Neural & Bio-inspired Processing and Robot Control

Huanqing Wang
Neural & Bio-inspired Processing and Robot Control

Author: Huanqing Wang

Publisher: Frontiers Media SA

ISBN: 9782889456970

Category:

Page: 135

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This Research Topic presents bio-inspired and neurological insights for the development of intelligent robotic control algorithms. This aims to bridge the inter-disciplinary gaps between neuroscience and robotics to accelerate the pace of research and development.

Nonlinear Circuits and Systems for Neuro-inspired Robot Control

Luca PatanèTechnology & Engineering
Nonlinear Circuits and Systems for Neuro-inspired Robot Control

Author: Luca Patanè

Publisher: Springer

ISBN: 9783319733470

Category: Technology & Engineering

Page: 99

View: 441

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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.

Management and Intelligent Decision-Making in Complex Systems: An Optimization-Driven Approach

Ameer Hamza KhanTechnology & Engineering
Management and Intelligent Decision-Making in Complex Systems: An Optimization-Driven Approach

Author: Ameer Hamza Khan

Publisher: Springer Nature

ISBN: 9789811593925

Category: Technology & Engineering

Page: 83

View: 447

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In this book, the authors focus on three aspects related to the development of articulated agents: presenting an overview of high-level control algorithms for intelligent decision-making of articulated agents, experimental study of the properties of soft agents as the end-effector of articulated agents, and accurate management of low-level torque-control loop to accurately control the articulated agents. This book summarizes recent advances related to articulated agents. The motive behind the book is to trigger theoretical and practical research studies related to articulated agents.

Bio-Inspired Systems: Computational and Ambient Intelligence

Joan CabestanyComputers
Bio-Inspired Systems: Computational and Ambient Intelligence

Author: Joan Cabestany

Publisher: Springer Science & Business Media

ISBN: 9783642024771

Category: Computers

Page: 1403

View: 611

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This book constitutes the refereed proceedings of the 10th International Work-Conference on Artificial Neural Networks, IWANN 2009, held in Salamanca, Spain in June 2009. The 167 revised full papers presented together with 3 invited lectures were carefully reviewed and selected from over 230 submissions. The papers are organized in thematic sections on theoretical foundations and models; learning and adaptation; self-organizing networks, methods and applications; fuzzy systems; evolutionary computation and genetic algoritms; pattern recognition; formal languages in linguistics; agents and multi-agent on intelligent systems; brain-computer interfaces (bci); multiobjetive optimization; robotics; bioinformatics; biomedical applications; ambient assisted living (aal) and ambient intelligence (ai); other applications.

Bio-Inspired Locomotion Control of Limbless Robots

Guoyuan LiTechnology & Engineering
Bio-Inspired Locomotion Control of Limbless Robots

Author: Guoyuan Li

Publisher: Springer Nature

ISBN: 9789811983849

Category: Technology & Engineering

Page: 185

View: 576

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This book presents a bio-inspired hierarchical control scheme step by step toward developing limbless robots capable of 3D locomotion, fast reflex response, as well as sophisticated reaction to environmental stimuli. This interdisciplinary book introduces how to combine biological concept with locomotion control of limbless robots. The special features of the book include limbless locomotion classification and control, design of biological locomotor and the integration of sensory information into the locomotor using artificial intelligence methods, and on-site demonstrations of limbless locomotion in different scenarios. The book is suitable for readers with engineering background, especially for researchers focused on bio-inspired robots.

Bioinspired Design and Control of Robots with Intrinsic Compliance

Yongping PanScience
Bioinspired Design and Control of Robots with Intrinsic Compliance

Author: Yongping Pan

Publisher: Frontiers Media SA

ISBN: 9782889661572

Category: Science

Page: 132

View: 840

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This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact.

