Exploiting Deep Semantics and Compositionality of Natural Language for Human-Robot-Interaction
| Autor: | Sean Trott, Jerome A. Feldman, Manfred Eppe |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
FOS: Computer and information sciences
0209 industrial biotechnology Computer Science - Computation and Language Grammar Natural language user interface Principle of compositionality Computer science Computer Science - Artificial Intelligence media_common.quotation_subject 02 engineering and technology Construction grammar Pragmatics Semantics Human–robot interaction Computer Science - Robotics 020901 industrial engineering & automation Artificial Intelligence (cs.AI) Human–computer interaction 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Cognitive linguistics Computation and Language (cs.CL) Robotics (cs.RO) Natural language media_common |
| Zdroj: | IROS |
| Popis: | We are developing a natural language interface for human robot interaction that implements reasoning about deep semantics in natural language. To realize the required deep analysis, we employ methods from cognitive linguistics, namely the modular and compositional framework of Embodied Construction Grammar (ECG) [18]. Using ECG, robots are able to solve fine-grained reference resolution problems and other issues related to deep semantics and compositionality of natural language. This also includes verbal interaction with humans to clarify commands and queries that are too ambiguous to be executed safely. We implement our NLU framework as a ROS package and present proof-of-concept scenarios with different robots, as well as a survey on the state of the art in knowledge-based language HRI. |
| Databáze: | OpenAIRE |
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