@InProceedings{lindes-EtAl:2017:RoboNLP,
  author    = {Lindes, Peter  and  Mininger, Aaron  and  Kirk, James R.  and  Laird, John E.},
  title     = {Grounding Language for Interactive Task Learning},
  booktitle = {Proceedings of the First Workshop on Language Grounding for Robotics},
  month     = {August},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {1--9},
  abstract  = {This paper describes how language is
	grounded by a comprehension system
	called Lucia within a robotic agent called
	Rosie that can manipulate objects and
	navigate indoors. The whole system is
	built within the Soar cognitive architecture
	and uses Embodied Construction Grammar
	(ECG) as a formalism for describing
	linguistic knowledge. Grounding is performed
	using knowledge from the grammar
	itself, from the linguistic context,
	from the agents perception, and from an
	ontology of long-term knowledge about
	object categories and properties and actions
	the agent can perform. The paper
	also describes a benchmark corpus of 200
	sentences in this domain along with test
	versions of the world model and ontology
	and gold-standard meanings for each
	of the sentences. The benchmark is contained
	in the supplemental materials.},
  url       = {http://www.aclweb.org/anthology/W17-2801}
}