Husband Tom Husband – författare

Classical optimization methodologies fall short in very large and complex domains. In this book is suggested a different approach to optimization, an approach which is based on the 'blind' and heuristic mechanisms of evolution and population genetics. The genetic approach to optimization introduces a new philosophy to optimization in general, but particularly to engineering. By introducing the 'genetic' approach to robot trajectory generation, much can be learned about the adaptive mechanisms of evolution and how these mechanisms can solve real world problems. It is suggested further that optimization at large may benefit greatly from the adaptive optimization exhibited by natural systems when attempting to solve complex optimization problems, and that the determinism of classical optimization models may sometimes be an obstacle in nonlinear systems.This book is unique in that it reports in detail on an application of genetic algorithms to a real world problem, and explains the considerations taken during the development work. Futhermore, it addresses robotics in two new aspects: the optimization of the trajectory specification which has so far been done by human operators and has not received much attention for both automation and optimization, and the introduction of a heuristic strategy to a field predominated by deterministic strategies.

This book aims to describe how parallel computer architectures can be used to enhance the performance of robots, and their great impact on future generations of robots. It provides an in-depth, consistent and rigorous treatment of the topic. A clear definition of tools with results is given which can be applied to parallel processing for robot kinematics and dynamics. Another advantageous feature is that the algorithms presented have been implemented using a parallel processing system, unlike many publications in the field which have presented results in only theoretical terms. This book also includes "e;benchmark"e; results that can be used for the development of future work, or can serve as a basis for comparison with other work. In addition, it surveys useful material to aid readers in pursuing further research.

This book presents recent trends in the field as perceived by a global selection of researchers and experts. Subjects covered include motion planning of mobile robots in unknown environments, coordination between mobility and manipulability, computation environments for mobile robots, nonlinear control of mobile robots and environmental modeling using advanced sensing technologies. Issues ranging from progress in applications to fundamental problems are discussed.

This book introduces interesting topics, from concepts to the latest research, on cellular and micro robotic systems. The cellular robotic system is a self-organizing robotic system composed of a large number of autonomous robotic units, named cells. This idea came from the organic structure of a living body. Several attractive topics in this area are covered, such as swarm intelligence, communications, and robotic mechanisms. The micro robotic system is currently the most fascinating technology. Micro mechanisms, control and intelligence, with respect to this system are treated here. The combination of both technologies will prepare the way for a new paradigm in the field of engineering.

The Oxford University Robotics Research Group has been working for several years to improve the ability of automated guided vehicles. This book brings together much of the key research work on sensors and planning that was inspired by an industrial vehicle donated by a factory automation division in GEC, GEC-FAST, together with background material to provide a basic but up-to-date reference guide to autonomous vehicle research. The book includes work on control, sensing technologies, sensor management and data-fusion, different styles of path planning suited for off-line or online plans and task planning. It is designed to act both as a reference for the robotics professional, and as a text for university-level courses.

With increasing demands for high precision autonomous control over wide operating envelopes, conventional control engineering approaches are unable to adequately deal with system complexity, nonlinearities, spatial and temporal parameter variations, and with uncertainty. Intelligent Control or self-organising/learning control is a new emerging discipline that is designed to deal with problems. Rather than being model based, it is experiential based. Intelligent Control is the amalgam of the disciplines of Artificial Intelligence, Systems Theory and Operations Research. It uses most recent experiences or evidence to improve its performance through a variety of learning schemas, that for practical implementation must demonstrate rapid learning convergence, be temporally stable, be robust to parameter changes and internal and external disturbances. It is shown in this book that a wide class of fuzzy logic and neural net based learning algorithms satisfy these conditions. It is demonstrated that this class of intelligent controllers is based upon a fixed nonlinear mapping of the input (sensor) vector, followed by an output layer linear mapping with coefficients that are updated by various first order learning laws. Under these conditions self-organising fuzzy logic controllers and neural net controllers have common learning attributes.A theme example of the navigation and control of an autonomous guided vehicle is included throughout, together with a series of bench examples to demonstrate this new theory and its applicability.

Advanced robot systems require sensory information to enable them to make decisions and to carry out actions in a versatile, autonomous way. Humans make considerable use of information derived through touch, and an emerging domain of robot sensing is tactile sensing. This book considers various aspects of tactile sensing, from hardware design through to the use of tactile data in exploratory situations using a multi-fingered robot hand.In the first part of the book, the current state of progress of tactile sensing is surveyed, and it is found that the field is still in an early stage of development. Next, some fundamental issues in planar elasticity, concerning the interaction between tactile sensors and the environment, are presented. Having established how the basic data can be derived from the sensors, the issues of what form tactile sensors should take, and how they should be used, are considered. This is particularly important given the infancy of this field. The human tactile system is examined, and then biological touch and its implications for robotics is looked at. Some experiments in dextrous manipulation using a robot hand are described, which apply some of these results. The integration of tactile sensors into a complete system is also considered, and another, novel, approach for using touch sensing in a flexible assembly machine is described.Both basic material and new research results are provided in this book, thus catering to different levels of readers. The chapters by world experts in different aspects of the field are integrated well into one volume. The editor and authors have produced a thorough and in-depth survey of all work in robot tactile sensing, making the book essential reading for all researchers in this emergent field.

This volume focusses on the problem of planning in the context of robotics. Unlike most books on robotics planning which are either too abstract or too specific, this one extends the techniques developed for generic planning problems with robotics-specific considerations so that the task of planning can be discussed in a more uniform way. It also includes the latest results in reconfigurable (mobile) robot planning, multiple robot planning, plan recovery, and planning in uncertain environments. This volume is probably the very first book in the market that provides a theoretical foundation for planning techniques and their applications. It also bridges the gap that has been existing for a long time between computer scientists and application engineers. It will be of interest to senior and graduate students in engineering and computer science, AI researchers and professionals.

This book presents an extensive survey of the state-of-the-art research in parallel computational algorithms and architectures for robot manipulator control and simulation. It deals not only with specifics but also includes general and broader issues which serve as a useful foundation to the topic. The educational flavor of the book makes it a necessary resource for researchers, engineers and students wanting to be familiarized with the potential offered by the application of parallel processing to robotic problems, and its current issues and trends.

The main focus of this book is on the uses of computer vision for inspection and model based matching. It also provides a short, self contained introductory course on computer vision. The authors describe various state-of-the-art approaches to probems and then set forth their proposed approach to matching and inspection. They deal primarily with 3-D vision but also discuss 2-D vision strategies when relevant.The book is suitable for researchers, final year undergraduates and graduate students. Useful review questions at the end of each chapter allow this book to be used for self-study.