DCG-UPUP-Away : automatic symbol acquisition through grounding to unknowns
Name
1020068951-MIT.pdf
Description
Full printable version
Size
9.15 MB
Format
Adobe PDF
Checksum (MD5)
d1585e4ba3c9c518f7804cf8698fb644
Author(s)
Tucker, Mycal (Mycal D.)
Advisor(s)
Nicholas Roy.
Alternative Title
Distributed Correspondence Graph - Unknown Phrase, Unknown Percept
Automatic symbol acquisition through grounding to unknowns
Date Issued
2016
Publisher
Massachusetts Institute of Technology
Abstract
Research in automatic natural language grounding, in which robots understand how phrases relate to real-world objects or actions, offers a compelling reality in which untrained humans can operate highly sophisticated robots. Current techniques for training robots to understand natural language, however, assume that there is a fixed set of phrases or objects that the robot will encounter during deployment. Instead, the real world is full of confusing jargon and unique objects that are nearly impossible to anticipate and therefore train for. This thesis presents a model called the Distributed Correspondence Graph - Unknown Phrase, Unknown Percept - Away (DCG-UPUP-Away) that augments the state of the art Distributed Correspondence Graph by recognizing unknown phrases and objects as unknown, as well as reasoning about objects that are not currently perceived. Furthermore, experimental results in simulation, as well as a trial run on a turtlebot platform, validate the effectiveness of DCG-UPUP-Away in grounding phrases and learning new phrases.
Description
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 91-96).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
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