Bioinspired solutions to the challenges of chemical sensing

Ramon Huerta
Bioinspired solutions to the challenges of chemical sensing

Author: Ramon Huerta

Publisher: Frontiers E-books

ISBN: 2889190951

Category:

Page: 190

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Chemical sensing is likely the most primordial sensory modality that emerged in the evolution of life. Without chemical sensing life on earth would probably not exist. It is used for detecting nutrients, avoiding threats, finding mating partners and various forms of communication and social interaction between animals. The advent of artificial sensors has created a myriad of problems in the areas of chemical detection and identification with applications in food quality and pollution control, chemical threat detection, health monitoring, robot control and even odor and taste synthesis. Efficient algorithms are needed to address the many challenges of chemical sensing in these areas, including (but not limited to) sensitivity levels, sensor drift, concentration invariance of analyte identity and complex mixtures. Defining and improving analysis methods for artificial chemical sensing remains an active research area in engineering and machine learning alike. In the course of evolution animals, bacteria and plants have developed sophisticated methods and algorithms for solving difficult problems in chemical sensing very efficiently. Complex signalling pathways inside single cells can trigger movement toward the source of a nutrient. Complex networks of neurons appear to be able to compute odor types and the distance to a source in turbulent flows. These networks of neurons use a combination of temporal coding, layered structures, simple Hebbian learning rules, reinforcement learning and inhibition to quickly learn about chemical stimuli that are critical for their survival. Olfaction is a vibrant filed of research because recent technological advances allow monitoring and manipulating brain areas inaccessible in the past thus allowing for rapid progress. This is particularly relevant because to this date the best solutions to many general chemical sensing problems are still found in animals rather than artificial devices. Many lessons may yet have to be learned from biological systems to solve the complex problems of chemical sensing with similar success as animals routinely do. This special issue has the ambitious goal of bringing together biologists and engineers to report on biological solutions and engineering approaches to chemical sensing challenges in order to better understand in what aspects both fields can find common ground of discussion and to thus promote novel areas of interdisciplinary research.

Bio-Inspired Self-Organizing Robotic Systems

Yan MengTechnology & Engineering
Bio-Inspired Self-Organizing Robotic Systems

Author: Yan Meng

Publisher: Springer

ISBN: 9783642207600

Category: Technology & Engineering

Page: 275

View: 589

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Self-organizing approaches inspired from biological systems, such as social insects, genetic, molecular and cellular systems under morphogenesis, and human mental development, has enjoyed great success in advanced robotic systems that need to work in dynamic and changing environments. Compared with classical control methods for robotic systems, the major advantages of bio-inspired self-organizing robotic systems include robustness, self-repair and self-healing in the presence of system failures and/or malfunctions, high adaptability to environmental changes, and autonomous self-organization and self-reconfiguration without a centralized control. “Bio-inspired Self-organizing Robotic Systems” provides a valuable reference for scientists, practitioners and research students working on developing control algorithms for self-organizing engineered collective systems, such as swarm robotic systems, self-reconfigurable modular robots, smart material based robotic devices, unmanned aerial vehicles, and satellite constellations.

Bio-Inspired Artificial Intelligence

Dario FloreanoComputers
Bio-Inspired Artificial Intelligence

Author: Dario Floreano

Publisher: MIT Press

ISBN: 9780262547734

Category: Computers

Page: 674

View: 240

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A comprehensive introduction to new approaches in artificial intelligence and robotics that are inspired by self-organizing biological processes and structures. New approaches to artificial intelligence spring from the idea that intelligence emerges as much from cells, bodies, and societies as it does from evolution, development, and learning. Traditionally, artificial intelligence has been concerned with reproducing the abilities of human brains; newer approaches take inspiration from a wider range of biological structures that that are capable of autonomous self-organization. Examples of these new approaches include evolutionary computation and evolutionary electronics, artificial neural networks, immune systems, biorobotics, and swarm intelligence—to mention only a few. This book offers a comprehensive introduction to the emerging field of biologically inspired artificial intelligence that can be used as an upper-level text or as a reference for researchers. Each chapter presents computational approaches inspired by a different biological system; each begins with background information about the biological system and then proceeds to develop computational models that make use of biological concepts. The chapters cover evolutionary computation and electronics; cellular systems; neural systems, including neuromorphic engineering; developmental systems; immune systems; behavioral systems—including several approaches to robotics, including behavior-based, bio-mimetic, epigenetic, and evolutionary robots; and collective systems, including swarm robotics as well as cooperative and competitive co-evolving systems. Chapters end with a concluding overview and suggested reading.