Utilize este identificador para referenciar este registo: http://hdl.handle.net/1822/17339

TítuloA dynamic field approach to goal inference, error detection and anticipatory action selection in human-robot collaboration
Autor(es)Bicho, E.
Erlhagen, Wolfram
Louro, Luís
Silva, Eliana Costa e
Silva, Rui Manuel Gomes
Hipólito, Nzoji
Palavras-chaveHuman-robot interaction
Human-robot collaboration
Goal inference
Error detection
Anticipation
Action selection
Dynamic Fields
DataNov-2011
EditoraJohn Benjamins Publishing Company
Resumo(s)In this chapter we present results of our ongoing research on efficient and fluent human-robot collaboration that is heavily inspired by recent experimental findings about the neurocognitive 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 as 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. More specifically, the results illustrate crucial cognitive capacities for efficient and successful human-robot collaboration such as goal inference, error detection and anticipatory action selection.
TipobookPart
URIhttp://hdl.handle.net/1822/17339
ISBN978 90 272 8339 9
Versão da editorahttp://benjamins.com/#catalog/books/ais.2.10bic/details
Arbitragem científicayes
AcessoopenAccess
Aparece nas coleções:CAlg - Livros e capítulos de livros/Books and book chapters

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