Activity recognition from the interactions between an assistive robotic walker and human users

Abstract

Detection of individuals' intention from a sequence of actions is an open and complex problem. In this paper we present a smart walker as mobility aid which can interpret the users' behaviour patterns to recognize their intentions and consequently act as an intelligent assistant. The result of the experiments performed in this paper demonstrates the potential of dynamic bayesian networks (DBN), in relation to their dynamic and unsupervised nature, for realistic human-robot interaction modelling.