural and multi-modal communication which mandates common-sense knowledge and the representation of possibly divergent mental models. This article is an attempt to characterise these challenges and to exhibit a set of key decisional issues that need to be addressed for a cognitive robot to successfully share space and tasks with a human. We identify first the needed individual and collaborative cognitive skills: geometric reasoning and situation assessment based on perspective-taking and affordance analysis; acquisition and representation of knowledge models for multiple agents (humans and robots, with their specificities); situated, natural and multi-modal dialogue; human-aware task planning; human–robot joint task achievement. The article discusses each of these abilities, presents working implementations, and shows how they combine in a coherent and original deliberative architecture for human–robot interaction. Supported by experimental results, we eventually show how explicit knowledge management, both symbolic and geometric, proves to be instrumental to richer and more natural human–robot interactions by pushing for pervasive, human-level semantics within the robot's deliberative system

Théorie et pratique de l'interaction humain-robot

National audienceIn this presentation, we will outline the various lines of research in which we have participated and contributed in the field of human-robot interaction.We'll start by explaining what interaction and robotic architecture are. We'll show how the notion of interaction has led us to evolve from the traditional architecture for autonomy to an architecture for interaction, notably through the theory of joint action developed in philosophy.Next, we'll talk about some of the components of this architecture to which we've contributed. We'll talk about data representation, how to model and supervise interaction, how to integrate learning and how to measure interaction quality.We then turn to more fundamental work, carried out with psychologists and philosophers on the notion of the social agent.Finally, we conclude with our research perspectives. To do this, we'll mention the research projects in which we're involved (ANR ai4hri Artificial Intelligence For Human-Robot Interaction, ANR ASTRID DISCUTER Dialogue Interactif Structuré, Consolidé et Unifié pour la réalisation de Tâches En Robotique, ANR PRCI ELSA Effective Learning of Social Affordances, ANR EPIIC ElectroPhysiological Involuntary Inputs for Collaborative robotics enhancement) which we will relate to our current work on defining a robotic architecture based on the notion of social practice.Dans cette présentation, nous développerons les différents axes de recherche auxquels nous avons participé et contribué dans le domaine de l'interaction humain-robot.Nous commencerons par expliquer ce que sont d'une part une interaction et d'autre part une architecture robotique. Nous montrerons comment la notion d'interaction nous a amené à faire évoluer la traditionnelle architecture pour l'autonomie vers une architecture pour l'interaction en passant notamment par la théorie de l'action jointe développée en philosophie.Ensuite, nous parlerons de certains constituants de cette architecture sur lesquels nous avons contribué. Il sera question de représentation des données, de la manière de modéliser et de superviser une interaction, de la manière d'intégrer de l'apprentissage et de mesurer la qualité de l'interaction.Nous aborderons ensuite un travail plus fondamental, réalisé avec des psychologues et des philosophes sur la notion d'agent social.Enfin, nous conclurons par nos perspectives de recherche. Pour cela, nous évoquerons les projets de recherche auxquels nous participons (ANR ai4hri Artificial Intelligence For Human-Robot Interaction, ANR ASTRID DISCUTER Dialogue Interactif Structuré, Consolidé et Unifié pour la réalisation de Tâches En Robotique, ANR PRCI ELSA Effective Learning of Social Affordances, ANR EPIIC ElectroPhysiological Involuntary Inputs for Collaborative robotics enhancement) que nous mettrons en relation avec nos travaux en cours portant sur la définition d'une architecture robotique basée sur la notion de pratique sociale

