Mem-elements for Neuromorphic Circuits with Artificial Intelligence Applications illustrates recent advances in the field of mem-elements (memristor, memcapacitor, meminductor) and their applications in nonlinear dynamical systems, computer science, analog and digital systems, and in neuromorphic circuits and artificial intelligence. The book is mainly devoted to recent results, critical aspects and perspectives of ongoing research on relevant topics, all involving networks of mem-elements devices in diverse applications. Sections contribute to the discussion of memristive materials and transport mechanisms, presenting various types of physical structures that can be fabricated to realize mem-elements in integrated circuits and device modeling. As the last decade has seen an increasing interest in recent advances in mem-elements and their applications in neuromorphic circuits and artificial intelligence, this book will attract researchers in various fields.

Control Theory in Biomedical Engineering: Applications in Physiology and Medical Robotics highlights the importance of control theory and feedback control in our lives and explains how this theory is central to future medical developments. Control theory is fundamental for understanding feedback paths in physiological systems (endocrine system, immune system, neurological system) and a concept for building artificial organs. The book is suitable for graduate students and researchers in the control engineering and biomedical engineering fields, and medical students and practitioners seeking to enhance their understanding of physiological processes, medical robotics (legs, hands, knees), and controlling artificial devices (pacemakers, insulin injection devices). Control theory profoundly impacts the everyday lives of a large part of the human population including the disabled and the elderly who use assistive and rehabilitation robots for improving the quality of their lives and increasing their independence.

Advanced Distributed Consensus for Multiagent Systems contributes to the further development of advanced distributed consensus methods for different classes of multiagent methods. The book expands the field of coordinated multiagent dynamic systems, including discussions on swarms, multi-vehicle and swarm robotics. In addition, it addresses advanced distributed methods for the important topic of multiagent systems, with a goal of providing a high-level treatment of consensus to different versions while preserving systematic analysis of the material and providing an accounting to math development in a unified way. This book is suitable for graduate courses in electrical, mechanical and computer science departments. Consensus control in multiagent systems is becoming increasingly popular among researchers due to its applicability in analyzing and designing coordination behaviors among agents in multiagent frameworks. Multiagent systems have been a fascinating subject amongst researchers as their practical applications span multiple fields ranging from robotics, control theory, systems biology, evolutionary biology, power systems, social and political systems to mention a few.

Discrete Networked Dynamic Systems: Analysis and Performance provides a high-level treatment of a general class of linear discrete-time dynamic systems interconnected over an information network, exchanging relative state measurements or output measurements. It presents a systematic analysis of the material and provides an account to the math development in a unified way. The topics in this book are structured along four dimensions: Agent, Environment, Interaction, and Organization, while keeping global (system-centered) and local (agent-centered) viewpoints. The focus is on the wide-sense consensus problem in discrete networked dynamic systems. The authors rely heavily on algebraic graph theory and topology to derive their results. It is known that graphs play an important role in the analysis of interactions between multiagent/distributed systems. Graph-theoretic analysis provides insight into how topological interactions play a role in achieving coordination among agents. Numerous types of graphs exist in the literature, depending on the edge set of G. A simple graph has no self-loop or edges. Complete graphs are simple graphs with an edge connecting any pair of vertices. The vertex set in a bipartite graph can be partitioned into disjoint non-empty vertex sets, whereby there is an edge connecting every vertex in one set to every vertex in the other set. Random graphs have fixed vertex sets, but the edge set exhibits stochastic behavior modeled by probability functions. Much of the studies in coordination control are based on deterministic/fixed graphs, switching graphs, and random graphs.

Industry 4.0 and the subsequent automation and digitalization of processes, including the tighter integration of machine-machine and human-machine intercommunication and collaboration, is adding additional complexity to future systems design and the capability to simulate, optimize, and adapt. Current solutions lack the ability to capture knowledge, techniques, and methods to create a sustainable and intelligent nerve system for enterprise systems. With the ability to innovate new designs and solutions, as well as automate processes and decision-making capabilities with heterogenous and holistic views of current and future challenges, there can be an increase in productivity and efficiency through sustainable automation. Therefore, better understandings of the underpinning knowledge and expertise of sustainable automation that can create a sustainable cycle that drives optimal automation and innovation in the field is needed Driving Innovation and Productivity Through Sustainable Automation enhances the understanding and the knowledge for the new ecosystems emerging in the Fourth Industrial Revolution. The chapters provide the knowledge and understanding of current challenges and new capabilities and solutions having been researched, developed, and applied within the industry to drive sustainable automation for innovation and productivity. This book is ideally intended for managers, executives, IT specialists, practitioners, stakeholders, researchers, academicians, and students who are interested in the current research on sustainable automation.

