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.