Vision Based Localisation for a Mobile Robot
Identifieur interne : 002A83 ( Crin/Corpus ); précédent : 002A82; suivant : 002A84Vision Based Localisation for a Mobile Robot
Auteurs : Franck Gechter ; François CharpilletSource :
English descriptors
- KwdEn :
- localization, pca, pomdp, robot, vision.
Abstract
We present a vision based localization system for a mobile robot that uses a representative set of images obtained during an initial exploration of the environment. This set of images makes it possible to represent the environment as a partially markov decision process. The originality of this approach is the resulting data fusion process that uses both image matching and decision made by the robot in order to estimate the set of plausible position of the robot and the associated probabilities. Image matching or recognition is achieved using principal components analysis.
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CRIN:gechter00aLe document en format XML
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<sourceDesc><biblStruct><analytic><title xml:lang="en">Vision Based Localisation for a Mobile Robot</title>
<author><name sortKey="Gechter, Franck" sort="Gechter, Franck" uniqKey="Gechter F" first="Franck" last="Gechter">Franck Gechter</name>
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<author><name sortKey="Charpillet, Francois" sort="Charpillet, Francois" uniqKey="Charpillet F" first="François" last="Charpillet">François Charpillet</name>
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<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>localization</term>
<term>pca</term>
<term>pomdp</term>
<term>robot</term>
<term>vision</term>
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<front><div type="abstract" xml:lang="en" wicri:score="2353">We present a vision based localization system for a mobile robot that uses a representative set of images obtained during an initial exploration of the environment. This set of images makes it possible to represent the environment as a partially markov decision process. The originality of this approach is the resulting data fusion process that uses both image matching and decision made by the robot in order to estimate the set of plausible position of the robot and the associated probabilities. Image matching or recognition is achieved using principal components analysis.</div>
</front>
</TEI>
<BibTex type="inproceedings"><ref>gechter00a</ref>
<crinnumber>A00-R-232</crinnumber>
<category>3</category>
<equipe>MAIA</equipe>
<author><e>Gechter, Franck</e>
<e>Charpillet, François</e>
</author>
<title>Vision Based Localisation for a Mobile Robot</title>
<booktitle>{International Conference on Tools with Artificial Intelligence}</booktitle>
<year>2000</year>
<month>Nov</month>
<keywords><e>vision</e>
<e>robot</e>
<e>pca</e>
<e>pomdp</e>
<e>localization</e>
</keywords>
<abstract>We present a vision based localization system for a mobile robot that uses a representative set of images obtained during an initial exploration of the environment. This set of images makes it possible to represent the environment as a partially markov decision process. The originality of this approach is the resulting data fusion process that uses both image matching and decision made by the robot in order to estimate the set of plausible position of the robot and the associated probabilities. Image matching or recognition is achieved using principal components analysis.</abstract>
</BibTex>
</record>
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