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TitleA software framework for the implementation of dynamic neural field control architectures for human-robot interaction
Author(s)Malheiro, Tiago Emanuel Quintas
Bicho, Estela
Machado, Toni
Louro, Luís
Monteiro, Sérgio
Vicente, Paulo
Erlhagen, Wolfram
Issue date29-Jun-2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
JournalIEEE International Conference on Autonomous Robot Systems and Competitions
Abstract(s)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.
TypeConference paper
AccessOpen access
Appears in Collections:CMAT - Artigos em atas de conferências e capítulos de livros com arbitragem / Papers in proceedings of conferences and book chapters with peer review

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