Intelligent Systems And Robotics

This is the first text of a series that focuses on developments in robotics and intelligent systems, and provides insight, guidance, and specific techniques for those concerned with the design and implementation of robotics and intelligent system applications.

Since the late 1960s, there has been a revolution in robots and industrial automation, from the design of robots with no computing or sensorycapabilities (first-generation), to the design of robots with limited computational power and feedback capabilities (second-generation), and the design of intelligent robots (third-generation), which possess diverse sensing and decision making capabilities. The development of the theory of intelligent machines has been developed in parallel to the advances in robot design. This theory is the natural outcome of research and development in classical control (1950s), adaptive and learning control (1960s), self-organizing control (1970s) and intelligent control systems (1980s). The theory of intelligent machines involves utilization and integration of concepts and ideas from the diverse disciplines of science, engineering and mathematics, and fields like artificial intelligence, system theory and operations research. The main focus and motivation is to bridge the gap between diverse disciplines involved and bring under a common cover several generic methodologies pertaining to what has been defined as machine intelligence. Intelligent robotic systems are a specific application of intelligent machines. They are complex computer controlled robotic systems equipped with a diverse set of visual and non visual sensors and possess decision making and problem solving capabilities within their domain of operation. Their modeling and control is accomplished via analytical and heuristic methodologies and techniques pertaining to generalized system theory and artificial intelligence. Intelligent Robotic Systems: Theory, Design and Applications, presents and justifies the fundamental concepts and ideas associated with the modeling and analysis of intelligent robotic systems. Appropriate for researchers and engineers in the general area of robotics and automation, Intelligent Robotic Systems is both a solid reference as well as a text for a graduate level course in intelligent robotics/machines.

As robotic systems make their way into standard practice, they have opened the door to a wide spectrum of complex applications. Such applications usually demand that the robots be highly intelligent. Future robots are likely to have greater sensory capabilities, more intelligence, higher levels of manual dexter ity, and adequate mobility, compared to humans. In order to ensure high-quality control and performance in robotics, new intelligent control techniques must be developed, which are capable of coping with task complexity, multi-objective decision making, large volumes of perception data and substantial amounts of heuristic information. Hence, the pursuit of intelligent autonomous robotic systems has been a topic of much fascinating research in recent years. On the other hand, as emerging technologies, Soft Computing paradigms consisting of complementary elements of Fuzzy Logic, Neural Computing and Evolutionary Computation are viewed as the most promising methods towards intelligent robotic systems. Due to their strong learning and cognitive ability and good tolerance of uncertainty and imprecision, Soft Computing techniques have found wide application in the area of intelligent control of robotic systems.

Intelligent Systems and Robotics focuses on new developments in robotics and intelligent systems and provides insight, guidance and specific techniques vital to those concerned with the design and implementation of robotics and intelligent system applications. Intelligent Systems and Robotics presents information on a 3-D vision for robots and intelligent control of a vision-based reasoning system with a robot manipulator. The reader will find authoritative presentations on autonomous land vehicle navigation, manipulator reachable workspace problems and the formulation of algorithms for their solution. Covered are methods for medical applications utilizing expert adaptive control, the integrated piezoelectric sensor/actuator design for distributed identification and control of smart machines, including theory, experiments, finite element formulation and analysis. Automatic repair of aircraft transparencies and geometric modeling utilized in robot task planning as well as the evaluation of standard fieldbus networks utilized in the factory environment are presented.

This collection of twenty-three timely contributions covers a well-selected repertory of topics within the autonomous systems field. The book discusses a range of design, construction, control, and operation problems along with a multiplicity of well-established and novel solutions.

Here is a comprehensive presentation of methodology for the design and synthesis of an intelligent complex robotic system, connecting formal tools from discrete system theory, artificial intelligence, neural network, and fuzzy logic. The necessary methods for solving real time action planning, coordination and control problems are described. A notable chapter presents a new approach to intelligent robotic agent control acting in a realworld environment based on a lifelong learning approach combining cognitive and reactive capabilities. Another key feature is the homogeneous description of all solutions and methods based on system theory formalism.

What is the Role of Intelligent Technologies in the Next Generation of Robots ? This monograph gives answers to this question and presents emergent trends of Intelligent Systems and Robotics. After an introductory chapter celebrating 70 year of publishing the McCulloch Pitts model the book consists of the 2 parts „Robotics“ and „Intelligent Systems“. The aim of the book is to contribute to shift conventional robotics in which the robots perform repetitive, pre-programmed tasks to its intelligent form, where robots possess new cognitive skills with ability to learn and adapt to changing environment. A main focus is on Intelligent Systems, which show notable achievements in solving various problems in intelligent robotics. The book presents current trends and future directions bringing together Robotics and Computational Intelligence. The contributions include widespread experimental and theoretical results on intelligent robotics such as e.g. autonomous robotics, new robotic platforms, or talking robots.

This book illustrates basic principles, along with the development of the advanced algorithms, to realize smart robotic systems. It speaks to strategies by which a robot (manipulators, mobile robot, quadrotor) can learn its own kinematics and dynamics from data. In this context, two major issues have been dealt with; namely, stability of the systems and experimental validations. Learning algorithms and techniques as covered in this book easily extend to other robotic systems as well. The book contains MATLAB- based examples and c-codes under robot operating systems (ROS) for experimental validation so that readers can replicate these algorithms in robotics platforms.