Toward cognitive robot companions

Abstract

If robots have to be, one day, part of our environment and assist humans in their daily life, they will have to be endowed not only with the necessary functions for sensing, moving and acting, but also and inevitably, with more advanced cognitive capacities. Indeed a robot that will interact with people will need to be able to understand the spatial and dynamic structure of its environment, to exhibit a social behavior, to communicate with humans at the appropriate level of abstraction, to focus its attention and to take decisions for achieving tasks, to learn new knowledge and to evolve new capacities in an open-ended fashion. The COGNIRON (The Cognitive Robot Companion) project1 studies the development of robots whose ultimate task would be serve and assist humans. Research is carried out in four main domains: Perception and spatial cognition. The project addresses the fundamental questions of scene understanding, object learning and recognition, and semantic labeling of space through interacting with humans. Human-Robot interaction. Enabling an embodied dialogue capability is essential for a cognitive robot companion interacting with humans. One of the crucial aspects is handling multi-modality to cope gestures and other non-verbal signals and to make references to the environment shared with humans. Another aspect of Human-robot interaction lies in understanding human actions by the robot so that it can act in an appropriate manner and understand human needs. This requires visual detection and tracking of humans, of their faces, 3D modeling of human body, interpretation of human activities based on gestures, postures, attitudes, and motions. Finally, the robot must exhibit an acceptable social behavior, respecting human social spaces and affective factors (e.g., user comfort). Decision-making and expression of intentions. Making decisions, be it for autonomous task achievement or for humanrobot interaction, is a fundamental capability of a cognitive robot. The project studies decision-making abilities in uncertain and varying environments, shared decision-making and actions with humans, intentionality expression by robots during interaction with humans, as well as cognitive architectures for the integration of robot capabilities. Learning. For a robot companion to show adaptive, life-long learning behavior, it must be capable of acquiring new skills when required, and of incremental acquisition of skills for learning complete tasks. Imitation learning from humans is one of the main approaches investigated by the project to achieve this learning capability. The talk will overview the achievements of the project and its results that are demonstrated in three main experimental settings, enabling to exhibit the abovementioned cognitive capacities : the robot home tour, the curious and proactive robot and the robot learner.