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Robotized Transcranial Magnetic Stimulation
by Lars RichterRobotized Transcranial Magnetic Stimulation describes the methods needed to develop a robotic system that is clinically applicable for the application of transcranial magnetic stimulation (TMS). Chapter 1 introduces the basic principles of TMS and discusses current developments towards robotized TMS. Part I (Chapters 2 and 3) systematically analyzes and clinically evaluates robotized TMS. More specifically, it presents the impact of head motion on the induced electric field. In Part II (Chapters 3 to 8), a new method for a robust robot/camera calibration, a sophisticated force-torque control with hand-assisted positioning, a novel FTA-sensor for system safety, and techniques for direct head tracking, are described and evaluated. Part III discusses these developments in the context of safety and clinical applicability of robotized TMS and presents future prospects of robotized TMS. Robotized Transcranial Magnetic Stimulation is intended for researchers as a guide for developing effective robotized TMS solutions. Professionals and practitioners may also find the book valuable.
Robots Helping Humans (A True Book)
by Natasha VizcarraHow do robots help humans? Discover the latest advancements with this book for young readers.Robots have been helping humans for many years. You can probably spot a few robots at work right at home or in your own neighborhood. But did you know that robots also accomplish some of the most dangerous—and often icky—jobs people need to do? Robots are at work in the deepest oceans, inside of sewers, and even inside people’s bodies! Robots Helping Humans uses engaging, interactive text—including critical-thinking questions—to introduce readers to how robotics have changed our lives for the better.ABOUT THIS SERIES:The world of media and technology is changing fast-and young students are right there in the thick of it. As children try to make sense of new technologies, they face a variety of critical issues, including how to access reliable sources of information, how to protect themselves online, and how to use technology in mindful and respectful ways. That's where the books in the Our Digital Future series can help. Each title has been developed to help young readers think critically and navigate new technologies with confidence and care
Robots Unlimited: Life in a Virtual Age
by David LevyConsider this: Robots will one day be able to write poetry and prose so touching that it will make men weep; compose dozens or even hundreds of symphonies that will rival the work of Mozart; judge a court case with absolute impartiality and fairness; or even converse with the natural ease of your best friend. Robots will one day be so life-like tha
Robots and Art
by Damith Herath Christian Kroos StelarcThe first compendium on robotic art of its kind, this book explores theintegration of robots into human society and our attitudes, fears and hopes ina world shared with autonomous machines. It raises questions about thebenefits, risks and ethics of the transformative changes to society that are the consequence of robotstaking on new roles alongside humans. It takes the reader on a journey into the world of the strange,the beautiful, the uncanny and the daring - and into the minds and works ofsome of the world's most prolific creators of robotic art. Offering anin-depth look at robotic art from the viewpoints of artists, engineers andscientists, it presentsoutstanding works of contemporary robotic art and brings together for the first time some of themost influential artists in this area in the last three decades. Starting froma historical review, this transdisciplinary work explores the nexus betweenrobotic research and the arts andexamines the diversityof robotic art, the encounter with robotic otherness, machine embodiment andhuman-robot interaction. Stories of difficulties, pitfalls and successes arerecalled, characterising the multifaceted collaborations across the diversedisciplines required to create robotic art. Although the book isprimarily targeted towards researchers, artists and students in robotics,computer science and the arts,its accessible style appeals to anyone intrigued by robots and the arts.
Robots and Lattice Automata
by Georgios Ch. Sirakoulis Andrew AdamatzkyThe book gives a comprehensive overview of the state-of-the-art research and engineering in theory and application of Lattice Automata in design and control of autonomous Robots. Automata and robots share the same notional meaning. Automata (originated from the latinization of the Greek word "αυτματον") as self-operating autonomous machines invented from ancient years can be easily considered the first steps of robotic-like efforts. Automata are mathematical models of Robots and also they are integral parts of robotic control systems. A Lattice Automaton is a regular array or a collective of finite state machines, or automata. The Automata update their states by the same rules depending on states of their immediate neighbours. In the context of this book, Lattice Automata are used in developing modular reconfigurable robotic systems, path planning and map exploration for robots, as robot controllers, synchronisation of robot collectives, robot vision, parallel robotic actuators. All chapters are written in an accessible manner and lavishly illustrated. The book will help computer and robotic scientists and engineers to understand mechanisms of decentralised functioning of robotic collectives and to design future and emergent reconfigurable, parallel and distributed robotic systems.
