Influenced by the results obtained in neuroscience and biology, we have introduced a model (AIRM) that, inspired by biological rhythms, adaptively controls a behavior based robotic system (BBRS). The proposed model is implemented by means of an NSP (Neuro Symbolic Processor). Since the NSP can be implemented on FPGA, we can take advantage of a parallel execution of the AIRM model and then an improvement of the BBRS performance.

A neural network generating adaptive rhythms for controlling Behavior Based Robotic Systems

De Gregorio M;
2008

Abstract

Influenced by the results obtained in neuroscience and biology, we have introduced a model (AIRM) that, inspired by biological rhythms, adaptively controls a behavior based robotic system (BBRS). The proposed model is implemented by means of an NSP (Neuro Symbolic Processor). Since the NSP can be implemented on FPGA, we can take advantage of a parallel execution of the AIRM model and then an improvement of the BBRS performance.
2008
Istituto di Scienze Applicate e Sistemi Intelligenti "Eduardo Caianiello" - ISASI
978-1-4244-3219-6
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/83147
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