Making sense of words: a robotic model for language abstraction

Francesca Stramandinoli, Davide Marocco, Angelo Cangelosi

Research output: Contribution to journalArticlepeer-review


Building robots capable of acting independently in unstructured environments is still a challenging task for roboticists. The capability to comprehend and produce language in a ‘human-like’ manner represents a powerful tool for the autonomous interaction of robots with human beings, for better understanding situations and exchanging information during the execution of tasks that require cooperation. In this work, we present a robotic model for grounding abstract action words (i.e. USE, MAKE) through the hierarchical organization of terms directly linked to perceptual and motor skills of a humanoid robot. Experimental results have shown that the robot, in response to linguistic commands, is capable of performing the appropriate behaviors on objects. Results obtained in case of inconsistency between the perceptual and linguistic inputs have shown that the robot executes the actions elicited by the seen object.

Original languageEnglish
Pages (from-to)367-383
Number of pages17
JournalAutonomous Robots
Issue number2
Early online date1 Jul 2016
Publication statusPublished - 1 Feb 2017


  • Developmental robotics
  • Embodiment
  • Language modeling
  • Sensorimotor knowledge
  • Symbol grounding


Dive into the research topics of 'Making sense of words: a robotic model for language abstraction'. Together they form a unique fingerprint.

Cite this