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Factoring the mapping problem: Mobile robot map-building in the Hybrid Spatial Semantic Hierarachy

¹ University of Texas
² University of Rochester

^* To whom correspondence should be addressed. E-mail: pbeeson{at}cs.utexas.edu.

	Abstract

We propose a factored approach to mobile robot map-building that handles qualitatively different types of uncertainty by combining the strengths of topological and metrical approaches. Our framework is based on a computational model of the human cognitive map; thus it allows robust navigation and communication within several different spatial ontologies. This paper focuses exclusively on the issue of map-building using the framework.

Our approach factors the mapping problem into natural sub-goals: building a metrical representation for local small-scale spaces; finding a topological map that represents the qualitative structure of large-scale space; and (when necessary) constructing a metrical representation for large-scale space using the skeleton provided by the topological map. We describe how to abstract a symbolic description of the robot's immediate surround from local metrical models, how to combine these local symbolic models in order to build global symbolic models, and how to create a globally consistent metrical map from a topological skeleton by connecting local frames of reference.

First published on May 19, 2009
The International Journal of Robotics Research 2009, doi:10.1177/0278364909100586


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