Abstract
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.
DOI
10.1007/s10514-016-9587-8
Publication Date
2017-02-01
Publication Title
Autonomous Robots
Volume
41
Issue
2
Publisher
Springer Science and Business Media LLC
ISSN
1573-7527
Embargo Period
2024-11-22
First Page
367
Last Page
383
Recommended Citation
Stramandinoli, F., Marocco, D., & Cangelosi, A. (2017) 'Making sense of words: a robotic model for language abstraction', Autonomous Robots, 41(2), pp. 367-383. Springer Science and Business Media LLC: Available at: https://doi.org/10.1007/s10514-016-9587-8
