<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>2027-8306</journal-id>
<journal-title><![CDATA[Revista de Investigación, Desarrollo e Innovación]]></journal-title>
<abbrev-journal-title><![CDATA[Revista Investig. Desarro. Innov.]]></abbrev-journal-title>
<issn>2027-8306</issn>
<publisher>
<publisher-name><![CDATA[Universidad Pedagógica y Tecnológica de Colombia]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S2027-83062022000100121</article-id>
<article-id pub-id-type="doi">10.19053/20278306.v12.n1.2022.14213</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Autonomous vehicle localization method based on an extended Kalman filter and geo-referenced landmarks]]></article-title>
<article-title xml:lang="es"><![CDATA[Método de localización para vehículos autónomos basado en el filtro de Kalman extendido y balizas georreferenciadas]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Posso-Bautista]]></surname>
<given-names><![CDATA[Breyner]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Bacca-Cortés]]></surname>
<given-names><![CDATA[Eval Bladimir]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Caicedo-Bravo]]></surname>
<given-names><![CDATA[Eduardo]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad del Valle  ]]></institution>
<addr-line><![CDATA[Cali ]]></addr-line>
<country>Colombia</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad del Valle  ]]></institution>
<addr-line><![CDATA[Cali ]]></addr-line>
<country>Colombia</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Universidad del Valle  ]]></institution>
<addr-line><![CDATA[Cali ]]></addr-line>
<country>Colombia</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>06</month>
<year>2022</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>06</month>
<year>2022</year>
</pub-date>
<volume>12</volume>
<numero>1</numero>
<fpage>121</fpage>
<lpage>136</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_arttext&amp;pid=S2027-83062022000100121&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_abstract&amp;pid=S2027-83062022000100121&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_pdf&amp;pid=S2027-83062022000100121&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract Autonomous vehicles are considered a viable technological option to implement first/last mile transportation in the cities of tomorrow with a high population density, and for this reason it is essential that they have a robust localization system for the routes first-mile transport and last-mile transport points, and the route&#8217;s planning and navigation. This article presents the implementation of an outdoor parking localization system which uses a map based on geo-referenced landmarks (road marking poles with reflective tape) and an Extended Kalman Filter, fed with both odometry and 3D LiDAR information. The system was evaluated in nine routes with distances between 85 m and 360 m, in which an error was obtained between the ground-truth and the algorithm&#8217;s estimated position below 0.3 m and 0.5 m for the position in X and Y coordinates, respectively. The results show that this is a promising method that should be tested in larger settings using both natural and artificial landmarks.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen Los vehículos autónomos se consideran una buena opción tecnológica para implementar el transporte de primera/última milla, en ciudades del futuro con alta densidad poblacional. Para ello es necesario contar con un sistema de localización robusto en las fases de: ubicación del punto inicial y final del recorrido, la planificación y la navegación. En este artículo se presenta la implementación de un sistema de localización en parqueaderos al aire libre, que usa un mapa basado en estructuras georreferenciadas (postes de delimitación vial con cinta reflectiva) y un filtro de Kalman extendido, alimentado con información de odometría y de un LiDAR 3D. El sistema se evalúa en nueve recorridos con distancias entre 85 m y 360 m, y se obtiene un error entre el ground-truth y la posición estimada por el algoritmo por debajo de 0.3 m y 0.5 m para la posición en X y Y, respectivamente. Los resultados muestran que este es un método prometedor que debe ser probado en entornos más grandes, usando una combinación de referencias naturales y artificiales.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[autonomous vehicles]]></kwd>
<kwd lng="en"><![CDATA[robot localization]]></kwd>
<kwd lng="en"><![CDATA[Kalman filters]]></kwd>
<kwd lng="en"><![CDATA[laser radar]]></kwd>
<kwd lng="es"><![CDATA[vehículos autónomos]]></kwd>
<kwd lng="es"><![CDATA[localización de robots]]></kwd>
<kwd lng="es"><![CDATA[filtros de Kalman]]></kwd>
<kwd lng="es"><![CDATA[radar láser]]></kwd>
</kwd-group>
</article-meta>
</front><back>
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