Bidirectional gaze guiding and indexing in human-robot interaction through a situated architecture

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.

Department dc:contributor.department

Program in Media Arts and Sciences (Massachusetts Institute of Technology)

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2017

Author dc:creator

• DePalma, Nicholas Brian

Advisor dc:contributor.advisor

• Cynthia Breazeal.

• Program in Media Arts and Sciences ()

Statement dc:rights

• MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/112522

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/112522