Théorie et pratique de l'interaction humain-robot

National audienceIn this presentation, we will outline the various lines of research in which we have participated and contributed in the field of human-robot interaction.We'll start by explaining what interaction and robotic architecture are. We'll show how the notion of interaction has led us to evolve from the traditional architecture for autonomy to an architecture for interaction, notably through the theory of joint action developed in philosophy.Next, we'll talk about some of the components of this architecture to which we've contributed. We'll talk about data representation, how to model and supervise interaction, how to integrate learning and how to measure interaction quality.We then turn to more fundamental work, carried out with psychologists and philosophers on the notion of the social agent.Finally, we conclude with our research perspectives. To do this, we'll mention the research projects in which we're involved (ANR ai4hri Artificial Intelligence For Human-Robot Interaction, ANR ASTRID DISCUTER Dialogue Interactif Structuré, Consolidé et Unifié pour la réalisation de Tâches En Robotique, ANR PRCI ELSA Effective Learning of Social Affordances, ANR EPIIC ElectroPhysiological Involuntary Inputs for Collaborative robotics enhancement) which we will relate to our current work on defining a robotic architecture based on the notion of social practice. The presentation will take place in French and will also be broadcast via http://live.laas.frDans cette présentation, nous développerons les différents axes de recherche auxquels nous avons participé et contribué dans le domaine de l'interaction humain-robot.Nous commencerons par expliquer ce que sont d'une part une interaction et d'autre part une architecture robotique. Nous montrerons comment la notion d'interaction nous a amené à faire évoluer la traditionnelle architecture pour l'autonomie vers une architecture pour l'interaction en passant notamment par la théorie de l'action jointe développée en philosophie.Ensuite, nous parlerons de certains constituants de cette architecture sur lesquels nous avons contribué. Il sera question de représentation des données, de la manière de modéliser et de superviser une interaction, de la manière d'intégrer de l'apprentissage et de mesurer la qualité de l'interaction.Nous aborderons ensuite un travail plus fondamental, réalisé avec des psychologues et des philosophes sur la notion d'agent social.Enfin, nous conclurons par nos perspectives de recherche. Pour cela, nous évoquerons les projets de recherche auxquels nous participons (ANR ai4hri Artificial Intelligence For Human-Robot Interaction, ANR ASTRID DISCUTER Dialogue Interactif Structuré, Consolidé et Unifié pour la réalisation de Tâches En Robotique, ANR PRCI ELSA Effective Learning of Social Affordances, ANR EPIIC ElectroPhysiological Involuntary Inputs for Collaborative robotics enhancement) que nous mettrons en relation avec nos travaux en cours portant sur la définition d'une architecture robotique basée sur la notion de pratique sociale. La présentation aura lieu en français et sera également diffusée via http://live.laas.f

Supervision pour un robot interactif: action et interaction pour un robot autonome en environnement humain

Human-Robot collaborative task achievement requires specific task supervision and execution. In order to close the loop with their human partners robots must maintain an interaction stream in order to communicate their own intentions and beliefs and to monitor the activity of their human partner. In this work we introduce SHARY, a supervisor dedicated to collaborative task achievement in the human robot interaction context. The system deals for one part with task refinement and on the other part with communication needed in the human-robot interaction context. To this end, each task is defined at a communication level and at an execution level. This system has been developped on the robot Rackham for a tour-guide demonstration and has then be used on the robot Jido for a task of fetch and carry to demonstrate system genericity.Nos travaux portent sur la supervision d'un robot autonome en environnement humain et plus particulièrement sur la prise en compte de l'interaction homme-robot au niveau décisionnel. Dans ce cadre, l'homme et le robot constituent un système dans lequel ils partagent un espace commun et échangent des informations à travers différentes modalités. L'interaction peut intervenir soit sur une requête explicite de l'homme, soit parce que le robot l'a estimée utile et en a pris l'initiative. Dans les deux cas le robot doit agir afin de satisfaire un but en prenant en compte de manière explicite la présence et les préferences de son partenaire humain. Pour cela, nous avons conçu et développé un système de supervision nommé Shary qui permet de gérer des tâches individuelles (où seul le robot est impliqué) et des tâches jointes (où le robot et un autre agent sont impliqués). Ce système se compose d'une mécanique d'exécution de tâches gérant d'une part la communication nécessaire au sein d'une tâche et d'autre part l'affinement de la tâche en sous-tâches. Pour cela chaque tâche est définie par un plan de communication et un plan de réalisation auxquels sont associés des moniteurs de suivi. Nous avons développé ce système sur le robot Rackham dans le cadre d'une tâche de "Guide de musée". Nous avons également utilisé ce système dans le cadre d'une tâche du type : "apporter quelque chose à quelqu'un" sur le robot Jido pour montrer la généricité du système

