Reliable topological place detection in bubble space

This paper introduces a novel approach to topo-logical place detection. The approach is based on previously proposed bubble space representation - where all sensory features and their relative S²- geometry are encoded in a manner that is implicitly dependent on robot pose. Its novelty is that ensuring sensory data reliability is integrated with place detection. This is achieved via checking for informativeness, coherence and plenitude using only the bubble space representation of the incoming sensory data. The stringency of these checks is controllable via a set of associated parameters. Experimental results with benchmark datasets indicate correct detection rates comparable to state-of-the-art approaches in place detection. Furthermore, the detected places can then be immediately used to generate the nodes in topological maps.