Local metrical and global topological maps in the hybrid spatial semantic hierarchy

Topological and metrical methods for representing spatial knowledge have complementary strengths. We present a hybrid extension to the spatial semantic hierarchy that combines their strengths and avoids their weaknesses. Metrical SLAM methods are used to build local maps of small-scale space within the sensory horizon of the agent, while topological methods are used to represent the structure of large-scale space. We describe how a local perceptual map is analyzed to identify a local topology description and is abstracted to a topological place. The map building method creates a set of topological map hypotheses that are consistent with travel experience. The set of maps is guaranteed under reasonable assumptions to include the correct map. We demonstrate the method on a real environment with multiple nested large-scale loops.