Robots and autonomous agents have permeated every aspect of human life. They are not only omnipresent on the shop floors; they have pervaded our homes and are around us everywhere. Design methodologies and implementation techniques of intelligent machines are making progress in leaps and bounds. Smart interaction, cooperation, and pro-activeness are the hallmarks of modern intelligent machines.

This book deals with the theoretical and methodological aspects of incorporating intelligence in "Autonomous Robots and Agents." Challenges faced in the real world to accomplish complex tasks, which require collaborative efforts, and methods to overcome them, are detailed. Several informative articles deal with navigation, localization and mapping of mobile robots, a problem that engineers and researchers are grappling with all the time.

This edited volume is targeted to present the latest state-of-the-art methodologies in Robotics. It is a compilation of the extended versions of the very best papers selected from the many that were presented at the 3rd International Conference on Autonomous Robots and Agents (ICARA 2006) which was held at Palmerston North, New Zealand from 11-14 December, 2006. Scientists and engineers who work with mobile robots will find this book very useful and stimulating.

Research on humanoid robots has been mostly with the aim of developing robots that can replace humans in the performance of certain tasks. Motion planning for these robots can be quite difficult, due to their complex kinematics, dynamics and environment. It is consequently one of the key research topics in humanoid robotics research and the last few years have witnessed considerable progress in the field. Motion Planning for Humanoid Robots surveys the remarkable recent advancement in both the theoretical and the practical aspects of humanoid motion planning. Various motion planning frameworks are presented in Motion Planning for Humanoid Robots, including one for skill coordination and learning, and one for manipulating and grasping tasks. The problem of planning sequences of contacts that support acyclic motion in a highly constrained environment is addressed and a motion planner that enables a humanoid robot to push an object to a desired location on a cluttered table is described. The main areas of interest include: * whole body motion planning, * task planning, * biped gait planning, and * sensor feedback for motion planning. Torque-level control of multi-contact behavior, autonomous manipulation of moving obstacles, and movement control and planning architecture are also covered. Motion Planning for Humanoid Robots will help readers to understand the current research on humanoid motion planning. It is written for industrial engineers, advanced undergraduate and postgraduate students.

One of the most important methods in dealing with the optimization of large, complex systems is that of hierarchical decomposition. The idea is to reduce the overall complex problem into manageable approximate problems or subproblems, to solve these problems, and to construct a solution of the original problem from the solutions of these simpler prob lems. Development of such approaches for large complex systems has been identified as a particularly fruitful area by the Committee on the Next Decade in Operations Research (1988) [42] as well as by the Panel on Future Directions in Control Theory (1988) [65]. Most manufacturing firms are complex systems characterized by sev eral decision subsystems, such as finance, personnel, marketing, and op erations. They may have several plants and warehouses and a wide variety of machines and equipment devoted to producing a large number of different products. Moreover, they are subject to deterministic as well as stochastic discrete events, such as purchasing new equipment, hiring and layoff of personnel, and machine setups, failures, and repairs.

Mechatronics is a synergic discipline integrating precise mechanics, electrotechnics, electronics and IT technologies. The main goal of mechatronical approach to design of complex products is to achieve new quality of their utility value at reasonable price. Successful accomplishment of this task would not be possible without application of advanced software and hardware tools for simulation of design, technologies and production control and also for simulation of behavior of these products in order to provide the highest possible level of spatial and functional integration of the final product.

This book brings a review of the current state of the art in mechatronics, as presented at the 8th International Conference Mechatronics 2009, organized by the Brno Technical University, Faculty of Mechanical Engineering, Czech Republic. The specific topics of the conference are Modelling and Simulation, Metrology & Diagnostics, Sensorics & Photonics, Control & Robotics, MEMS Design & Mechatronic Products, Production Machines and Biomechanics. The selected contributions provide an insight into the current development of these scientific disciplines, present the new results of research and development and indicate the trends of development in the interdisciplinary field of mechatronic systems. Therefore, the book provides the latest and helpful information both for the R&D specialists and for the designers working in mechatronics and related fields.

This book provides a thorough overview of cutting-edge research on electronics applications relevant to industry, the environment, and society at large. It covers a broad spectrum of application domains, from automotive to space and from health to security, while devoting special attention to the use of embedded devices and sensors for imaging, communication and control. The book is based on the 2015 ApplePies Conference, held in Rome, which brought together researchers and stakeholders to consider the most significant current trends in the field of applied electronics and to debate visions for the future. Areas addressed by the conference included information communication technology; biotechnology and biomedical imaging; space; secure, clean and efficient energy; the environment; and smart, green and integrated transport. As electronics technology continues to develop apace, constantly meeting previously unthinkable targets, further attention needs to be directed toward the electronics applications and the development of systems that facilitate human activities. This book, written by industrial and academic professionals, represents a valuable contribution in this endeavor.