The current literature on dynamic systems is quite comprehensive, and system theory's mathematical jargon can remain quite complicated. Thus, there is a need for a compendium of accessible research that involves the broad range of fields that dynamic systems can cover, including engineering, life sciences, and the environment, and which can connect researchers in these fields. The Handbook of Research on Modeling, Analysis, and Control of Complex Systems is a comprehensive reference book that describes the recent developments in a wide range of areas including the modeling, analysis, and control of dynamic systems, as well as explores related applications. The book acts as a forum for researchers seeking to understand the latest theory findings and software problem experiments. Covering topics that include chaotic maps, predictive modeling, random bit generation, and software bug prediction, this book is ideal for professionals, academicians, researchers, and students in the fields of electrical engineering, computer science, control engineering, robotics, power systems, and biomedical engineering.

Industrial automation is driving the development of robot manipulators in various applications, with much of the research effort focussed on flexible manipulators and their advantages compared to their rigid counterparts. This book reports recent advances and new developments in the analysis and control of these robot manipulators. After a general overview of flexible manipulators the book introduces a range of modelling and simulation techniques based on the Lagrange equation formulation, parametric approaches based on linear input/output models using system identification techniques, neuro-modelling approaches, and numerical techniques for dynamic characterisation using finite difference and finite element techniques. Control techniques are then discussed, including a range of open-loop and closed-loop control techniques based on classical and modern control methods including neuro and iterative control, and a range of soft-computing control techniques based on fuzzy logic, neural networks, and evolutionary and bio-inspired optimisation paradigms. Finally the book presents SCEFMAS, a software environment for analysis, design, simulation and control of flexible manipulators. Flexible Robot Manipulators is essential reading for advanced students of robotics, mechatronics and control engineering and will serve as a source of reference for research in areas of modelling, simulation and control of dynamic flexible structures in general and, specifically, of flexible robotic manipulators.

A comprehensive exploration of the control schemes of human-robot interactions In Human-Robot Interaction Control Using Reinforcement Learning, an expert team of authors delivers a concise overview of human-robot interaction control schemes and insightful presentations of novel, model-free and reinforcement learning controllers. The book begins with a brief introduction to state-of-the-art human-robot interaction control and reinforcement learning before moving on to describe the typical environment model. The authors also describe some of the most famous identification techniques for parameter estimation. Human-Robot Interaction Control Using Reinforcement Learning offers rigorous mathematical treatments and demonstrations that facilitate the understanding of control schemes and algorithms. It also describes stability and convergence analysis of human-robot interaction control and reinforcement learning based control. The authors also discuss advanced and cutting-edge topics, like inverse and velocity kinematics solutions, H2 neural control, and likely upcoming developments in the field of robotics. Readers will also enjoy: A thorough introduction to model-based human-robot interaction control Comprehensive explorations of model-free human-robot interaction control and human-in-the-loop control using Euler angles Practical discussions of reinforcement learning for robot position and force control, as well as continuous time reinforcement learning for robot force control In-depth examinations of robot control in worst-case uncertainty using reinforcement learning and the control of redundant robots using multi-agent reinforcement learning Perfect for senior undergraduate and graduate students, academic researchers, and industrial practitioners studying and working in the fields of robotics, learning control systems, neural networks, and computational intelligence, Human-Robot Interaction Control Using Reinforcement Learning is also an indispensable resource for students and professionals studying reinforcement learning.

Handbook of Robotic and Image-Guided Surgery provides state-of-the-art systems and methods for robotic and computer-assisted surgeries. In this masterpiece, contributions of 169 researchers from 19 countries have been gathered to provide 38 chapters. This handbook is 744 pages, includes 659 figures and 61 videos. It also provides basic medical knowledge for engineers and basic engineering principles for surgeons. A key strength of this text is the fusion of engineering, radiology, and surgical principles into one book.

This book is designed primarily as a laboratory operations manual for fundamental mechatronics and robotics experiential and project-based learning. It is also ordered in that starting with the Tricycle Robot, students build up their knowledge and experience of programming to be able to tackle the Rickshaw Robot and finally the most complex robot, i.e., the Hexapod Robot. The book is aimed at university and college students; however, with robotics curricula extending down into lower grades this book can also be very useful for teachers at any school level. Furthermore, the book provides useful ideas for driverless vehicles and robots, as well as for educators who are developing practical project-based teaching and learning modules. Readers of the book can easily modify the coding, computing language, and hardware to suit personal preferences.

