Scientific Methods In Mobile Robotics

Aims at a theoretical understanding of the operation of autonomous mobile robots. This book presents the research on the application of chaos theory, parametric and non-parametric statistics and dynamical systems theory in this field. Practical examples and case studies show how robot behaviour can be logged, analysed, interpreted and modelled.

Mobile robotics has until now focused on issues like design of controllers and robot hardware. It is now ready to embrace theoretical methods from dynamical systems theory, statistics and system identification to produce a formalized approach based on quantitative analyses and computer models of the interaction between robot, task and environment. This book is a step towards a theoretical understanding of the operation of autonomous mobile robots. It presents cutting-edge research on the application of chaos theory, parametric and non-parametric statistics and dynamical systems theory in this field. Practical examples and case studies show how robot behaviour can be logged, analysed, interpreted and modelled, aiding design of controllers, analysis of agent behaviour and verification of results. As the first book to apply advanced scientific methods to mobile robots it will interest researchers, lecturers and post-graduate students in robotics, artificial intelligence and cognitive science.

Introduction -- Math fundamentals -- Numerical methods -- Dynamics -- Optimal estimation -- State estimation -- Control -- Perception -- Localization and mapping -- Motion planning

Mobile Robotics: A Practical Introduction (2nd edition) is an excellent introduction to the foundations and methods used for designing completely autonomous mobile robots. A fascinating, cutting-edge, research topic, autonomous mobile robotics is now taught in more and more universities. In this book you are introduced to the fundamental concepts of this complex field via twelve detailed case studies that show how to build and program real working robots. Topics covered in clued learning, autonomous navigation in unmodified, noisy and unpredictable environments, and high fidelity robot simulation. This new edition has been updated to include a new chapter on novelty detection, and provides a very practical introduction to mobile robotics for a general scientific audience. It is essential reading for 2nd and 3rd year undergraduate students and postgraduate students studying robotics, artificial intelligence, cognitive science and robot engineering. The update and overview of core concepts in mobile robotics will assist and encourage practitioners of the field and set challenges to explore new avenues of research in this exiting field. The author is Senior Lecturer at the Department of Computer Science at the University of Essex. "A very fine overview over the relevant problems to be solved in the attempt to bring intelligence to a moving vehicle." Professor Dr. Ewald von Puttkamer, University of Kaiserslautern "Case studies show ways of achieving an impressive repertoire of kinds of learned behaviour, navigation and map-building. The book is an admirable introduction to this modern approach to mobile robotics and certainly gives a great deal of food for thought. This is an important and though-provoking book." Alex M. Andrew in Kybernetes Vol 29 No 4 and Robotica Vol 18

Mobile Robotics presents the different tools and methods that enable the design of mobile robots; a discipline booming with the emergence of flying drones, underwater mine-detector robots, robot sailboats and vacuum cleaners. Illustrated with simulations, exercises and examples, this book describes the fundamentals of modeling robots, developing the concepts of actuators, sensors, control and guidance. Three-dimensional simulation tools are also explored, as well as the theoretical basis for the reliable localization of robots within their environment. This revised and updated edition contains additional exercises and a completely new chapter on the Bayes filter, an observer that enhances our understanding of the Kalman filter and facilitates certain proofs.

As mobile robots become more common in general knowledge and practices, as opposed to simply in research labs, there is an increased need for the introduction and methods to Simultaneous Localization and Mapping (SLAM) and its techniques and concepts related to robotics. Simultaneous Localization and Mapping for Mobile Robots: Introduction and Methods investigates the complexities of the theory of probabilistic localization and mapping of mobile robots as well as providing the most current and concrete developments. This reference source aims to be useful for practitioners, graduate and postgraduate students, and active researchers alike.

Introduction to Mobile Robot Control provides a complete and concise study of modeling, control, and navigation methods for wheeled non-holonomic and omnidirectional mobile robots and manipulators. The book begins with a study of mobile robot drives and corresponding kinematic and dynamic models, and discusses the sensors used in mobile robotics. It then examines a variety of model-based, model-free, and vision-based controllers with unified proof of their stabilization and tracking performance, also addressing the problems of path, motion, and task planning, along with localization and mapping topics. The book provides a host of experimental results, a conceptual overview of systemic and software mobile robot control architectures, and a tour of the use of wheeled mobile robots and manipulators in industry and society. Introduction to Mobile Robot Control is an essential reference, and is also a textbook suitable as a supplement for many university robotics courses. It is accessible to all and can be used as a reference for professionals and researchers in the mobile robotics field. Clearly and authoritatively presents mobile robot concepts Richly illustrated throughout with figures and examples Key concepts demonstrated with a host of experimental and simulation examples No prior knowledge of the subject is required; each chapter commences with an introduction and background

Robots have evolved impressively since the 3-D manipulator built by C.W. K- ward (1957), the two little electromechanical turtles Elmer and Elsie [Walter, 1950, Walter, 1951], and the ?rst mobile robots controlled by comp- ers, Shakey [Nilsson, 1984], CART [Moravec, 1979, Moravec, 1983], and - lare [Giralt et al., 1979]. Since then, we have seen industrial robot manipu- tors working in car factories, automatic guided vehicles moving heavy loads along pre-de?ned routes, human-remotely-operated robots neutralising bombs, and even semi-autonomous robots, like Sojourner, going to Mars and moving from one position to another commanded from Earth. Robots will go further and further in our society. However, there is still a kind of robot that has not completely taken off so far: autonomous robots. Autonomy depends upon working without human supervision for a considerable amount of time, taking independent decisions, adapting to new challenges in dynamic environments, interacting with other systems and humans, and so on. Research on autonomy is highly motivated by the expectations of having robots that can work with us and for us in everyday environments, assisting us at home or work, acting as servants and companions to help us in the execution of different tasks, so that we can have more spare time and a better quality of life.