Paper Info
Title
A software framework for the implementation of Dynamic Neural Field control architectures for human-robot interaction
Abstract
Useful and efficient human-robot interaction in joint tasks requires the design of a cognitive control architecture that endows robots with crucial cognitive and social capabilities such as intention recognition and complementary action selection. Herein, we present a software framework that eases the design and implementation of Dynamic Neural Field (DNF) cognitive architectures for human-robot joint tasks. We provide a graphical user interface to draw instances of the robot's control architecture. In addition, it allows to simulate, inspect and parametrize them in real-time. The framework eases parameter tuning by allowing changes on-the-fly and by connecting the cognitive architecture with simulated or real robots. Using the case study of an anthropomorphic robot providing assistance to a disabled person during a meal scenario, we illustrate the applicability of the framework.
Year
DOI
Venue
2017
10.1109/ICARSC.2017.7964067
2017 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)
Keywords
Field
DocType
software framework,dynamic neural field control architectures,human-robot interaction,cognitive control architecture,cognitive capabilities,social capabilities,anthropomorphic robot
Architecture,Computer science,Robot kinematics,Graphical user interface,Human–computer interaction,Artificial intelligence,Cognitive architecture,Action selection,Robot,Software framework,Human–robot interaction
Conference
ISSN
ISBN
Citations 
2573-9360
978-1-5090-6235-5
0
PageRank 
References 
Authors
0.34
7
7
Name
Order
Citations
PageRank
tiago malheiro152.52
Estela Bicho222324.15
Toni Machado301.69
Luís Louro4234.00
sergio monteiro563.21
Paulo Vicente601.01
Wolfram Erlhagen710822.63