Incremental On-Line Topological Map Learning for A Visual Homing Application

In this paper we propose an on-line incremental vision-based topological map learning for AIBO robots. The topological map is represented through a graph, where the vertices encode views from the robot´s environment and the edges the spatial relationship between these views. The views are represented through their SIFT keypoints. The proposed map learning method has been successfully applied to a homing application.