<?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>2026-09-18T21:57:52Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/106380" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/106380</identifier><datestamp>2026-06-06T00:55:46Z</datestamp><setSpec>com_1721.1_7582</setSpec><setSpec>com_1721.1_7581</setSpec><setSpec>col_1721.1_131023</setSpec></header><metadata><dim:dim xmlns:dim="http://www.dspace.org/xmlns/dspace/dim" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.dspace.org/xmlns/dspace/dim http://www.dspace.org/schema/dim.xsd">
   <dim:field mdschema="dc" element="contributor" qualifier="advisor" lang="en_US">Russ L. Tedrake.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Susilo, Hans (Hans V.)</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2017-01-12T18:18:27Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2017-01-12T18:18:27Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2016</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2016</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">http://hdl.handle.net/1721.1/106380</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">967656473</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">This electronic version was submitted by the student author.  The certified thesis is available in the Institute Archives and Special Collections.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Cataloged from student-submitted PDF version of thesis.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (pages 61-62).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">We need better methods of dynamic parameter estimation because robots are becoming more complex and their interactions with the unmodeled world are becoming more frequent. These methods should be fast, reliable, and easily adaptable to various classes of robots. Here, we design and build a parameter estimation system in a robotic simulation and controls framework called Drake. The parameter estimation works by minimizing the error between a model and the observed data from a given trajectory. Using our estimator, we then compare the minimization of three types of errors, generated by the dynamics model, energetic model, and simulation model. We quantify the speed and performance of each algorithm on the Acrobot system.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Hans Susilo.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">M.Eng.</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">62 pages</dim:field>
   <dim:field mdschema="dc" element="language" qualifier="iso" lang="en_US">eng</dim:field>
   <dim:field mdschema="dc" element="publisher" lang="en_US">Massachusetts Institute of Technology</dim:field>
   <dim:field mdschema="dc" element="rights" lang="en_US">M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.</dim:field>
   <dim:field mdschema="dc" element="rights" qualifier="uri" lang="en_US">http://dspace.mit.edu/handle/1721.1/7582</dim:field>
   <dim:field mdschema="dc" element="subject" lang="en_US">Electrical Engineering and Computer Science.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">Parameter estimation of manipulator robot dynamics</dim:field>
   <dim:field mdschema="dc" element="type" lang="en_US">Thesis</dim:field>
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	&lt;Language>eng&lt;/Language>
   	&lt;Title>Parameter estimation of manipulator robot dynamics&lt;/Title>
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   	&lt;PublicationDate>2016&lt;/PublicationDate>
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        	&lt;DisplayName>Susilo, Hans (Hans V.)&lt;/DisplayName>
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    &lt;Keyword>Electrical Engineering and Computer Science.&lt;/Keyword>
   	&lt;Abstract>We need better methods of dynamic parameter estimation because robots are becoming more complex and their interactions with the unmodeled world are becoming more frequent. These methods should be fast, reliable, and easily adaptable to various classes of robots. Here, we design and build a parameter estimation system in a robotic simulation and controls framework called Drake. The parameter estimation works by minimizing the error between a model and the observed data from a given trajectory. Using our estimator, we then compare the minimization of three types of errors, generated by the dynamics model, energetic model, and simulation model. We quantify the speed and performance of each algorithm on the Acrobot system.&lt;/Abstract>
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