Book 1

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.

Book 3

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.

Book 4

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.

Book 6

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.

Book 9

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.

Book 10

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.

Book 11

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.

Book 26

This book describes recent work on active sensors for mobile robots. An active sensor interacts with its surroundings to supply data on demand for a particular function, gathering and abstracting information according to need rather than acting as a generic data gatherer. Details of the physical operation are hidden.The book deals mainly with active range sensors, which provide rapid information for local planning, describing extraction of two-dimensional features such as lines, corners and cylinders to reconstruct a plan of a building. It is structured according to the physical principles of the sensors, since to a large extent these determine the function of the sensors and the methods of processing. Recent work using sonar, optoelectronic sensors and radar is described. Sections on vision and on sensor management develop the idea of software adaptation for efficient operation in a changing environment.