A dynamical systems approach to online event segmentation in cognitive robotics

Abstract

This paper addresses the problem of segmenting perception in physical robots into meaningful events along time. In structured environments this problem can be approached using domain-specific techniques, but in the general case, as when facing unknown environments, this becomes a non-trivial problem. We propose a dynamical systems approach to this problem, consisting of simultaneously learning a model of the robot’s interaction with the environment (robot and world seen as a single, coupled dynamical system), and deriving predictions about its short-term evolution. Event boundaries are detected once synchronization is lost, according to a simple statistical test. An experimental proof of concept of the proposed framework is presented, simulating a simple active perception task of a robot following a ball. The results reported here corroborate the approach, in the sense that the event boundaries are correctly detected.