Bidirectional gaze guiding and indexing in human-robot interaction through a situated architecture
Name
1012938756-MIT.pdf
Description
Full printable version
Size
17.63 MB
Format
Adobe PDF
Checksum (MD5)
767d47eda2f30f6d528bc95525abf5ea
Author(s)
DePalma, Nicholas Brian
Advisor(s)
Cynthia Breazeal.
Date Issued
2017
Publisher
Massachusetts Institute of Technology
Abstract
In this body of work, I present a situated and interactive agent perception system that can index into its world and, through a bidirectional exchange of referential gesture, direct its internal indexing system toward both well-known objects as well as simple visuo-spatial indexing in the world. The architecture presented incorporates a novel method for synthetic human-robot joint attention, an internal and automatic crowdsourcing system that provides opportunistic and lifelong robotic socio-visual learning, supports the bidirectional process of following referential behavior; and generates referential behavior useful for directing the gaze of human peers. This document critically probes questions in human-robot interaction around our understanding of gaze manipulation and memory imprinting on human partners in similar architectures and makes recommendations that may improve human-robot peer-to-peer learning.
Description
Thesis: Ph. D., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2017.
Cataloged from PDF version of thesis.
Includes bibliographical references.
Subjects
Program in Media Arts and Sciences ()
MIT Department
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
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