<?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>2026-09-19T09:47:31Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/35583" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/35583</identifier><datestamp>2022-01-13T07:54:11Z</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">Jeffrey A. Hoffman and Joseph H. Saleh.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Arnold, Julie Ann, S.M. Massachusetts Institute of Technology</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Massachusetts Institute of Technology. Dept. of Aeronautics and Astronautics.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Massachusetts Institute of Technology. Department of Aeronautics and Astronautics</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2007-01-10T16:42:55Z</dim:field>
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   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2006</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2006</dim:field>
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   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">74491388</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2006.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (p. 113-121).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">Human-robotic systems will play a critical role in space exploration, should NASA embark on missions to the Moon and Mars. A unified framework to optimally leverage the capabilities of humans and robots in space exploration will be an invaluable tool for mission planning. Although there is a growing body of literature on human robotic interactions (HRI), there is not yet a framework that lends itself both to a formal representation of heterogeneous teams of humans and robots, and to an evaluation of such teams across a series of common, task-based metrics. My objective in this thesis is to lay the foundations of a unified framework for architecting human-robotic systems for optimal task performance given a set of metrics. First, I review literature from different fields including HRI and human-computer interaction, and synthesize multiple considerations for architecting heterogeneous teams of humans and robots. I then present methods to systematically and formally capture the characteristics that describe a human-robotic system to provide a basis for evaluating human-robotic systems against a common set of metrics.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">(cont.) I propose an analytical formulation of common metrics to guide the design and evaluate the performance of human-robot systems, and I then apply the analytical formulation to a case study of a multi-agent human-robot system developed at NASA. Finally, I discuss directions for further research aimed at developing this framework.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Julie Ann Arnold.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">S.M.</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">121 p.</dim:field>
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   <dim:field mdschema="dc" element="publisher" lang="en_US">Massachusetts Institute of Technology</dim:field>
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   <dim:field mdschema="dc" element="subject" lang="en_US">Aeronautics and Astronautics.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">Towards a framework for architecting heterogeneous teams of humans and robots for space exploration</dim:field>
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   	&lt;Title>Towards a framework for architecting heterogeneous teams of humans and robots for space exploration&lt;/Title>
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   	&lt;Abstract>Human-robotic systems will play a critical role in space exploration, should NASA embark on missions to the Moon and Mars. A unified framework to optimally leverage the capabilities of humans and robots in space exploration will be an invaluable tool for mission planning. Although there is a growing body of literature on human robotic interactions (HRI), there is not yet a framework that lends itself both to a formal representation of heterogeneous teams of humans and robots, and to an evaluation of such teams across a series of common, task-based metrics. My objective in this thesis is to lay the foundations of a unified framework for architecting human-robotic systems for optimal task performance given a set of metrics. First, I review literature from different fields including HRI and human-computer interaction, and synthesize multiple considerations for architecting heterogeneous teams of humans and robots. I then present methods to systematically and formally capture the characteristics that describe a human-robotic system to provide a basis for evaluating human-robotic systems against a common set of metrics.&lt;/Abstract>
   	&lt;Abstract>(cont.) I propose an analytical formulation of common metrics to guide the design and evaluate the performance of human-robot systems, and I then apply the analytical formulation to a case study of a multi-agent human-robot system developed at NASA. Finally, I discuss directions for further research aimed at developing this framework.&lt;/Abstract>
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