Towards a “chaotic” smooth pursuit

Abstract

Real autonomous systems are very difficult to design, mainly due to the ever changing conditions of the environments where they are supposed to work. In the area of humanoid robotics these difficulties are increased not only because of the complexity of their mechanical structure, above all because they are supposed to work under the same dynamic conditions as we humans do. Our approach for the creation of real autonomy in artificial systems is based on the use of nonlinear dynamical systems. The purpose of this research is to demonstrate the feasibility of using coupled chaotic systems within the area of cognitive developmental robotics. In our quest towards the design and implementation of a real self-adaptive autonomous cognitive architecture, we have decided to start with a simple application that will tell us how appropriate this approach can be for humanoid robots. Once an object appears in front of a camera, we demonstrate that the visual input is enough for the self-organization of the axes controlling the motion of a single eye, both in a virtual and a real platform. No learning or specific coding of the task is needed, which results in a very fast adaptation and robustness to perturbations. Another equally important goal of this research is the possibility of having new insights about how the coordination of multiple degrees of freedom emerges in human infants.