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TitleA dynamic field approach to goal inference and error monitoring for human-robot interaction
Author(s)Bicho, E.
Louro, Luís
Hipólito, Nzoji
Erlhagen, Wolfram
KeywordsHuman-robot interaction
Goal inference
Error monitoring
Joint action
Anticipatory behavior
Action understanding
Dynamic neural fields
Issue date2009
CitationDAUTENHAHN, E., ed. lit. – “AISB Convention 2009 on Adaptive & Emergent Behaviour & Complex Systems : proceedings of the International Symposium on New Frontiers in Human-Robot Interaction, 1, Edinburgh, Scotland, 2009”. [S.l. : s.n, 2009]. p. 31-37.
Abstract(s)In this paper we present results of our ongoing research on non-verbal human-robot interaction that is heavily inspired by recent experimental findings about the neuro-cognitive mechanisms supporting joint action in humans. The robot control architecture implements the joint coordination of actions and goals as a dynamic process that integrates contextual cues, shared task knowledge and the predicted outcome of the user’s motor behavior. The architecture is formalized by a coupled system of dynamic neural fields representing a distributed network of local but connected neural populations with specific functionalities. We validate the approach in a task in which a robot and a human user jointly construct a toy ’vehicle’. We show that the context-dependent mapping from action observation onto appropriate complementary actions allows the robot to cope with dynamically changing joint action situations. This includes a basic form of error monitoring and compensation.
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
DEI - Artigos em atas de congressos internacionais

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