Title
Integrating verbal and nonverbal communication in a dynamic neural field architecture for human-robot interaction.
Abstract
How do humans coordinate their intentions, goals and motor behaviors when performing joint action tasks? Recent experimental evidence suggests that resonance processes in the observer's motor system are crucially involved in our ability to understand actions of others', to infer their goals and even to comprehend their action-related language. In this paper, we present a control architecture for human-robot collaboration that exploits this close perception-action linkage as a means to achieve more natural and efficient communication grounded in sensorimotor experiences. The architecture is formalized by a coupled system of dynamic neural fields representing a distributed network of neural populations that encode in their activation patterns goals, actions and shared task knowledge. We validate the verbal and nonverbal communication skills of the robot in a joint assembly task in which the human-robot team has to construct toy objects from their components. The experiments focus on the robot's capacity to anticipate the user's needs and to detect and communicate unexpected events that may occur during joint task execution.
Year
DOI
Venue
2010
10.3389/fnbot.2010.00005
Front. Neurorobot.
Keywords
Field
DocType
neural fields,mirror system,joint action,goal inference,natural communication,neurorobotics,human robot interaction,bioinformatics,biomedical research,nonverbal communication
ENCODE,Architecture,Mirror neuron,Communication,Computer science,Nonverbal communication,Artificial intelligence,Unexpected events,Robot,Observer (quantum physics),Machine learning,Human–robot interaction
Journal
Volume
ISSN
Citations 
4
1662-5218
21
PageRank 
References 
Authors
1.19
14
3
Name
Order
Citations
PageRank
Estela Bicho122324.15
Luís Louro2234.00
Wolfram Erlhagen310822.63