<?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>2026-04-17T14:21:25Z</responseDate><request verb="GetRecord" identifier="oai:www.recercat.cat:2117/100823" metadataPrefix="oai_dc">https://recercat.cat/oai/request</request><GetRecord><record><header><identifier>oai:recercat.cat:2117/100823</identifier><datestamp>2025-07-22T22:36:29Z</datestamp><setSpec>com_2072_1033</setSpec><setSpec>col_2072_452951</setSpec></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
   <dc:title>Development of an application for the generation of robot trajectories based on learning by demonstration techniques</dc:title>
   <dc:creator>Dávila Carmona, Cristian</dc:creator>
   <dc:contributor>Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial</dc:contributor>
   <dc:contributor>Casals Gelpí, Alicia</dc:contributor>
   <dc:contributor>Vinagre Ruiz, Manuel</dc:contributor>
   <dc:subject>Àrees temàtiques de la UPC::Informàtica</dc:subject>
   <dc:subject>Machine learning</dc:subject>
   <dc:subject>Algorithms</dc:subject>
   <dc:subject>Aprenentatge per demostració</dc:subject>
   <dc:subject>Baxter</dc:subject>
   <dc:subject>ROS</dc:subject>
   <dc:subject>DTW</dc:subject>
   <dc:subject>GMM</dc:subject>
   <dc:subject>Learning by demonstration</dc:subject>
   <dc:subject>Aprenentatge automàtic</dc:subject>
   <dc:subject>Algorismes</dc:subject>
   <dc:description>En col·laboració amb la Universitat de Barcelona (UB) i la Universitat Rovira i Virgili (URV).</dc:description>
   <dc:description>The need of designing and implementing software to prepare robots for the execution of&#xd;
new tasks implies an expensive cost that requires specific hardware, software and knowledge.&#xd;
Learning by demonstration is a paradigm for enabling robots to autonomously&#xd;
perform new tasks learning from previous demonstrations. This project focuses on how&#xd;
to facilitate the learning of new tasks by robots through demonstrations performed by humans.&#xd;
In order to accomplish this goal, this thesis considers two subproblems: imitation&#xd;
and correspondence. Three different algorithms are used in order to solve both subproblems,&#xd;
in addition to a reinforcement learning to improve the final solution through new&#xd;
demonstrations. Moreover, a methodology is proposed to perform experimentation using&#xd;
these algorithms, including a final discussion over their performance and future work.</dc:description>
   <dc:date>2017-01</dc:date>
   <dc:type>Master thesis</dc:type>
   <dc:identifier>https://hdl.handle.net/2117/100823</dc:identifier>
   <dc:identifier>122523</dc:identifier>
   <dc:language>eng</dc:language>
   <dc:rights>Open Access</dc:rights>
   <dc:format>application/pdf</dc:format>
   <dc:publisher>Universitat Politècnica de Catalunya</dc:publisher>
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