Robots in Care and Everyday Life: Future, Ethics, Social Acceptance (SpringerBriefs in Sociology)
by Uwe EngelThis open access book presents detailed findings about the ethical, legal, and social acceptance of robots in the German and European context. The key resource is the Bremen AI Delphi survey of scientists and politicians and a related population survey. The focus is on trust in robotic assistance, human willingness to use this assistance, and the expected personal well-being in human-robot interaction. Using recent data from Eurostat, the European Social Survey, and the Eurobarometer survey, the analysis is extended to Germany and the EU. The acceptance of robots in care and everyday life is viewed against their acceptance in other contexts of life and the scientific research. The book reports on how the probability of five complex future scenarios is evaluated by experts and politicians. These scenarios cover a broad range of topics, including the worst-case scenario of cutthroat competition for jobs, the wealth promise of AI, communication in human-robot interaction, robotic assistance, and ethical and legal conflicts. International economic competition alone will ensure that countries invest sustainably in the future technologies of AI and robots. But will these technologies also be accepted by the population? The book raises the core issue of how governments can gain the needed social, ethical, and user acceptance of AI and robots in everyday life. This highly topical book is of interest to researchers, professionals and policy makers working on various aspects of human-robot interaction. This is an open access book.
Robots in Education: An Introduction to High-Tech Social Agents, Intelligent Tutors, and Curricular Tools
by Massimiliano Cappuccio Friederike Eyssel Paul Baxter Tony Belpaeme Christoph Bartneck Fady Alnajjar Cinzia Di Dio Jürgen Handke Omar Mubin Mohammad Obaid Natalia Reich-StiebertRobots in Education is an accessible introduction to the use of robotics in formal learning, encompassing pedagogical and psychological theories as well as implementation in curricula. Today, a variety of communities across education are increasingly using robots as general classroom tutors, tools in STEM projects, and subjects of study. This volume explores how the unique physical and social-interactive capabilities of educational robots can generate bonds with students while freeing instructors to focus on their individualized approaches to teaching and learning. Authored by a uniquely interdisciplinary team of scholars, the book covers the basics of robotics and their supporting technologies; attitudes toward and ethical implications of robots in learning; research methods relevant to extending our knowledge of the field; and more.
Robots, Automation and the Innovation Economy (Routledge Studies in the Economics of Innovation)
by Jon-Arild JohannessenCascades of new technologies and innovations are entering our lives so fast that it is difficult for us to adapt to one innovation before the next becomes embedded into our everyday lives. What happens when the changes brought by technology are so profound that they affect all aspects of our lives? This book explores the potential impact of artificial intelligence (AI) and intelligent robots on individuals, organizations and society, specifically examining the impact on jobs and workplaces in the future. It provides an understanding of how we can adapt to changes that appear like flocks of black swans.Five key areas are unpacked in the book: automation, AI, (the significance of AI technology), innovation, competence transformation, and the fact that the pace of change is so rapid that it outstrips our ability to adapt to consecutive changes. The main objective is to show how AI will change society and how we as individuals and society must adapt in order to survive what the author terms ‘robot shock’, together with its consequences and after-effects. It offers a greater understanding of resistance to change and how we need to adopt strategies for adapting to major changes. Each of the book’s six chapters also contains policy inputs, framed as propositions, that are intended specifically for decision-makers. The book concludes by offering possible strategies for overcoming the negative effects of ‘robot shock’.The book intends to send a message to leaders of institutions, decision-makers and anyone attempting to understand and explain how we – as a social system – can succeed in tackling the many major challenges and crises faced by humanity.
