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Exploiting local perceptual models for topological map-building (2003)
Patrick Beeson
,
Matt MacMahon
,
Joseph Modayil
,
Jefferson Provost
, Francesco Savelli and
Benjamin Kuipers
The Spatial Semantic Hierarchy (SSH) provides a robot-independent ontology and logical theory for building topological maps of large-scale environments online. Existing SSH implementations make very limited use of perceptual information and thus create many candidate maps. Metrical mapping implementations capture detailed knowledge about local small-scale space but do not handle large environments well due to computational limitations and global metrical uncertainty. In this paper, we extend the SSH to utilize better sensory information by incorporating information derived from local metrical models into the large-scale space framework. This new extension of the Spatial Semantic Hierarchy uses local topology obtained from local perceptual models to constrain a global topological map search.
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Citation:
In
IJCAI-2003 Workshop on Reasoning with Uncertainty in Robotics (RUR-03)
, 2003.
Bibtex:
@inproceedings{beeson:ijcai-rur03, title={Exploiting local perceptual models for topological map-building}, author={Patrick Beeson and Matt MacMahon and Joseph Modayil and Jefferson Provost and Francesco Savelli and Benjamin Kuipers}, booktitle={IJCAI-2003 Workshop on Reasoning with Uncertainty in Robotics (RUR-03)}, url="http://nn.cs.utexas.edu/?beeson:ijcai-rur03", year={2003} }
People
Patrick Beeson
pbeeson [at] traclabs com
Benjamin Kuipers
kuipers [at] cs utexas edu
Matt MacMahon
adastra [at] cs utexas edu
Joseph Modayil
modayil [at] cs utexas edu
Jefferson Provost
Ph.D. Alumni
jefferson provost [at] gmail com
Areas of Interest
Navigation and Mapping