Industrial machines, automobiles, airplanes, robots, and machines are among the myriad possible hosts of embedded systems. The author researches robotic vehicles and remote operated vehicles (ROVs), especially Underwater Robotic Vehicles (URVs), used for a wide range of applications such as exploring oceans, monitoring environments, and supporting operations in extreme environments. Embedded Mechatronics System Design for Uncertain Environments has been prepared for those who seek to easily develop and design embedded systems for control purposes in robotic vehicles. It reflects the multidisciplinarily of embedded systems from initial concepts (mechanical and electrical) to the modelling and simulation (mathematical relationships), creating graphical-user interface (software) and their actual implementations (mechatronics system testing). The author proposes new solutions for the prototyping, simulation, testing, and design of real-time systems using standard PC hardware including Linux (R), Raspbian (R), ARDUINO (R), and MATLAB (R) xPC Target.

Incorporating intelligence in industrial systems can help to increase productivity, cut-off production costs, and to improve working conditions and safety in industrial environments. This need has resulted in the rapid development of modeling and control methods for industrial systems and robots, of fault detection and isolation methods for the prevention of critical situations in industrial work-cells and production plants, of optimization methods aiming at a more profitable functioning of industrial installations and robotic devices and of machine intelligence methods aiming at reducing human intervention in industrial systems operation. To this end, the book analyzes and extends some main directions of research in modeling and control for industrial systems. These are: (i) industrial robots, (ii) mobile robots and autonomous vehicles, (iii) adaptive and robust control of electromechanical systems, (iv) filtering and stochastic estimation for multisensor fusion and sensorless control of industrial systems (iv) fault detection and isolation in robotic and industrial systems, (v) optimization in industrial automation and robotic systems design, and (vi) machine intelligence for robots autonomy. The book will be a useful companion to engineers and researchers since it covers a wide spectrum of problems in the area of industrial systems. Moreover, the book is addressed to undergraduate and post-graduate students, as an upper-level course supplement of automatic control and robotics courses.

Many computer scientists, engineers, applied mathematicians, and physicists use geometry theory and geometric computing methods in the design of perception-action systems, intelligent autonomous systems, and man-machine interfaces. This handbook brings together the most recent advances in the application of geometric computing for building such systems, with contributions from leading experts in the important fields of neuroscience, neural networks, image processing, pattern recognition, computer vision, uncertainty in geometric computations, conformal computational geometry, computer graphics and visualization, medical imagery, geometry and robotics, and reaching and motion planning. For the first time, the various methods are presented in a comprehensive, unified manner.

This handbook is highly recommended for postgraduate students and researchers working on applications such as automated learning; geometric and fuzzy reasoning; human-like artificial vision; tele-operation; space maneuvering; haptics; rescue robots; man-machine interfaces; tele-immersion; computer- and robotics-aided neurosurgery or orthopedics; the assembly and design of humanoids; and systems for metalevel reasoning.

Mechanics and Control of Soft-fingered Manipulation introduces a new approach to the modeling of fingertips that have a soft pad and a hard back plate, similar to human fingers. Starting from the observation of soft-fingered grasping and manipulation, the book provides a parallel distributed model that takes into account tangential deformation of the fingertips. The model is supported with many experimental verifications and simulation results. Statics and dynamics in soft-fingered grasping and manipulation are also formulated based on this new model. The book uniquely investigates how soft fingertips with hard back plates enhance dexterity in grasping and manipulation, theoretically and experimentally, revealing the differences between soft-fingered and rigid-fingered manipulation. Researchers involved in object manipulation by robotic hands, as well as in human dexterity in object manipulation, will find this text enlightening.

Evolutionary Algorithms (EAs) now provide mature optimization tools that have successfully been applied to many problems, from designing antennas to complete robots, and provided many human-competitive results. In robotics, the integration of EAs within the engineer's toolbox made tremendous progress in the last 20 years and proposes new methods to address challenging problems in various setups: modular robotics, swarm robotics, robotics with non-conventional mechanics (e.g. high redundancy, dynamic motion, multi-modality), etc. This book takes its roots in the workshop on "New Horizons in Evolutionary Design of Robots" that brought together researchers from Computer Science and Robotics during the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS-2009) in Saint Louis (USA). This book features extended contributions from the workshop, thus providing various examples of current problems and applications, with a special emphasis on the link between Computer Science and Robotics. It also provides a comprehensive and up-to-date introduction to Evolutionary Robotics after 20 years of maturation as well as thoughts and considerations from several major actors in the field. This book offers a comprehensive introduction to the current trends and challenges in Evolutionary Robotics for the next decade.

