<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-05-27T05:29:20Z</responseDate><request verb="GetRecord" identifier="oai:riuma.uma.es:10630/9841" metadataPrefix="marc">https://riuma.uma.es/rest/oai/request</request><GetRecord><record><header><identifier>oai:riuma.uma.es:10630/9841</identifier><datestamp>2026-02-03T12:37:21Z</datestamp><setSpec>com_10630_2254</setSpec><setSpec>col_10630_37957</setSpec></header><metadata><record xmlns="http://www.loc.gov/MARC21/slim" xmlns:dcterms="http://purl.org/dc/terms/" xmlns:doc="http://www.lyncode.com/xoai" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.loc.gov/MARC21/slim http://www.loc.gov/standards/marcxml/schema/MARC21slim.xsd">
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      <subfield code="a">dc</subfield>
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   <datafield ind2=" " ind1=" " tag="720">
      <subfield code="a">Blanco-Claraco, José Luis</subfield>
      <subfield code="e">author</subfield>
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   <datafield ind2=" " ind1=" " tag="260">
      <subfield code="c">2009</subfield>
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      <subfield code="a">This thesis focuses on the problem of enabling mobile robots to autonomously build&#xd;
world models of their environments and to employ them as a reference to self–localization&#xd;
and navigation.&#xd;
For mobile robots to become truly autonomous and useful, they must be able of&#xd;
reliably moving towards the locations required by their tasks. This simple requirement&#xd;
gives raise to countless problems that have populated research in the mobile robotics&#xd;
community for the last two decades. Among these issues, two of the most relevant&#xd;
are: (i) secure autonomous navigation, that is, moving to a target avoiding collisions&#xd;
and (ii) the employment of an adequate world model for robot self-referencing within&#xd;
the environment and also for locating places of interest. The present thesis introduces&#xd;
several contributions to both research fields.&#xd;
Among the contributions of this thesis we find a novel approach to extend SLAM&#xd;
to large-scale scenarios by means of a seamless integration of geometric and topological&#xd;
map building in a probabilistic framework that estimates the hybrid metric-topological&#xd;
(HMT) state space of the robot path. The proposed framework unifies the research areas&#xd;
of topological mapping, reasoning on topological maps and metric SLAM, providing&#xd;
also a natural integration of SLAM and the “robot awakening” problem.&#xd;
Other contributions of this thesis cover a wide variety of topics, such as optimal&#xd;
estimation in particle filters, a new probabilistic observation model for laser scanners&#xd;
based on consensus theory, a novel measure of the uncertainty in grid mapping, an&#xd;
efficient method for range-only SLAM, a grounded method for partitioning large maps&#xd;
into submaps, a multi-hypotheses approach to grid map matching, and a mathematical&#xd;
framework for extending simple obstacle avoidance methods to realistic robots.</subfield>
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      <subfield code="a">http://hdl.handle.net/10630/9841</subfield>
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      <subfield code="a">Robots autónomos - Tesis doctorales</subfield>
   </datafield>
   <datafield ind2="0" ind1="0" tag="245">
      <subfield code="a">Contributions to Localization, Mapping and Navigation in Mobile Robotics</subfield>
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