Théorie et pratique de l'interaction humain-robot

National audienceIn this presentation, we will outline the various lines of research in which we have participated and contributed in the field of human-robot interaction.We'll start by explaining what interaction and robotic architecture are. We'll show how the notion of interaction has led us to evolve from the traditional architecture for autonomy to an architecture for interaction, notably through the theory of joint action developed in philosophy.Next, we'll talk about some of the components of this architecture to which we've contributed. We'll talk about data representation, how to model and supervise interaction, how to integrate learning and how to measure interaction quality.We then turn to more fundamental work, carried out with psychologists and philosophers on the notion of the social agent.Finally, we conclude with our research perspectives. To do this, we'll mention the research projects in which we're involved (ANR ai4hri Artificial Intelligence For Human-Robot Interaction, ANR ASTRID DISCUTER Dialogue Interactif Structuré, Consolidé et Unifié pour la réalisation de Tâches En Robotique, ANR PRCI ELSA Effective Learning of Social Affordances, ANR EPIIC ElectroPhysiological Involuntary Inputs for Collaborative robotics enhancement) which we will relate to our current work on defining a robotic architecture based on the notion of social practice.Dans cette présentation, nous développerons les différents axes de recherche auxquels nous avons participé et contribué dans le domaine de l'interaction humain-robot.Nous commencerons par expliquer ce que sont d'une part une interaction et d'autre part une architecture robotique. Nous montrerons comment la notion d'interaction nous a amené à faire évoluer la traditionnelle architecture pour l'autonomie vers une architecture pour l'interaction en passant notamment par la théorie de l'action jointe développée en philosophie.Ensuite, nous parlerons de certains constituants de cette architecture sur lesquels nous avons contribué. Il sera question de représentation des données, de la manière de modéliser et de superviser une interaction, de la manière d'intégrer de l'apprentissage et de mesurer la qualité de l'interaction.Nous aborderons ensuite un travail plus fondamental, réalisé avec des psychologues et des philosophes sur la notion d'agent social.Enfin, nous conclurons par nos perspectives de recherche. Pour cela, nous évoquerons les projets de recherche auxquels nous participons (ANR ai4hri Artificial Intelligence For Human-Robot Interaction, ANR ASTRID DISCUTER Dialogue Interactif Structuré, Consolidé et Unifié pour la réalisation de Tâches En Robotique, ANR PRCI ELSA Effective Learning of Social Affordances, ANR EPIIC ElectroPhysiological Involuntary Inputs for Collaborative robotics enhancement) que nous mettrons en relation avec nos travaux en cours portant sur la définition d'une architecture robotique basée sur la notion de pratique sociale

What Is It to Implement a Human-Robot Joint Action?

International audienceJoint action in the sphere of human–human interrelations may be a model for human–robot interactions. Human–human interrelations are only possible when several prerequisites are met, inter alia: (1) that each agent has a representation within itself of its distinction from the other so that their respective tasks can be coordinated; (2) each agent attends to the same object, is aware of that fact, and the two sets of “attentions” are causally connected; and (3) each agent understands the other’s action as intentional. The authors explain how human–robot interaction can benefit from the same threefold pattern. In this context, two key problems emerge. First, how can a robot be programed to recognize its distinction from a human subject in the same space, to detect when a human agent is attending to something, to produce signals which exhibit their internal state and make decisions about the goal-directedness of the other’s actions such that the appropriate predictions can be made? Second, what must humans learn about robots so they are able to interact reliably with them in view of a shared goal? This dual process is here examined by reference to the laboratory case of a human and a robot who team up in building a stack with four blocks

Semantic Spatial Representation: a unique representation of an environment based on an ontology for robotic applications

International audienceIt is important, for human-robot interaction, to endow the robot with the knowledge necessary to understand human needs and to be able to respond to them. We present a formalized and unified representation for indoor environments using an ontology devised for a route description task in which a robot must provide explanations to a person. We show that this representation can be used to choose a route to explain to a human as well as to verbalize it using a route perspective. Based on ontology, this representation has a strong possibility of evolution to adapt to many other applications. With it, we get the semantics of the environment elements while keeping a description of the known connectivity of the environment. This representation and the illustration algorithms, to find and verbalize a route, have been tested in two environments of different scales

Evaluation of the Quality of Interaction from the robot point of view in Human-Robot Interactions

International audienceIt is important for a service robot to be able to evaluate if an interaction with a human is going well or not. This paper presents a novel way to evaluate human-robot interactions, in the context of social interactions and collaborative tasks between a human and a robot. We propose a model allowing the robot to measure in real-time the quality of its interactions. This new information will improve its decision-making process