Robust Argumentation Machines: First International Conference, RATIO 2024, Bielefeld, Germany, June 5–7, 2024, Proceedings (Lecture Notes in Computer Science #14638)
by Michael Kohlhase Philipp Cimiano Benno Stein Anette FrankThis open access book constitutes the proceedings of the First International Conference on Robust Argumentation Machines, RATIO 2024, which took place in Bielefeld, Germany, during June 5-7, 2024. The 20 full papers and 1 short paper included in the proceedings were carefully reviewed and selected from 24 submissions. They were organized in topical sections as follows: Argument Mining; Debate Analysis and Deliberation; Argument Acquisition, Annotation and Quality Assessment; Computational Models of Argumentation; Interactive Argumentation, Recommendation and Personalization; and Argument Search and Retrieval.
Robust Cloud Integration with Azure
by Abhishek Kumar Gyanendra Kumar Gautam James Corbould Mahindra Morar Martin AbbottUnleash the power of serverless integration with Azure About This Book • Build and support highly available and scalable API Apps by learning powerful Azure-based cloud integration • Deploy and deliver applications that integrate seamlessly in the cloud and quickly adapt as per your integration needs • Deploy hybrid applications that work and integrate on the cloud (using Logic Apps and BizTalk Server) Who This Book Is For This book is for Microsoft Enterprise developers, DevOps, and IT professionals who would like to use Azure App Service and Microsoft Cloud Integration technologies to create cloud-based web and mobile apps. What You Will Learn • Explore new models of robust cloud integration in Microsoft Azure • Create your own connector and learn how to publish and manage it • Build reliable, scalable, and secure business workflows using Azure Logic Apps • Simplify SaaS connectivity with Azure using Logic Apps • Connect your on-premises system to Azure securely • Get to know more about Logic Apps and how to connect to on-premises “line-of-business” applications using Microsoft BizTalk Server In Detail Microsoft is focusing heavily on Enterprise connectivity so that developers can build scalable web and mobile apps and services in the cloud. In short, Enterprise connectivity from anywhere and to any device. These integration services are being offered through powerful Azure-based services. This book will teach you how to design and implement cloud integration using Microsoft Azure. It starts by showing you how to build, deploy, and secure the API app. Next, it introduces you to Logic Apps and helps you quickly start building your integration applications. We'll then go through the different connectors available for Logic Apps to build your automated business process workflow. Further on, you will see how to create a complex workflow in Logic Apps using Azure Function. You will then add a SaaS application to your existing cloud applications and create Queues and Topics in Service Bus on Azure using Azure Portal. Towards the end, we'll explore event hubs and IoT hubs, and you'll get to know more about how to tool and monitor the business workflow in Logic Apps. Using this book, you will be able to support your apps that connect to data anywhere—be it in the cloud or on-premises. Style and approach This practical hands-on tutorial shows you the full capability of App Service and other Azure-based integration services to build scalable and highly available web and mobile apps. It helps you successfully build and support your applications in the cloud or on-premises successfully. We'll debunk the popular myth that switching to cloud is risky—it's not!
Robust Cluster Analysis and Variable Selection (ISSN)
by Gunter RitterClustering remains a vibrant area of research in statistics. Although there are many books on this topic, there are relatively few that are well founded in the theoretical aspects. In Robust Cluster Analysis and Variable Selection, Gunter Ritter presents an overview of the theory and applications of probabilistic clustering and variable selection,
Robust Computational Techniques for Boundary Layers
by Grigory I. Shishkin Paul Farrell Alan Hegarty John M. Miller Eugene O'RiordanCurrent standard numerical methods are of little use in solving mathematical problems involving boundary layers. In Robust Computational Techniques for Boundary Layers, the authors construct numerical methods for solving problems involving differential equations that have non-smooth solutions with singularities related to boundary layers. They pres
Robust Computing with Nano-scale Devices
by Chao HuangRobust Nano-Computing focuses on various issues of robust nano-computing, defect-tolerance design for nano-technology at different design abstraction levels. It addresses both redundancy- and configuration-based methods as well as fault detecting techniques through the development of accurate computation models and tools. The contents present an insightful view of the ongoing researches on nano-electronic devices, circuits, architectures, and design methods, as well as provide promising directions for future research.
