The paradigm of Cellular Non-linear Networks is ubiquitously applied in different research fields. In this chapter the breakthrough in bio-robotics and brain science research is focused. In particular the implementation of CNN-based CPGs is discussed proposing different implementations on bio-inspired robots: hexapods, lamprey-like structures, crab-inspired platforms and others. Furthermore the locomotion control system has been extended following a bottom-up procedure to include higher cognitive capabilities. The CNN paradigm was applied to design and implement perceptual architecture inspired by the insect world. Reaction-Diffusion CNN systems have been used to model the arousal of behavioral solution optimized to the on-going environmental conditions. An approach based on Turing patterns is illustrated including experimental results on navigation control with a roving robot. Finally, interesting works based on the olfactory system of insects, modeled with the Winner-less Competition principle, are reported and discussed.
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