Nonlinear Circuits And Systems For Neuro Inspired Robot Control


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Nonlinear Circuits and Systems for Neuro-inspired Robot Control


Nonlinear Circuits and Systems for Neuro-inspired Robot Control

Author: Luca Patanè

language: en

Publisher: Springer

Release Date: 2018-03-20


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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.

Biology-Inspired Engineering and Engineering-Inspired Biology


Biology-Inspired Engineering and Engineering-Inspired Biology

Author: Jan-Matthias Braun

language: en

Publisher: Frontiers Media SA

Release Date: 2021-01-04


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Bio-inspired Emergent Control of Locomotion Systems


Bio-inspired Emergent Control of Locomotion Systems

Author: Mattia Frasca

language: en

Publisher: World Scientific

Release Date: 2004


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This book deals with locomotion control of biologically inspired robots realized through an analog circuital paradigm as cellular nonlinear networks. It presents a general methodology for the control of bio-inspired robots and several case studies, as well as describes a new approach to motion control and the related circuit architecture.