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

Patrick Beeson, Joseph Modayil, and Benjamin Kuipers. Factoring the mapping problem: Mobile robot map-building in the Hybrid Spatial Semantic Hierarchy. International Journal of Robotics Research, 29(4):428–459, April 2010.
Local download is a pre-print version. Final version can be found here.

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.

Additional Information

Local download is a pre-print version. Final version can be found here.

BibTeX

@Article{Beeson-ijrr-10,
  author =       {Patrick Beeson and Joseph Modayil and Benjamin Kuipers},
  title =        {Factoring the mapping problem: Mobile robot map-building in
                  the {Hybrid Spatial Semantic Hierarchy}},
  journal =      {International Journal of Robotics Research},
  year =         2010,
  volume =       29,
  number =       4,
  month =        {April},
  pages =        {428--459},
  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.},
  url =          {http://dx.doi.org/10.1177/0278364909100586},
  wwwnote =      {Local download is a pre-print version.  Final version can be
                  found <a href="http://dx.doi.org/10.1177/0278364909100586">
                  here</a>.},
  bib2html_extra_info ={Local download is a pre-print version.  Final version
                  can be found <a
                  href="http://dx.doi.org/10.1177/0278364909100586">
                  here</a>.},
  bib2html_pubtype ={Journal},
  bib2html_rescat ={Topological/Hybrid Map-Building},
}

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