Soutenance de thèse : Syed Khursheed Hasnain
Titre de la thèse
Développement d'un mécanisme de communication implicite pour les interactions homme-robot.
Development of implicit communication mechanism for human-robot interactions.
Date et lieu de soutenance
Jeudi 10 juillet 2014, 14h.
Université de Cergy-Pontoise, site de St-Martin 2, Amphithéâtre des Colloques.
Moyens de communication implicites, Interactions Homme-Robot, Synchronisation, Mécanismes de résonance, Système dynamique, Réseaux de neurones.
As robots start moving closer to our social and daily lives, issues of agency and social behavior become more important. However, despite noticeable advances in Human Robot Interaction (HRI), the developed technologies induce two major drawbacks : (i) HRI are highly demanding, (ii) humans have to adapt their way of thinking to the potential and limitations of the Robot. Thereby, HRI induce an important cognitive load which question the acceptability of the future robots. Consequently, we can address the question of understanding and mastering the development of pleasant yet efficient human-robot interactions which increase self- esteem, engagement (or pleasure), and efficacy of the human when interacting with the machine. In this race for more user-friendly HRI systems (robotic companion, intelligent objects etc.), working on the technical features (the design of appearance and superficial traits of behavior) can contribute to some partial solutions for punctual or short-term interactions. For instance, a major focus of interest has been put on the expressiveness and the appearance of robots and avatars. Yet, these approaches have neglected the importance of understanding the dynamics of interactions. In our opinion, intuitive communication refers to the ability of the robot to detect the crucial signals of the interaction and use them to adapt one's dynamics to the other's behavior. In fact, this central issue is highly dependent on the robot's capabilities to sense the human world and interact with it in a way that emulates human-human interactions. In early communication among humans, synchrony was found to be a funda- mental mechanism relying on very low-level sensory-motor networks, inducing the synchronization of inter-individual neural populations from sensory flows (vision, audition, or touch). Synchrony is caused by the interaction but also sustains the interaction itself in a circular way, as promoted by the enaction approach. Consequently, to become a partner in a working together scenario, the machine can obtain a minimal level of autonomy and adaptation by predicting the rhythmic structure of the interaction to build reinforcement signals to adapt the robot behavior as it can maintain the interest of the human in more long-term interactions. More precisely, as we are aiming for more “intuitive” and “natural” HRI, we took advantages of recent discoveries in low-level human interactions and studied Unintentional Synchronizations during rhythmic human robot interactions. We argue that exploiting natural stability and adaptability properties of unintentional synchronizations and rhythmic activities in human-human interactions can solve several of the acceptability problems of HRIs, and allow rethinking the current approaches to design them.
Implicit communication mechanis, Human-Robot interactions, Synchronisation, Resonance mechanisms, Dynamical system approach, Neural network
Composition du jury
- Philippe GAUSSIER, Professeur, Université de Cergy-Pontoise, Directeur de thèse
- Ghilès MOSTAFAOUI, Maitre de conférences, Université de Cergy-Pontoise, Co-directeur de thèse
- Lola CANAMERO, Associate Professor, University of Hertfordshire, Rapporteur
- Mohamed CHETOUANI, Professeur, University Pierre and Marie Curie, Rapporteur
- Ludovic MARIN, Maitre de conférences, Université Montpellier 1, Examinateur
- Gérard BAILLY, Directeur de recherche CNRS, CNRS, GIPSA-Lab Grenoble, Examinateur