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Nonlinear circuits and systems for n...

Arena, Paolo.

Nonlinear circuits and systems for neuro-inspired robot control

Record Type:	Electronic resources : Monograph/item
Title/Author:	Nonlinear circuits and systems for neuro-inspired robot controlby Luca Patane, Roland Strauss, Paolo Arena.
Author:	Patane, Luca.
other author:	Strauss, Roland.
Published:	Cham :Springer International Publishing :2018.
Description:	xii, 99 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	RobotsControl systems.
Online resource:	http://dx.doi.org/10.1007/978-3-319-73347-0
ISBN:	9783319733470$q(electronic bk.)

Nonlinear circuits and systems for neuro-inspired robot control
Patane, Luca.

Nonlinear circuits and systems for neuro-inspired robot control[electronic resource] /by Luca Patane, Roland Strauss, Paolo Arena. - Cham :Springer International Publishing :2018. - xii, 99 p. :ill., digital ;24 cm. - SpringerBriefs in applied sciences and technology,2191-530X. - SpringerBriefs in applied sciences and technology..

Biological Investigation of Neural Circuits in the Insect Brain -- Nonlinear Neuro-inspired Circuits and Systems: Processing and Learning Issues -- Modelling Spatial Memory -- Controlling and Learning Motor Function -- Learning Spatio-temporal Behavioural Sequences -- Towards Neural Reusable Neuro-inspired Systems -- Summary and Conclusions.

This book guides readers along a path that proceeds from neurobiology to nonlinear-dynamical circuits, to nonlinear neuro-controllers and to bio-inspired robots. It provides a concise exploration of the essence of neural processing in simple animal brains and its adaptation and extrapolation to modeling, implementation, and realization of the analogous emergent features in artificial but bio-inspired robots: an emerging research field. The book starts with a short presentation of the main areas of the Drosophila brain. These are modeled as nonlinear dynamical structures, which are then used to showcase key features like locomotion, motor learning, memory formation, and exploitation. It also discusses additional complex behaviors, such as sequence learning and perception, which have recently been discovered to exist in insects. Much of the material presented has been tested in biorobotics classes for the Master's degree in Automation Engineering and Control of Complex Systems at the University of Catania. Reporting on the work fostered by several national and international research projects, the book offers researchers novel ideas on how neuro-inspired dynamics can be used in developing the autonomous machines of the future.

ISBN: 9783319733470$q(electronic bk.)

Standard No.: 10.1007/978-3-319-73347-0doiSubjects--Topical Terms:

182098
Robots
--Control systems.

LC Class. No.: TJ211.35 / .P383 2018

Dewey Class. No.: 629.892

Nonlinear circuits and systems for neuro-inspired robot control
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520 $a This book guides readers along a path that proceeds from neurobiology to nonlinear-dynamical circuits, to nonlinear neuro-controllers and to bio-inspired robots. It provides a concise exploration of the essence of neural processing in simple animal brains and its adaptation and extrapolation to modeling, implementation, and realization of the analogous emergent features in artificial but bio-inspired robots: an emerging research field. The book starts with a short presentation of the main areas of the Drosophila brain. These are modeled as nonlinear dynamical structures, which are then used to showcase key features like locomotion, motor learning, memory formation, and exploitation. It also discusses additional complex behaviors, such as sequence learning and perception, which have recently been discovered to exist in insects. Much of the material presented has been tested in biorobotics classes for the Master's degree in Automation Engineering and Control of Complex Systems at the University of Catania. Reporting on the work fostered by several national and international research projects, the book offers researchers novel ideas on how neuro-inspired dynamics can be used in developing the autonomous machines of the future.
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