Robust Control Algorithms for Flexible Manipulators
by Santhakumar Mohan Bidyadhar Subudhi Kshetrimayum Lochan Binoy Krishna RoyVarious modelling and control of two-link flexible manipulators are presented in this book. The lumped parameter modelling method and the assumed modes method modelling are comprehensively reviewed. The book also reviews the trajectory tracking problem and tip trajectory tracking problem along with the suppression of tip deflection of the links. An exponential time varying signal and a chaotic signal are considered as the desired trajectories. The identical/ non-identical slave manipulator is synchronised with the controlled master manipulator so that the slave manipulator indirectly follows the desired manipulator.
Robust Control Design with MATLAB®
by Da-Wei Gu Mihail M Konstantinov Petko H. PetkovRobust Control Design with MATLAB® (second edition) helps the student to learn how to use well-developed advanced robust control design methods in practical cases. To this end, several realistic control design examples from teaching-laboratory experiments, such as a two-wheeled, self-balancing robot, to complex systems like a flexible-link manipulator are given detailed presentation. All of these exercises are conducted using MATLAB® Robust Control Toolbox 3, Control System Toolbox and Simulink®. By sharing their experiences in industrial cases with minimum recourse to complicated theories and formulae, the authors convey essential ideas and useful insights into robust industrial control systems design using major H-infinity optimization and related methods allowing readers quickly to move on with their own challenges. The hands-on tutorial style of this text rests on an abundance of examples and features for the second edition: * rewritten and simplified presentation of theoretical and methodological material including original coverage of linear matrix inequalities; * new Part II forming a tutorial on Robust Control Toolbox 3; * fresh design problems including the control of a two-rotor dynamic system; and * end-of-chapter exercises. Electronic supplements to the written text that can be downloaded from extras.springer.com/isbn include: * M-files developed with MATLAB® help in understanding the essence of robust control system design portrayed in text-based examples; * MDL-files for simulation of open- and closed-loop systems in Simulink®; and * a solutions manual available free of charge to those adopting Robust Control Design with MATLAB® as a textbook for courses. Robust Control Design with MATLAB® is for graduate students and practising engineers who want to learn how to deal with robust control design problems without spending a lot of time in researching complex theoretical developments.
Robust Control Systems with Genetic Algorithms
by Mo Jamshidi Renato A. Krohling Leandro dos S. Coelho Peter J. FlemingIn recent years, new paradigms have emerged to replace-or augment-the traditional, mathematically based approaches to optimization. The most powerful of these are genetic algorithms (GA), inspired by natural selection, and genetic programming, an extension of GAs based on the optimization of symbolic codes.Robust Control Systems with Genetic Algorithms builds a bridge between genetic algorithms and the design of robust control systems. After laying a foundation in the basics of GAs and genetic programming, it demonstrates the power of these new tools for developing optimal robust controllers for linear control systems, optimal disturbance rejection controllers, and predictive and variable structure control. It also explores the application of hybrid approaches: how to enhance genetic algorithms and programming with fuzzy logic to design intelligent control systems. The authors consider a variety of applications, such as the optimal control of robotic manipulators, flexible links and jet engines, and illustrate a multi-objective, genetic algorithm approach to the design of robust controllers with a gasification plant case study.The authors are all masters in the field and clearly show the effectiveness of GA techniques. Their presentation is your first opportunity to fully explore this cutting-edge approach to robust optimal control system design and exploit its methods for your own applications.
Robust Control of Robots
by Marco H. Terra Marcel Bergerman Adriano A. SiqueiraRobust Control of Robots bridges the gap between robust control theory and applications, with a special focus on robotic manipulators. It is divided into three parts: robust control of regular, fully-actuated robotic manipulators;robust post-failure control of robotic manipulators; androbust control of cooperative robotic manipulators.In each chapter the mathematical concepts are illustrated with experimental results obtained with a two-manipulator system. They are presented in enough detail to allow readers to implement the concepts in their own systems, or in Control Environment for Robots, a MATLAB®-based simulation program freely available from the authors. The target audience for Robust Control of Robots includes researchers, practicing engineers, and graduate students interested in implementing robust and fault tolerant control methodologies to robotic manipulators.
