This book provides an overview of model-based environmental visual perception for humanoid robots. The visual perception of a humanoid robot creates a bidirectional bridge connecting sensor signals with internal representations of environmental objects. The objective of such perception systems is to answer two fundamental questions: What & where is it? To answer these questions using a sensor-to-representation bridge, coordinated processes are conducted to extract and exploit cues matching robot's mental representations to physical entities. These include sensor & actuator modeling, calibration, filtering, and feature extraction for state estimation. This book discusses the following topics in depth: * Active Sensing: Robust probabilistic methods for optimal, high dynamic range image acquisition are suitable for use with inexpensive cameras. This enables ideal sensing in arbitrary environmental conditions encountered in human-centric spaces. The book quantitatively shows the importance of equipping robots with dependable visual sensing. * Feature Extraction & Recognition: Parameter-free, edge extraction methods based on structural graphs enable the representation of geometric primitives effectively and efficiently. This is done by eccentricity segmentation providing excellent recognition even on noisy & low-resolution images. Stereoscopic vision, Euclidean metric and graph-shape descriptors are shown to be powerful mechanisms for difficult recognition tasks. * Global Self-Localization & Depth Uncertainty Learning: Simultaneous feature matching for global localization and 6D self-pose estimation are addressed by a novel geometric and probabilistic concept using intersection of Gaussian spheres. The path from intuition to the closed-form optimal solution determining the robot location is described, including a supervised learning method for uncertainty depth modeling based on extensive ground-truth training data from a motion capture system. The methods and experiments are presented in self-contained chapters with comparisons and the state of the art. The algorithms were implemented and empirically evaluated on two humanoid robots: ARMAR III-A & B. The excellent robustness, performance and derived results received an award at the IEEE conference on humanoid robots and the contributions have been utilized for numerous visual manipulation tasks with demonstration at distinguished venues such as ICRA, CeBIT, IAS, and Automatica.

This book focuses on the basic control and filtering synthesis problems for discrete-time switched linear systems under time-dependent switching signals. Chapter 1, as an introduction of the book, gives the backgrounds and motivations of switched systems, the definitions of the typical time-dependent switching signals, the differences and links to other types of systems with hybrid characteristics and a literature review mainly on the control and filtering for the underlying systems. By summarizing the multiple Lyapunov-like functions (MLFs) approach in which different requirements on comparisons of Lyapunov function values at switching instants, a series of methodologies are developed for the issues on stability and stabilization, and l2-gain performance or tube-based robustness for l disturbance, respectively, in Chapters 2 and 3. Chapters 4 and 5 are devoted to the control and filtering problems for the time-dependent switched linear systems with either polytopic uncertainties or measurable time-varying parameters in different sense of disturbances. The asynchronous switching problem, where there is time lag between the switching of the currently activated system mode and the controller/filter to be designed, is investigated in Chapter 6. The systems with various time delays under typical time-dependent switching signals are addressed in Chapter 7.

The present book includes a set of selected extended papers from the 11th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2014), held in Vienna, Austria, from 1 to 3 September 2014. The conference brought together researchers, engineers and practitioners interested in the application of informatics to Control, Automation and Robotics. Four simultaneous tracks will be held, covering Intelligent Control Systems, Optimization, Robotics, Automation, Signal Processing, Sensors, Systems Modelling and Control, and Industrial Engineering, Production and Management. Informatics applications are pervasive in many areas of Control, Automation and Robotics. ICINCO 2014 received 301 submissions, from 49 countries, in all continents. After a double blind paper review performed by the Program Committee, 20% were accepted as full papers and thus selected for oral presentation. Additional papers were accepted as short papers and posters. A further selection was made after the Conference, based also on the assessment of presentation quality and audience interest, so that this book includes the extended and revised versions of the very best papers of ICINCO 2014. Commitment to high quality standards is a major concern of ICINCO that will be maintained in the next editions, considering not only the stringent paper acceptance ratios but also the quality of the program committee, keynote lectures, participation level and logistics.

