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Synchronization of Internal Neural Rhythms in Multi-Robotic Systems

Fraunhofer Institute for Autonomous Intelligent Systems, Sankt Augustin, Germany, Bernstein Center for Computational Neuroscience, University of Göttingen, Germany, steffen_wischmann{at}web.de

Martin Hülse

Fraunhofer Institute for Autonomous Intelligent Systems, Sankt Augustin, Germany, martin.huelse{at}ais.fraunhofer.de

Johannes F. Knabe

Fraunhofer Institute for Autonomous Intelligent Systems, Sankt Augustin, Germany, j.f.knabe{at}herts.ac.uk

Frank Pasemann

Fraunhofer Institute for Autonomous Intelligent Systems, Sankt Augustin, Germany, frank.pasemann{at}ais.fraunhofer.de

This paper introduces a method for the coordination of individual action within a group of robots that have to accomplish a common task, gathering energy in a dynamic environment and transferring this energy to a nest. Each individual behavioral pattern is driven by an internal neural rhythm generator exhibiting quasi-periodic oscillations. The paper describes the implementation of this generator, its influence on the dynamics of artificial recurrent neural networks controlling the robots, and the synchronization of internal rhythms with differing frequencies in a group of situated and embodied robots. Synchronization is achieved either by environmental stimuli or even by self-organizing processes solely based on local interactions within a robot population of up to 150 robots. The proposed experimental methodology is used as a bottom-up approach and starting point for answering the question about the complexity required at the individual level to generate sophisticated behavioral patterns at the group level

Key Words: recurrent neural networks • neural behavior control • minimally cognitive behavior • swarm robotics • behavior coordination

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