1 Grundlagen der Dynamik regelungstechnischer Systeme.- 1.1 Allgemeine Zielsetzung der Regelungstechnik.- 1.2 Regelkreis.- 1.3 Voraussetzungen fur Blockorientierung und Regelkreisbildung.- 1.4 Aufgaben der Regelungstechnik.- 1.5 UEbertragungsfunktion und Regelungssystemtheorie.- 1.6 Anfangsbedingungen und Nullstellen der UEbertragungsfunktion.- 1.7 Ausgangssignal Xa(s) bei x a(k)(0?)=0.- 1.8 Nichtverschwindende Vorgeschichte xa(k)(0?)?0.- 1.9 Analyse im Spektralbereich. Verknupfung mehrerer Elemente.- 1.10 Regelstrecke und Stoergroessen.- 1.11 Einschleifiger Standardregelkreis.- 1.12 Sensitivitat.- 1.13 Differentielle Sensitivitat fur den Standardregelkreis.- 1.14 Linearisierung.- 1.15 Regelkreis im Signalflussdiagramm.- 1.16 Spezielle Elemente regelungstechnischer Systeme.- 1.16.1 Rationale UEbertragungselemente.- 1.16.2 Totzeit-Elemente.- 1.16.3 Allpass-Elemente.- 1.16.4 Laufzeitelemente.- 2 Regelkreisanalyse im Zeitbereich.- 2.1 Regelkreis-Reaktion auf einfache Signale.- 2.2 Mehrfache Polstellen von Xa(s).- 2.3 Naherung fur kleine Zeitwerte.- 2.4 Naherung fur grosse Zeitwerte.- 2.5 Faltungsintegral und Naherung durch Faltungssumme.- 2.6 Regelungen mit Totzeitelementen.- 3 Formulierung kontinuierlicher Regelungssysteme im Zustandsraum.- 3.1 Grundlagen.- 3.2 Transitionsmatrix (Fundamentalmatrix).- 3.3 Potenzreihenentwicklung der Transitionsmatrix.- 3.4 Zustandsregler. Fuhrungs- und Stoerungsverhalten.- 3.5 Vorfilterbemessung.- 4 Analyseverfahren im Frequenzbereich.- 4.1 Frequenzgang.- 4.2 Ortskurven des Frequenzgangs.- 4.3 Ortskurven von typischen stabilen Regelkreis-Element en.- 4.4 Ortskurven instabiler Regelkreiselemente.- 4.5 Frequenzgangsortskurve des Regelkreises.- 4.6 Ermittlung von Zeitbereichssignalen aus dem Frequenzbereich.- 4.7 Ermittlung des Frequenzganges aus der gemessenen Systemantwort.- 4.8 Bode-Diagramm.- 4.9 Phasenminimum-Beziehungen.- 4.10 Knickstellen der Regelschleife und des Regelkreises.- 4.11 H?-Norm einer UEbertragungsfunktion.- 5 Regelstrecken im Regelkreis.- 5.1 Antriebe. Allgemeines.- 5.2 Stromrichtergespeiste Gleichstromantriebe.- 5.3 Stromleitverfahren.- 5.4 Begrenzungsregelung.- 5.5 Kupplungselastizitat.- 5.6 Umrichtergespeiste Asynchronmaschine.- 5.7 Thermische Regelstrecken.- 5.7.1 Durchlauferhitzer, Warmetauscher.- 5.7.2 Kessel und Turbine.- 5.8 Hydraulische Regelstrecken.- 5.9 Pneumatische Regelstrecke.- 5.10 Mechanische Positionsregelstrecken.- 5.10.1 Einfache Fahrzeuglenkung.- 5.10.2 Balancierung.- 5.10.3 Passagierflugzeug.- 5.10.4 Raketenantrieb.- 5.11 Verfahrenstechnische Regelstrecken.- 5.12 Elektronische und nachrichtentechnische Regelstrecken.- 5.12.1 Verstarkungsausgleich.- 5.12.2 Scharfabstimmung.- 5.12.3 Zeilensynchronisierung.- 5.12.4 Rauschunterdruckung.- 5.13 Phase-Locked Loops (PLL).- 5.13.1 Phase-Locked Loop in analoger Ersatzrechnung.- 5.13.2 Regelungen an einem CD-Player.- 5.14 Schaltzeichen (Sinnbilder) fur technische Regelstrecken.- 5.15 Volkswirtschaftliche Regelungen.- 5.16 Physiologische und psychische Regelkreise.- 5.17 Soziologische Regelungen.- 6 Stellglieder und Verstarker.- 6.1 Stromrichterstellglieder.- 6.2 Umrichter fur Drehfeldmaschinen.- 6.3 Stellmotoren fur mechanische Positionierung.- 6.4 Stellglieder fur Flussigkeits-, Gasstroeme u. koernige Stoffe.- 6.5 Schaltzeichen fur Stellglieder und Verstarker.- 7 Regelungstechnischer Einsatz von Sensoren und Messumformern.- 7.1 Anforderungen.- 7.2 Messrauschen.- 7.3 Leistung eines Rauschsignales.- 8 Identifikationsverfahren.- 8.1 Auswertung der Sprungantwort von PDT1-Elementen.- 8.2 Auswertung der Sprungantwort von PT2-Elementen.- 8.3 Wendetangentenmethode bei PT2-Elementen.- 8.4 Auswertung der Sprungantwort von IT1-Elementen.- 8.5 Momentenmethode an der Gewichtsfunktion.- 8.6 Identifikation mit Hilfsregler.- 8.7 Identifikation mit fiktivem Serienelement.- 8.8 Regressionsanalyse. Quadratische Ausgleichsrechnung.- 9 Regler. Ausfuhrung und Dimensionierung.- 9.1 Operationsverstarker.- 9.2 Elektr

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.

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 ?

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 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.

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 monograph has arisen from the multidisciplinary research extending over biology, robotics and hybrid systems theory. It is inspired by modeling reactive behavior of the immune system cell population, where each cell is considered an independent agent. The authors formulate the optimal control of maximizing the probability of robotic presence in a given region and discuss the application of the Minimum Principle for partial differential equations to this problem.