@InProceedings{marge-EtAl:2017:RoboNLP,
  author    = {Marge, Matthew  and  Bonial, Claire  and  Foots, Ashley  and  Hayes, Cory  and  Henry, Cassidy  and  Pollard, Kimberly  and  Artstein, Ron  and  Voss, Clare  and  Traum, David},
  title     = {Exploring Variation of Natural Human Commands to a Robot in a Collaborative Navigation Task},
  booktitle = {Proceedings of the First Workshop on Language Grounding for Robotics},
  month     = {August},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {58--66},
  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.},
  url       = {http://www.aclweb.org/anthology/W17-2808}
}