This book is a delight for academics, researchers and professionals working in evolutionary and swarm computing, computational intelligence, machine learning and engineering design, as well as search and optimization in general. It provides an introduction to the design and development of a number of popular and recent swarm and evolutionary algorithms with a focus on their applications in engineering problems in diverse domains. The topics discussed include particle swarm optimization, the artificial bee colony algorithm, Spider Monkey optimization algorithm, genetic algorithms, constrained multi-objective evolutionary algorithms, genetic programming, and evolutionary fuzzy systems. A friendly and informative treatment of the topics makes this book an ideal reference for beginners and those with experience alike.

This monograph is devoted to the theory and development of autonomous navigation of mobile robots using computer vision based sensing mechanism. The conventional robot navigation systems, utilizing traditional sensors like ultrasonic, IR, GPS, laser sensors etc., suffer several drawbacks related to either the physical limitations of the sensor or incur high cost. Vision sensing has emerged as a popular alternative where cameras can be used to reduce the overall cost, maintaining high degree of intelligence, flexibility and robustness.

This book includes a detailed description of several new approaches for real life vision based autonomous navigation algorithms and SLAM. It presents the concept of how subgoal based goal-driven navigation can be carried out using vision sensing. The development concept of vision based robots for path/line tracking using fuzzy logic is presented, as well as how a low-cost robot can be indigenously developed in the laboratory with microcontroller based sensor systems. The book describes successful implementation of integration of low-cost, external peripherals, with off-the-shelf procured robots. An important highlight of the book is that it presents a detailed, step-by-step sample demonstration of how vision-based navigation modules can be actually implemented in real life, under 32-bit Windows environment. The book also discusses the concept of implementing vision based SLAM employing a two camera based system.

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Robotic Sailing 2017. This book contains the peer-reviewed papers presented at the 10th International Robotic Sailing Conference which was organized in conjunction with the 10th World Robotic Sailing Championship held in Horten, Norway the 4th-9th of September 2017. The seven papers cover topics of interest for autonomous robotic sailing which represents some of the most challenging research and development areas. The book is divided into two parts. The first part contains papers which focus on the design of sails and software for the assessment and predication of sailboat performance as well as software platforms and middleware for sailboat competition and research. The second part includes algorithms and strategies for navigation and collision avoidance on local, mid- and long range. The differences in approach in the included papers show that robotic sailing is still an emerging cross-disciplinary science. The multitude of suggestions to the specific problems of prediction and simulation of sailboats as well as the challenges of route planning, anti-grounding and collision avoidance are good indicators of science in its infancy. Hence, we may expect the future to hold great advances for robotic sailing.

By the dawn of the new millennium, robotics has undergone a major tra- formation in scope and dimensions. This expansion has been brought about bythematurityofthe?eldandtheadvancesinitsrelatedtechnologies.From a largely dominant industrial focus, robotics has been rapidly expanding into the challenges of the human world. The new generation of robots is expected to safely and dependably co-habitat with humans in homes, workplaces, and communities, providingsupportinservices, entertainment, education, heal- care, manufacturing, and assistance. Beyond its impact on physical robots, the body of knowledge robotics has produced is revealing a much wider range of applications reaching across - verse research areas and scienti?c disciplines, such as: biomechanics, haptics, neurosciences, virtual simulation, animation, surgery, and sensor networks among others. In return, the challenges of the new emerging areas are pr- ing an abundant source of stimulation and insights for the ?eld of robotics. It is indeed at the intersection of disciplines that the most striking advances happen. The goal of the series of Springer Tracts in Advanced Robotics (STAR) is to bring, in a timely fashion, the latest advances and developments in robotics on the basis of their signi?cance and quality. It is our hope that the wider dissemination of research developments will stimulate more exchanges and collaborations among the research community and contribute to further advancement of this rapidly growing ?

Mechatronics is a core subject for engineers, combining elements of mechanical and electronic engineering into the development of computer-controlled mechanical devices such as DVD players or anti-lock braking systems. This book is the most comprehensive text available for both mechanical and electrical engineering students and will enable them to engage fully with all stages of mechatronic system design. It offers broader and more integrated coverage than other books in the field with practical examples, case studies and exercises throughout and an Instructor's Manual. A further key feature of the book is its integrated coverage of programming the PIC microcontroller, and the use of MATLAB and Simulink programming and modelling, along with code files for downloading from the accompanying website.
*Integrated coverage of PIC microcontroller programming, MATLAB and Simulink modelling
*Fully developed student exercises, detailed practical examples
*Accompanying website with Instructor's Manual, downloadable code and image bank

Rescue Robotics presents the most significant findings of the DDT Project on robots and systems for urban search and rescue. This project was launched by the Japanese government in 2002 with the aim of applying a wide variety of robotics technologies to find a solution to the problem of disaster response, especially urban search and rescue in large-scale earthquakes.