Robust Data Mining
by Panos M. Pardalos Petros Xanthopoulos Theodore B. TrafalisData uncertainty is a concept closely related with most real life applications that involve data collection and interpretation. Examples can be found in data acquired with biomedical instruments or other experimental techniques. Integration of robust optimization in the existing data mining techniques aim to create new algorithms resilient to error and noise. This work encapsulates all the latest applications of robust optimization in data mining. This brief contains an overview of the rapidly growing field of robust data mining research field and presents the most well known machine learning algorithms, their robust counterpart formulations and algorithms for attacking these problems. This brief will appeal to theoreticians and data miners working in this field.
Robust Emotion Recognition using Spectral and Prosodic Features
by K. Sreenivasa Rao Shashidhar G. KoolagudiIn this brief, the authors discuss recently explored spectral (sub-segmental and pitch synchronous) and prosodic (global and local features at word and syllable levels in different parts of the utterance) features for discerning emotions in a robust manner. The authors also delve into the complementary evidences obtained from excitation source, vocal tract system and prosodic features for the purpose of enhancing emotion recognition performance. Features based on speaking rate characteristics are explored with the help of multi-stage and hybrid models for further improving emotion recognition performance. Proposed spectral and prosodic features are evaluated on real life emotional speech corpus.
Robust Explainable AI (SpringerBriefs in Intelligent Systems)
by Francesco Leofante Matthew WickerThe area of Explainable Artificial Intelligence (XAI) is concerned with providing methods and tools to improve the interpretability of black-box learning models. While several approaches exist to generate explanations, they are often lacking robustness, e.g., they may produce completely different explanations for similar events. This phenomenon has troubling implications, as lack of robustness indicates that explanations are not capturing the underlying decision-making process of a model and thus cannot be trusted. This book aims at introducing Robust Explainable AI, a rapidly growing field whose focus is to ensure that explanations for machine learning models adhere to the highest robustness standards. We will introduce the most important concepts, methodologies, and results in the field, with a particular focus on techniques developed for feature attribution methods and counterfactual explanations for deep neural networks. As prerequisites, a certain familiarity with neural networks and approaches within XAI is desirable but not mandatory. The book is designed to be self-contained, and relevant concepts will be introduced when needed, together with examples to ensure a successful learning experience.
Robust Image Authentication in the Presence of Noise
by Nataša ŽivićThis book addresses the problems that hinder image authentication in the presence of noise. It considers the advantages and disadvantages of existing algorithms for image authentication and shows new approaches and solutions for robust image authentication. The state of the art algorithms are compared and, furthermore, innovative approaches and algorithms are introduced. The introduced algorithms are applied to improve image authentication, watermarking and biometry. Aside from presenting new directions and algorithms for robust image authentication in the presence of noise, as well as image correction, this book also: Provides an overview of the state of the art algorithms for image authentication in the presence of noise and modifications, as well as a comparison of these algorithms, Presents novel algorithms for robust image authentication, whereby the image is tried to be corrected and authenticated, Examines different views for the solution of problems connected to image authentication in the presence of noise, Shows examples, how the new techniques can be applied to image authentication, watermarking and biometry. This book is written on the one hand for students, who want to learn about image processing, authentication, watermarking and biometry, and on the other hand for engineers and researchers, who work on aspects of robustness against modifications of secure images.
