Building vision-based Topological maps for mobile robots by Evolving Self-Organizing Maps

Abstract

We propose a method to build topological maps from vision sensor information for mobile robots navigations. The method is based on Evolving Self-Organizing Maps (ESOM) proposed by Deng. Nodes and paths represent essential visual information in local environments and similarity relationships between environments respectively in Topological maps built by the ESOM. Moreover, the ESOM can online build the maps in real-time without pre-defined landmarks and metrical information of environments. In this presentation we show the validity of this method.