In this paper we introduce a probabilistic approach to support visual supervision and gesture recognition. Task knowledge is both of geometric and visual nature and it is encoded in parametric eigenspaces. Learning processes for compute modal subspaces (eigenspaces) are the…

In this article we describe a novel algorithm that allows fast and continuous learning on a physical robot working in a real environment. The learning process is never stopped and new knowledge gained from robot-environment interactions can be incorporated into…

This paper presents a new system for recognition and imitation of a set of facial expressions using the visual information acquired by the robot. Besides, the proposed system detects and imitates the interlocutor’s head pose and motion. The approach described…

MACSimJX provides the means for advanced modelling and development of multiagent driven control systems. This is achieved by drawing together two modelling tools used extensively in their respective communities. These are Simulink, a tool used for control systems development and…

The ability of building robust semantic space representations of environments is crucial for the development of truly autonomous robots. This task, inherently connected with cognition, is traditionally achieved by training the robot with a supervised learning phase. We argue that…