Exploring Variation of Natural Human Commands to a Robot in a Collaborative Navigation Task

Matthew Marge, Claire Bonial, Ashley Foots, Cory Hayes, Cassidy Henry, Kimberly Pollard, Ron Artstein, Clare Voss, David Traum


Abstract
Robot-directed communication is variable, and may change based on human perception of robot capabilities. To collect training data for a dialogue system and to investigate possible communication changes over time, we developed a Wizard-of-Oz study that (a) simulates a robot’s limited understanding, and (b) collects dialogues where human participants build a progressively better mental model of the robot’s understanding. With ten participants, we collected ten hours of human-robot dialogue. We analyzed the structure of instructions that participants gave to a remote robot before it responded. Our findings show a general initial preference for including metric information (e.g., move forward 3 feet) over landmarks (e.g., move to the desk) in motion commands, but this decreased over time, suggesting changes in perception.
Anthology ID:
W17-2808
Volume:
Proceedings of the First Workshop on Language Grounding for Robotics
Month:
August
Year:
2017
Address:
Vancouver, Canada
Venues:
RoboNLP | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
58–66
Language:
URL:
https://www.aclweb.org/anthology/W17-2808
DOI:
10.18653/v1/W17-2808
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PDF:
http://aclanthology.lst.uni-saarland.de/W17-2808.pdf
Poster:
 W17-2808.Poster.pdf