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.
['Elvina Motard', 'Bogdan Raducanu', 'Viviane Cadenat', 'Jordi Vitrià']
Incremental On-Line Topological Map Learning for A Visual Homing Application