Robust Latent Feature Learning for Incomplete Big Data (SpringerBriefs in Computer Science)
by Di WuIncomplete big data are frequently encountered in many industrial applications, such as recommender systems, the Internet of Things, intelligent transportation, cloud computing, and so on. It is of great significance to analyze them for mining rich and valuable knowledge and patterns. Latent feature analysis (LFA) is one of the most popular representation learning methods tailored for incomplete big data due to its high accuracy, computational efficiency, and ease of scalability. The crux of analyzing incomplete big data lies in addressing the uncertainty problem caused by their incomplete characteristics. However, existing LFA methods do not fully consider such uncertainty. In this book, the author introduces several robust latent feature learning methods to address such uncertainty for effectively and efficiently analyzing incomplete big data, including robust latent feature learning based on smooth L1-norm, improving robustness of latent feature learning using L1-norm, improving robustness of latent feature learning using double-space, data-characteristic-aware latent feature learning, posterior-neighborhood-regularized latent feature learning, and generalized deep latent feature learning. Readers can obtain an overview of the challenges of analyzing incomplete big data and how to employ latent feature learning to build a robust model to analyze incomplete big data. In addition, this book provides several algorithms and real application cases, which can help students, researchers, and professionals easily build their models to analyze incomplete big data.
Robust Machine Learning: Distributed Methods for Safe AI (Machine Learning: Foundations, Methodologies, and Applications)
by Rachid Guerraoui Nirupam Gupta Rafael PinotToday, machine learning algorithms are often distributed across multiple machines to leverage more computing power and more data. However, the use of a distributed framework entails a variety of security threats. In particular, some of the machines may misbehave and jeopardize the learning procedure. This could, for example, result from hardware and software bugs, data poisoning or a malicious player controlling a subset of the machines. This book explains in simple terms what it means for a distributed machine learning scheme to be robust to these threats, and how to build provably robust machine learning algorithms. Studying the robustness of machine learning algorithms is a necessity given the ubiquity of these algorithms in both the private and public sectors. Accordingly, over the past few years, we have witnessed a rapid growth in the number of articles published on the robustness of distributed machine learning algorithms. We believe it is time to provide a clear foundation to this emerging and dynamic field. By gathering the existing knowledge and democratizing the concept of robustness, the book provides the basis for a new generation of reliable and safe machine learning schemes. In addition to introducing the problem of robustness in modern machine learning algorithms, the book will equip readers with essential skills for designing distributed learning algorithms with enhanced robustness. Moreover, the book provides a foundation for future research in this area.
Robust Modelling and Simulation
by Miguel Mujica Mota Idalia Flores De La Mota Antoni Guasch Miquel Angel PieraThis book presents for the first time a methodology that combines the power of a modelling formalism such as colored petri nets with the flexibility of a discrete event program such as SIMIO. Industrial practitioners have seen the growth of simulation as a methodology for tacking problems in which variability is the common denominator. Practically all industrial systems, from manufacturing to aviation are considered stochastic systems. Different modelling techniques have been developed as well as mathematical techniques for formalizing the cause-effect relationships in industrial and complex systems. The methodology in this book illustrates how complexity in modelling can be tackled by the use of coloured petri nets, while at the same time the variability present in systems is integrated in a robust fashion. The book can be used as a concise guide for developing robust models, which are able to efficiently simulate the cause-effect relationships present in complex industrial systems without losing the simulation power of discrete-event simulation. In addition SIMIO's capabilities allows integration of features that are becoming more and more important for the success of projects such as animation, virtual reality, and geographical information systems (GIS).
Robust Motion Detection in Real-Life Scenarios
by Ángel P. Pobil Ester Martínez-MartínThis work proposes a complete sensor-independent visual system that provides robust target motion detection. First, the way sensors obtain images, in terms of resolution distribution and pixel neighbourhood, is studied. This allows a spatial analysis of motion to be carried out. Then, a novel background maintenance approach for robust target motion detection is implemented. Two different situations are considered: a fixed camera observing a constant background where objects are moving; and a still camera observing objects in movement within a dynamic background. This distinction lies on developing a surveillance mechanism without the constraint of observing a scene free of foreground elements for several seconds when a reliable initial background model is obtained, as that situation cannot be guaranteed when a robotic system works in an unknown environment. Other problems are also addressed to successfully deal with changes in illumination, and the distinction between foreground and background elements.