EstelaBicho PierreMallet GregorSchöner Target Representation on an Autonomous Vehicle with Low-Level Sensors. I. J. Robotic Res. 19 424-447 2000 EstelaBicho GregorSchöner The dynamic approach to autonomous robotics demonstrated on a low-level vehicle platform. Robotics and Autonomous Systems 21 23-35 1997 W.Erlhagen E.Bicho The dynamic neural field approach to cognitive robotics Journal of Neural Engineering 3 36-54 2006 Abstract This tutorial presents an architecture for autonomous robots to generate behavior in joint action tasks. To efficiently interact with another agent in solving a mutual task, a robot should be endowed with cognitive skills such as memory, decision making, action understanding and prediction. The proposed architecture is strongly inspired by our current understanding of the processing principles and the neuronal circuitry underlying these functionalities in the primate brain. As a mathematical framework, we use a coupled system of dynamic neural fields, each representing the basic functionality of neuronal populations in different brain areas. It implements goal-directed behavior in joint action as a continuous process that builds on the interpretation of observed movements in terms of the partner’s action goal. We validate the architecture in two experimental paradigms: (1) a joint search task; (2) a reproduction of an observed or inferred end state of a grasping–placing sequence. We also review some of the mathematical results about dynamic neural fields that are important for the implementation work. W.Erlhagen E.Bicho The dynamic neural field approach to cognitive robotics Journal of Neural Engineering 3 36-54 2006 Abstract This tutorial presents an architecture for autonomous robots to generate behavior in joint action tasks. To efficiently interact with another agent in solving a mutual task, a robot should be endowed with cognitive skills such as memory, decision making, action understanding and prediction. The proposed architecture is strongly inspired by our current understanding of the processing principles and the neuronal circuitry underlying these functionalities in the primate brain. As a mathematical framework, we use a coupled system of dynamic neural fields, each representing the basic functionality of neuronal populations in different brain areas. It implements goal-directed behavior in joint action as a continuous process that builds on the interpretation of observed movements in terms of the partner’s action goal. We validate the architecture in two experimental paradigms: (1) a joint search task; (2) a reproduction of an observed or inferred end state of a grasping–placing sequence. We also review some of the mathematical results about dynamic neural fields that are important for the implementation work. WolframErlhagen AlbertMukovskiy EstelaBicho GiorgioPanin CsabaKiss AloisKnoll HeinT. vanSchie HaroldBekkering Goal-directed imitation for robots: A bio-inspired approach to action understanding and skill learning. Robotics and Autonomous Systems 54 353-360 2006 WolframErlhagen AlbertMukovskiy EstelaBicho GiorgioPanin CsabaKiss AloisKnoll HeinT. vanSchie HaroldBekkering Goal-directed imitation for robots: A bio-inspired approach to action understanding and skill learning. Robotics and Autonomous Systems 54 353-360 2006 WolframErlhagen AlbertMukovskiy EstelaBicho GiorgioPanin CsabaKiss AloisKnoll HeinT. vanSchie HaroldBekkering Action Understanding and Imitation Learning in a Robot-Human Task. Springer 3696 261-268 2005 SergioMonteiro MiguelVaz EstelaBicho Attractor Dynamics Generates Robot Formation: from Theory to Implementation. IEEE 2582-2586 2004 AlbertoBarbosaRaposo AdailtonJosé Alves DaCruz Alessandrode LimaBicho AlfredoK.Kojima CarlosA. M. dosSantos IslaC. F. daSilva LéoPiniMagalhães PauloC. P. deAndrade Ferramentas de Programação Livres para Computação Gráfica e Animação por Computador. RITA 7 7-42 2000 JorgeSemião JuanJ.Rodríguez-Andina FabianVargas MarcelinoBicho DosSantos IsabelC.Teixeira JoãoPauloTeixeira Improving the Tolerance of Pipeline Based Circuits to Power Supply or Temperature Variations. IEEE Computer Society 303-311 2007