Intelligent Unmanned Ground Vehicles describes the technology developed and the results obtained by the Carnegie Mellon Robotics Institute in the course of the DARPA Unmanned Ground Vehicle (UGV) project. The goal of this work was to equip off-road vehicles with computer-controlled, unmanned driving capabilities. The book describes contributions in the area of mobility for UGVs including: tools for assembling complex autonomous mobility systems; on-road and off-road navigation; sensing techniques; and route planning algorithms. In addition to basic mobility technology, the book covers a number of integrated systems demonstrated in the field in realistic scenarios. The approaches presented in this book can be applied to a wide range of mobile robotics applications, from automated passenger cars to planetary exploration, and construction and agricultural machines. Intelligent Unmanned Ground Vehicles shows the progress that was achieved during this program, from brittle specially-built robots operating under highly constrained conditions, to groups of modified commercial vehicles operating in tough environments. One measure of progress is how much of this technology is being used in other applications. For example, much of the work in road-following, architectures and obstacle detection has been the basis for the Automated Highway Systems (AHS) prototypes currently under development. AHS will lead to commercial prototypes within a few years. The cross-country technology is also being used in the development of planetary rovers with a projected launch date within a few years. The architectural tools built under this program have been used in numerous applications, from an automated harvester to an autonomous excavator. The results reported in this work provide tools for further research development leading to practical, reliable and economical mobile robots.

In the research area of computer science, practitioners are constantly searching for faster platforms with pertinent results. With analytics that span environmental development to computer hardware emulation, problem-solving algorithms are in high demand. Field-Programmable Gate Array (FPGA) is a promising computing platform that can be significantly faster for some applications and can be applied to a variety of fields. FPGA Algorithms and Applications in the IoT, AI, and High-Performance Computing provides emerging research exploring the theoretical and practical aspects of computable algorithms and applications within robotics and electronics development. Featuring coverage on a broad range of topics such as neuroscience, bioinformatics, and artificial intelligence, this book is ideally designed for computer science specialists, researchers, professors, and students seeking current research on cognitive analytics and advanced computing.

Based on interdisciplinary research into "Directional Change", a new data-driven approach to financial data analysis, Detecting Regime Change in Computational Finance: Data Science, Machine Learning and Algorithmic Trading applies machine learning to financial market monitoring and algorithmic trading. Directional Change is a new way of summarising price changes in the market. Instead of sampling prices at fixed intervals (such as daily closing in time series), it samples prices when the market changes direction ("zigzags"). By sampling data in a different way, this book lays out concepts which enable the extraction of information that other market participants may not be able to see. The book includes a Foreword by Richard Olsen and explores the following topics: Data science: as an alternative to time series, price movements in a market can be summarised as directional changes Machine learning for regime change detection: historical regime changes in a market can be discovered by a Hidden Markov Model Regime characterisation: normal and abnormal regimes in historical data can be characterised using indicators defined under Directional Change Market Monitoring: by using historical characteristics of normal and abnormal regimes, one can monitor the market to detect whether the market regime has changed Algorithmic trading: regime tracking information can help us to design trading algorithms It will be of great interest to researchers in computational finance, machine learning and data science. About the Authors Jun Chen received his PhD in computational finance from the Centre for Computational Finance and Economic Agents, University of Essex in 2019. Edward P K Tsang is an Emeritus Professor at the University of Essex, where he co-founded the Centre for Computational Finance and Economic Agents in 2002.

This book provides a decentralized approach for the identification and control of robotics systems. It also presents recent research in decentralized neural control and includes applications to robotics. Decentralized control is free from difficulties due to complexity in design, debugging, data gathering and storage requirements, making it preferable for interconnected systems. Furthermore, as opposed to the centralized approach, it can be implemented with parallel processors. This approach deals with four decentralized control schemes, which are able to identify the robot dynamics. The training of each neural network is performed on-line using an extended Kalman filter (EKF). The first indirect decentralized control scheme applies the discrete-time block control approach, to formulate a nonlinear sliding manifold. The second direct decentralized neural control scheme is based on the backstepping technique, approximated by a high order neural network.The third control scheme applies a decentralized neural inverse optimal control for stabilization. The fourth decentralized neural inverse optimal control is designed for trajectory tracking. This comprehensive work on decentralized control of robot manipulators and mobile robots is intended for professors, students and professionals wanting to understand and apply advanced knowledge in their field of work.