While human capabilities can withstand broad levels of strain, they cannot hope to compete with the advanced abilities of automated technologies. Developing advanced robotic systems will provide a better, faster means to produce goods and deliver a level of seamless communication and synchronization that exceeds human skill. Advanced Robotics and Intelligent Automation in Manufacturing is a pivotal reference source that provides vital research on the application of advanced manufacturing technologies in regards to production speed, quality, and innovation. While highlighting topics such as human-machine interaction, quality management, and sensor integration, this publication explores state-of-the-art technologies in the field of robotics engineering as well as human-robot interaction. This book is ideally designed for researchers, students, engineers, manufacturers, managers, industry professionals, and academicians seeking to enhance their innovative design capabilities.

Robots have come a long way thanks to advances in sensing and computer vision technologies and can be found today in healthcare, medicine and industry. Researchers have been looking at providing them with senses such as the ability to see, smell, hear and perceive touch in order to mimic and interact with humans and their surrounding environments. Topics covered in this edited book include various types of sensors used in robotics, sensing schemes (e-skin, tactile skin, e-nose, neuromorphic vision and touch), sensing technologies and their applications including healthcare, prosthetics, robotics and wearables. This book will appeal to researchers, scientists, engineers, and graduate and advanced students working in robotics, sensor technologies and electronics, and their applications in robotics, haptics, prosthetics, wearable and interactive systems, cognitive engineering, neuro-engineering, computational neuroscience, medicine and healthcare technologies.

Biomimetic research is an emerging field that aims to draw inspiration and substances from natural sources and create biological systems in structure, mechanism, and function through robotics. The products have a wide array of application including surgical robots, prosthetics, neurosurgery, and biomedical image analysis. The Handbook of Research on Biomimetics and Biomedical Robotics provides emerging research on robotics, mechatronics, and the application of biomimetric design. While highlighting mechatronical challenges in today's society, readers will find new opportunities and innovations in design capabilities in intelligent robotics and interdisciplinary biomedical products. This publication is a vital resource for senior and graduate students, researchers, and scientists in engineering seeking current research on best ways to globally expand online higher education.

Path Planning for Vehicles Operating in Uncertain 2D-environments presents a survey that includes several path planning methods developed using fuzzy logic, grapho-analytical search, neural networks, and neural-like structures, procedures of genetic search, and unstable motion modes.

Cellular Actuators: Modularity and Variability in Muscle-Inspired Actuation describes the roles actuators play in robotics and their insufficiency in emerging new robotic applications, such as wearable devices and human co-working robots where compactness and compliance are important. Piezoelectric actuators, the topic of this book, provide advantages like displacement scale, force, reliability, and compactness, and rely on material properties to provide displacement and force as reactions to electric stimulation. The authors, renowned researchers in the area, present the fundamentals of muscle-like movement and a system-wide study that includes the design, analysis, and control of biologically inspired actuators. This book is the perfect guide for researchers and practitioners who would like to deploy this technology into their research and products.

Autonomic networking aims to solve the mounting problems created by increasingly complex networks, by enabling devices and service-providers to decide, preferably without human intervention, what to do at any given moment, and ultimately to create self-managing networks that can interface with each other, adapting their behavior to provide the best service to the end-user in all situations. This book gives both an understanding and an assessment of the principles, methods and architectures in autonomous network management, as well as lessons learned from, the ongoing initiatives in the field. It includes contributions from industry groups at Orange Labs, Motorola, Ericsson, the ANA EU Project and leading universities. These groups all provide chapters examining the international research projects to which they are contributing, such as the EU Autonomic Network Architecture Project and Ambient Networks EU Project, reviewing current developments and demonstrating how autonomic management principles are used to define new architectures, models, protocols, and mechanisms for future network equipment.

There have been major recent advances in robotic systems that can replace humans in undertaking hazardous activities in demanding or dangerous environments. Published in association with the CLAWAR (Climbing and Walking Robots and Associated Technologies Association) (www.clawar.org), this important book reviews the development of robotic systems for de-mining and other risky activities such as fire-fighting. Part one provides an overview of the use of robots for humanitarian de-mining work. Part two discusses the development of sensors for mine detection whilst Part thee reviews developments in both teleoperated and autonomous robots. Building on the latter, Part four concentrates on robot autonomous navigation. The final part of the book reviews research on multi-agent-systems (MAS) and the multi-robotics-systems (MRS), promising tools that take into account modular design of mobile robots and the use of several robots in multi-task missions. With its distinguished editors and international team of contributors, Using robots in hazardous environments: landmine detection, de-mining and other applications is a standard reference for all those researching the use of robots in hazardous environments as well as government and other agencies wishing to use robots for dangerous tasks such as landmine detection and disposal.