Learning view graphs for robot navigation

Abstract

We present a purely vision-based scheme for learning a parsimonious representation of an open environment. Using simple exploration behaviours, our system constructs a graph of appropriately chosen views. To navigate between views connected in the graph, we employ a homing strategy inspired by findings of insect ethology. Simulations and robot experiments demonstrate the feasibility of the proposed approach. Introduction 1 To survive in unpredictable and sometimes hostile environments animals have developed powerful strategies to find back to their shelter or to a previously visited food source. Successful navigation can already be achieved using simple mechanisms such as association of landmarks with movements (Wehner et al. 1996) or tracking of environmental features (Collett 1996). To understand more complex forms of spatial behaviour like finding shortcuts, however, we have to go beyond reactive control strategies, towards systems with internal states. In as far as they ...