This monograph presents and analyzes the optimization, game-theoretic and simulation models of control mechanisms for ecological-economic systems. It is devoted to integrated assessment mechanisms for total risks and losses, penalty mechanisms, risk payment mechanisms, financing and costs compensation mechanisms for risk level reduction, sales mechanisms for risk level quotas, audit mechanisms, mechanisms for expected losses reduction, economic motivation mechanisms, optimization mechanisms for regional environmental (risk level reduction) programs, and mechanisms for authorities' interests coordination. The book is aiming at undergraduate and postgraduate students, as well as at experts in mathematical modeling and control of ecological economic, socioeconomic and organizational systems.

This book presents a novel decision-making support system based on paraconsistent annotated evidential logic, which directly handles imprecise, incomplete and contradictory data. The authors offer insights into areas such as engineering and biomedicine, as well as related fields. Decision analysis is useful in making choices when the consequences of actions are uncertain, like in business administration, where it assists in making investment decisions, and in health care, Decision analysis is also valuable when the possible actions may lead to conflicting consequences. A fundamental tenet of decision analysis is that even though the available information is incomplete, a decision must be made. Thus, analyses often contain assumptions about or estimates of missing data. The contribution that this method can provide to professionals and companies has significant relevance in terms of the impact of information systems on productivity and quality of the companies; the lack of training companies for proper planning and management of information systems; and the need for interdisciplinary treatment of several sectors of almost all related scientific areas. This book is a valuable resource for professionals seeking a competitive edge in their performance.

Advances in H Control Theory is concerned with state-of-the-art developments in three areas: the extended treatment of mostly deterministic switched systems with dwell-time; the control of retarded stochastic state-multiplicative noisy systems; and a new approach to the control of biochemical systems, exemplified by the threonine synthesis and glycolytic pathways. Following an introduction and extensive literature survey, each of these major topics is the subject of an individual part of the book. The first two parts of the book contain several practical examples taken from various fields of control engineering including aircraft control, robot manipulation and process control. These examples are taken from the fields of deterministic switched systems and state-multiplicative noisy systems. The text is rounded out with short appendices covering mathematical fundamentals: -algebra and the input-output method for retarded systems. Advances in H Control Theory is written for engineers engaged in control systems research and development, for applied mathematicians interested in systems and control and for graduate students specializing in stochastic control.

This book presents a foray into the fascinating process of risk management, beginning from classical methods and approaches to understanding risk all the way into cutting-age thinking. Risk management by necessity must lie at the heart of governing our ever more complex digital societies. New phenomena and activities necessitate a new look at how individuals, firms, and states manage the uncertainty they must operate in. Initial chapters provide an introduction to traditional methods and show how they can be built upon to better understand the workings of the modern economy. Later chapters review digital activities and assets like cryptocurrencies showing how such emergent risks can be conceptualized better. Network theory figures prominently and the book demonstrates how it can be used to gauge the risk in the digital sectors of the economy. Predicting the unpredictable black swan events is also discussed in view of a wider adoption of economic simulations. The journey concludes by looking at how individuals perceive risk and make decisions as they operate in a virtual social network. This book interests the academic audience, but it also features insights and novel research results that are relevant for practitioners and policymakers.

Darwin2K: An Evolutionary Approach to Automated Design for Robotics is an essential reference tool for researchers, professionals, and students involved in robot design or in evolutionary synthesis, design, and optimization. It is also necessary for users of Darwin2K. Researchers and hobbyists interested in genetic algorithms and artificial life techniques will find the book interesting. The primary purpose of this book is to describe a methodology for using computers to automatically design robots to meet the specific needs of an application. Details of many novel aspects of the methodology are presented, including an evolutionary algorithm for synthesizing and optimizing multiple objective functions, an algorithm for dynamic simulation of arbitrary robots, an extensible software architecture, and a new representation for robots that is appropriate for robot design. The methodology as a whole is significant in terms of its impact on robot design practices, and as a case study in building evolutionary design systems. Individual parts of the systems are also relevant to other areas. For example, the evolutionary algorithm can be used for design and optimization problems other than robotics, and the dynamic simulation algorithm can be used for analysis and simulation of existing robots or as a part of a manual design tool. The book also gives an overview of previous work in automated design of robots, and of evolutionary design in other engineering disciplines.

