Reducing the gap between cognitive and robotic systems

Abstract

Service robots will gradually be present in residences interacting with human beings in unstructured environments. Their acceptance is conditioned to the evolution of research in the area of social robotics, in particular using cognitive systems. One factor that compromises the rapid evolution of these studies is the difficulty in modeling cognitive systems due to the volume and complexity of information produced by a chaotic world full of sensory information. In addition, the validation of results with the use of real environments involving buildings, and people presents a high cost of installation and maintenance. This article offers two strategies to speed up this process. The first involves the definition of OntCog ontology that models the senses captured by the agent robotic sensors. This modeling facilitates the reproduction of experiments associated with cognitive models and the comparison among different implementations. The second is associated with the development of Robot House Simulator, which provides an environment where a robot and a human character can interact socially with increasing levels of cognitive processing. An unprecedented feature of this simulator is to provide information about all the senses of the robot, actually only the sense of vision or touch has been considered in the existing robotic simulators.