From 2002 to 2007 more than 100 researchers took part in the DDT Project, coming from a wide spectrum of research and development to make up four research groups: Aerial Robot Systems MU (Mission Unit), Information Infrastructure System MU, In-Rubble Robot System MU, and On-Rubble Robot System MU. This book discusses their development and testing of various robotic systems and technologies such as serpentine robots, traced vehicles, intelligent human interface and data processing, as well as analysing and verifying the results of these experiments.

Rescue Robotics will be of interest to researchers and students, but will also prove useful for emergency response personnel. It offers an insight into the state of the art of rescue robotics and its readers will benefit from a knowledge of the advanced technologies involved in this field.

Optimization is an integral part to science and engineering. Most real-world applications involve complex optimization processes, which are di?cult to solve without advanced computational tools. With the increasing challenges of ful?lling optimization goals of current applications there is a strong drive to advancethe developmentofe?cientoptimizers. The challengesintroduced by emerging problems include: * objective functions which are prohibitively expensive to evaluate, so ty- callysoonlyasmallnumber ofobjectivefunctionevaluationscanbemade during the entire search, * objective functions which are highly multimodal or discontinuous, and * non-stationary problems which may change in time (dynamic). Classical optimizers may perform poorly or even may fail to produce any improvement over the starting vector in the face of such challenges. This has motivated researchers to explore the use computational intelligence (CI) to augment classical methods in tackling such challenging problems. Such methods include population-based search methods such as: a) evolutionary algorithms and particle swarm optimization and b) non-linear mapping and knowledgeembedding approachessuchasarti?cialneuralnetworksandfuzzy logic, to name a few. Such approaches have been shown to perform well in challenging settings. Speci?cally, CI are powerful tools which o?er several potential bene?ts such as: a) robustness (impose little or no requirements on the objective function) b) versatility (handle highly non-linear mappings) c) self-adaptionto improveperformance and d) operationin parallel(making it easy to decompose complex tasks). However, the successful application of CI methods to real-world problems is not straightforward and requires both expert knowledge and trial-and-error experiments.

This book presents cutting-edge results on stability analysis and control scheme designs for networked teleoperation systems. It highlights new research on commonly encountered nonlinear teleoperation systems, including the stability analysis of teleoperation systems with asymmetric time-varying delays, stability analysis of teleoperation systems with interval time delays, and so on. Moreover, the book presents several high-performance control scheme designs for teleoperation systems when the velocity is available and unavailable, and for systems with nonlinear input. The results presented here mark a substantial contribution to nonlinear teleoperation system theory, robotic control theory and networked control system theory. As such, the book will be of interest to university researchers, R&D engineers and graduate students in control theory and control engineering who wish to learn about the core principles, methods, algorithms, and applications of networked teleoperation systems, robotic systems and nonlinear control systems.

This book presents recent advances in the field of intelligent systems. Composed of fourteen selected chapters, it covers a wide range of research that varies from applications in industrial data science to those in applied science. Today the word INNOVATION is more and more connected with the words INTELLIGENT and SECURITY, as such the book discusses the theory and applications of hot topics such as big data, education applications of robots with different levels of autonomy, knowledge-based modeling and control of complex dynamical systems, sign-based synthesis of behavior, security issues with intelligent systems, innovative intelligent control design, neuromorphic computation, data-driven classification, intelligent modeling and measurement innovations, multisensor data association, personal education assistants, a modern production architecture, study of peer review and scientometrics, intelligent research on bug report data, and clustering non-Gaussian data. The broad and varied research discussed represents the mainstream of contemporary intelligent innovations that are slowly but surely changing the world.

Internal combustion engines (ICE) still have potential for substantial improvements, particularly with regard to fuel efficiency and environmental compatibility. In order to fully exploit the remaining margins, increasingly sophisticated control systems have to be applied. This book offers an introduction to cost-effective model-based control-system design for ICE. The primary emphasis is put on the ICE and its auxiliary devices. Mathematical models for these processes are developed and solutions for selected feedforward and feedback control-problems are presented.