This monograph focuses on characterizing the stability and performance consequences of inserting limited-capacity communication networks within a control loop. The text shows how integration of the ideas of control and estimation with those of communication and information theory can be used to provide important insights concerning several fundamental problems such as: * minimum data rate for stabilization of linear systems over noisy channels; * minimum network requirement for stabilization of linear systems over fading channels; and * stability of Kalman filtering with intermittent observations. A fundamental link is revealed between the topological entropy of linear dynamical systems and the capacities of communication channels. The design of a logarithmic quantizer for the stabilization of linear systems under various network environments is also extensively discussed and solutions to many problems of Kalman filtering with intermittent observations are demonstrated. Analysis and Design of Networked Control Systems will interest control theorists and engineers working with networked systems and may also be used as a resource for graduate students with backgrounds in applied mathematics, communications or control who are studying such systems.

Presents a number of new and potentially useful self-learning (adaptive) control algorithms and theoretical as well as practical results for both unconstrained and constrained finite Markov chains-efficiently processing new information by adjusting the control strategies directly or indirectly.

This up-to-the-minute reference/text provides vital information on new approaches to stability, stabilization, control design, and filtering of electronics and computer systems-explicating the latest developments in time-delay systems (TDS) and uncertain time-delay systems (UTDS). Features helpful appendices detailing important facets of matrix theory, standard lemmas and mathematical results, and applications of industry-tested software Utilizing mathematical formality to foster intuitive understanding, Robust Control and Filtering for Time-Delay Systems discusses finite capabilities of data processing and transmission throughout systems analyzes inherent physical phenomena and computational delays impacting system performance showcases the state-space approach in systems representation and analysis defines and delineates concepts of robustness, robust performance, and robust design highlights linear and many classes of nonlinear system theory, matrix theory, and modern control theory describes delays as constant or time-varying, known or unknown, deterministic or stochastic assesses continuous-time and discrete-time systems independently and in relation to each other elucidates stability analysis and control synthesis supplies unification of results on control design and filtering and more Containing over 300 bibliographic citations and more than 1500 equations, Robust Control and Filtering for Time-Delay Systems is a must-read reference for electrical, electronics, computer, and control engineers, and an exceptional text for upper-level undergraduate and graduate students in these disciplines.

Production costs are being reduced by automation, robotics, computer-integrated manufacturing, cost reduction studies and more. These new technologies are expensive to buy, repair, and maintain. Hence, the demand on maintenance is growing and its costs are escalating. This new environment is compelling industrial maintenance organizations to make the transition from fixing broken machines to higher-level business units for securing production capacity. On the academic front, research in the area of maintenance management and engineering is receiving tremendous interest from researchers. Many papers have appeared in the literature dealing with the modeling and solution of maintenance problems using operations research (OR) and management science (MS) techniques. This area represents an opportunity for making significant contributions by the OR and MS communities. Maintenance, Modeling, and Optimization provides in one volume the latest developments in the area of maintenance modeling. Prominent scholars have contributed chapters covering a wide range of topics. We hope that this initial contribution will serve as a useful informative introduction to this field that may permit additional developments and useful directions for more research in this fast-growing area. The book is divided into six parts and contains seventeen chapters. Each chapter has been subject to review by at least two experts in the area of maintenance modeling and optimization. The first chapter provides an introduction to major maintenance modeling areas illustrated with some basic models. Part II contains five chapters dealing with maintenance planning and scheduling. Part III deals with preventive maintenance in six chapters. Part IV focuses on condition-based maintenance and contains two chapters. Part V deals with integrated production and maintenance models and contains two chapters. Part VI addresses issues related to maintenance and new technologies, and also deals with Just-in-Time (JIT) and Maintenance.

Quantitative Feedback Design of Linear and Nonlinear Control Systems is a self-contained book dealing with the theory and practice of Quantitative Feedback Theory (QFT). The author presents feedback synthesis techniques for single-input single-output, multi-input multi-output linear time-invariant and nonlinear plants based on the QFT method. Included are design details and graphs which do not appear in the literature, which will enable engineers and researchers to understand QFT in greater depth. Engineers will be able to apply QFT and the design techniques to many applications, such as flight and chemical plant control, robotics, space, vehicle and military industries, and numerous other uses. All of the examples were implemented using MatlabA(R) Version 5.3; the script file can be found at the author's Web site. QFT results in efficient designs because it synthesizes a controller for the exact amount of plant uncertainty, disturbances and required specifications. Quantitative Feedback Design of Linear and Nonlinear Control Systems is a pioneering work that illuminates QFT, making the theory - and practice - come alive.

