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Hybrid Neuronal Architectures for Biomimetic Robot Controllers

Summary: Hybrid Neuronal Architectures for Biomimetic Robot
Abstract - We are developing robots controllers based on
biomimetic design principles. The goal is to realize the adaptive
capabilities of the animal models in natural environments. We
report feasibility studies of a hybrid architecture that instantiates
a command and coordinating level with computed discrete time
map-based (DTM) neuronal networks and the central pattern
generators with analog VLSI electronic neuron (AV) networks.
DTM networks are realized using neurons based on a 1-D or 2-D
Map with two additional parameters that define silent, spiking
and bursting regimes. Electronic neurons based on Hindmarsh-
Rose electronic neurons can be instantiated in analog VLSI and
exhibit similar behavior to discrete components. We have
constructed locomotor CPGs with AV networks that can be
modulated to select different behaviors on the basis of selective
command input. The two technologies can be fused by interfacing
the signals from the DTM circuits directly to the AV CPGs. Using
DTMs we have been able to simulate complex sensory fusion for
rheotaxic behavior based on both hydrodynamic and optical flow


Source: Ayers, Joseph - Marine Science Center & Department of Biology, Northeastern University


Collections: Engineering