The discussions concerning pollutant emissions and fuel economy of ICE in automotive applications constantly intensified since the first edition of this book was published. Concerns about the air quality, the limited resources of fossil fuels and the detrimental effects of greenhouse gases exceedingly spurred the interest of both the industry and academia in further improvements.

The most important changes and additions included in this second edition are: restructured and slightly extended section on superchargers, short subsection on rotational oscillations and their treatment on engine test-benches, complete section on modeling, detection, and control of engine knock, improved physical and chemical model for the three-way catalytic converter, new methodology for the design of an air-to-fuel ratio controller, short introduction to thermodynamic engine-cycle calculation and corresponding control-oriented aspects.

The book offers a comprehensive overview of controllability problems and minimum energy control for broad classes of dynamical systems, including linear, semilinear and nonlinear systems, which are important for modeling systems in automatic control, electrical engineering, mechanics and informatics. It develops the theory of controllability for both finite and infinite dimensional dynamical systems described by differential state equation, and studies in detail functional analysis and matrix algebra, which provide essential and effective tools for the new solutions of a number of important controllability problems. The theoretical results are illustrated by examples throughout the book. Primarily intended for academic researchers working in mathematical control theory, the self-contained text is easily accessible and particularly interesting for control engineering and applied mathematics graduates.

While domain decomposition methods have a long history dating back well over one hundred years, it is only during the last decade that they have become a major tool in numerical analysis of partial differential equations. This monograph emphasizes domain decomposition methods in the context of so-called virtual optimal control problems and treats optimal control problems for partial differential equations and their decompositions using an all-at-once approach.

A proceedings volume from teh 1st IFAC Symposium, Expo, Finland, 21-23 June 2004

Robotized 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.

This book presents techniques that enable mobile manipulation robots to autonomously adapt to new situations. Covers kinematic modeling and learning; self-calibration; tactile sensing and object recognition; imitation learning and programming by demonstration.

Multi-agent systems have numerous civilian, homeland security, and military applications; however, for all these applications, communication bandwidth, sensing range, power constraints, and stealth requirements preclude centralized command and control. The alternative is distributed coordination, which is more promising in terms of scalability, robustness, and flexibility. Distributed Coordination of Multi-agent Networks introduces problems, models, and issues such as collective periodic motion coordination, collective tracking with a dynamic leader, and containment control with multiple leaders, and explores ideas for their solution. Solving these problems extends the existing application domains of multi-agent networks; for example, collective periodic motion coordination is appropriate for applications involving repetitive movements, collective tracking guarantees tracking of a dynamic leader by multiple followers in the presence of reduced interaction and partial measurements, and containment control enables maneuvering of multiple followers by multiple leaders. The authors models for distributed coordination arise from physical constraints and the complex environments in which multi-agent systems operate; they include Lagrangian models more realistic for mechanical-systems modeling than point models and fractional-order systems which better represent the consequences of environmental complexity. Other issues addressed in the text include the time delays inherent in networked systems, optimality concerns associated with the deisgn of energy-efficent algorithms, and the use of sampled-data settings in systems with intermittent neightbor-neighbor contact. Researchers, graduate students, and engineers interested in the field of multi-agent systems will find this monograph useful in introducing them to presently emerging research directions and problems in distributed coordination of multi-agent networks. The Communications and Control Engineering series reports major technological advances which have potential for great impact in the fields of communication and control. It reflects research in industrial and academic institutions around the world so that the readership can exploit new possibilities as they become available.

This thesis presents a novel neuro-fuzzy modeling approach for grasp neuroprostheses. At first, it offers a detailed study of discomfort due to the application of Functional Electrical Stimulation to the upper limb. Then, it discusses briefly previous methods to model hand movements induced by FES with the purpose of introducing the new modeling approach based on intelligent systems. This approach is thoroughly described in the book, together with the proposed application to induce hand and finger movements by means of a surface FES system based on multi-field electrodes. The validation tests, carried out on both healthy and neurologically impaired subjects, demonstrate the efficacy of the proposed modeling method. All in all, the book proposes an innovative system based on fuzzy neural networks that is expected to improve the design and validation of advanced control systems for non-invasive grasp neuroprostheses.