This book is intended to be an exhaustive study on regularity and other properties of continuity for different types of non-additive multimeasures and with respect to different types of topologies. The book is addressed to graduate and postgraduate students, teachers and all researchers in mathematics, but not only. Since the notions and results offered by this book are closely related to various notions of the theory of probability, this book will be useful to a wider category of readers, using multivalued analysis techniques in areas such as control theory and optimization, economic mathematics, game theory, decision theory, etc. Measure and integration theory developed during the early years of the 20th century is one of the most important contributions to modern mathematical analysis, with important applications in many fields. In the last years, many classical problems from measure theory have been treated in the non-additive case and also extended in the set-valued case. The property of regularity is involved in many results of mathematical analysis, due to its applications in probability theory, stochastic processes, optimal control problems, dynamical systems, Markov chains, potential theory etc.

The contributions for this book have been gathered over several years from conferences held in the series of Mechatronics and Machine Vision in Practice, the latest of which was held in Ankara, Turkey. The essential aspect is that they concern practical applications rather than the derivation of mere theory, though simulations and visualization are important components. The topics range from mining, with its heavy engineering, to the delicate machining of holes in the human skull or robots for surgery on human flesh. Mobile robots continue to be a hot topic, both from the need for navigation and for the task of stabilization of unmanned aerial vehicles. The swinging of a spray rig is damped, while machine vision is used for the control of heating in an asphalt-laying machine. Manipulators are featured, both for general tasks and in the form of grasping fingers. A robot arm is proposed for adding to the mobility scooter of the elderly. Can EEG signals be a means to control a robot? Can face recognition be achieved in varying illumination?"

Hidenori Kimura, renowned system and control theorist, turned 60 years of age in November, 2001. To celebrate this memorable occasion, his friends, collaborators, and former students gathered from all over the world and held a symposium in his honor on November 1 and 2, 2001, at the Sanjo Conference Hall at the University of Tokyo. Reflecting his current research interests, the symposium was entitled "Cybernetics in the 21st Century: Information and Complexity in Control Theory," and it drew nearly 150 attendees. There were twenty-five lectures, on which the present volume is based. Hidenori Kimura was born on November 3, 1941, in Tokyo, just prior to the outbreak of the Second World War. It is not hard to imagine, then, that his early days, like those of so many of his contemporaries, must have been difficult. Fortunately, the war ended in 1945, and his generation found itself thoroughly occupied with the rebuilding effort and with Japan's uphill journey in the last half-century. He entered the University of Tokyo in 1963, received a B. S. in 1965, an M. S. in 1967, and, in 1970, a Ph. D. degree for his dissertation "A Study of Differential Games. " After obtaining his doctorate, he joined the Department of Control En gineering at Osaka University as a research associate, and in 1973 he was promoted to an associate professor."

This book focusses on Industry 4.0 which is one of the most challenging trends for all categories of manufacturing enterprises. In this book, variety of mechatronic solutions are discussed to develop a manufacturing control system for small and medium-sized enterprises as they impose to improve their capabilities by integration into Industry 4.0 standards.

This monograph focuses on how to achieve more robot autonomy by means of reliable processing skills. "Nonlinear Kalman Filtering for Force-Controlled Robot Tasks " discusses the latest developments in the areas of contact modeling, nonlinear parameter estimation and task plan optimization for improved estimation accuracy. Kalman filtering techniques are applied to identify the contact state based on force sensing between a grasped object and the environment. The potential of this work is to be found not only for industrial robot operation in space, sub-sea or nuclear scenarios, but also for service robots operating in unstructured environments co-habited by humans where autonomous compliant tasks require active sensing.

Distributed manipulation effects motion on objects through a large number of points of contact. The primary benefit of distributed manipulators is that many small inexpensive mechanisms can move and transport large heavy objects. In fact, each individual component is simple, but their combined effect is quite powerful. Furthermore, distributed manipulators are fault-tolerant because if one component breaks, the other components can compensate for the failure and the whole system can still perform its task. Finally, distributed manipulators can perform a variety of tasks in parallel. Distributed manipulation can be performed by many types of mechanisms at different scales. Due to the recent advances of MEMS (micro-electro-mechanical system) technology, it has become feasible to quickly manufacture distributed micro-manipulators at low cost. One such system is an actuator array where hundreds of micro-scaled actuators transport and manipulate small objects that rest on them. Macroscopic versions of the actuator array have also been developed and analyzed. Another form of distributed manipulation is derived from a vibrating plate, and teams of mobile robots have been used to herd large objects into desired locations. There are many fundamental issues involved in distributed manipulation. Since a distributed manipulator has many actuators, distributed control strategies must be considered to effectively manipulate objects. A basic understanding of contact analysis between the actuators and object must also be considered. When each actuator in the array has a sensor, distributed sensing presents some basic research challenges. Distributed computation and communication are key issues to enable the successful deployment of distributed manipulators into use. Finally, the trade-off in centralized and de-centralized approaches in all of these algorithms must be investigated.