Robotic Systems and Autonomous Platforms: Advances in Materials and Manufacturing showcases new materials and manufacturing methodologies for the enhancement of robotic and autonomous systems. Initial chapters explore how autonomous systems can enable new uses for materials, including innovations on different length scales, from nano, to macro and large systems. The means by which autonomous systems can enable new uses for manufacturing are also addressed, highlighting innovations in 3D additive manufacturing, printing of materials, novel synthesis of multifunctional materials, and robotic cooperation. Concluding themes deliver highly novel applications from the international academic, industrial and government sectors. This book will provide readers with a complete review of the cutting-edge advances in materials and manufacturing methodologies that could enhance the capabilities of robotic and autonomous systems. - Presents comprehensive coverage of materials and manufacturing technologies, as well as sections on related technology, such as sensing, communications, autonomy/control and actuation - Explores potential applications demonstrated by a selection of case-studies - Contains contributions from leading experts in the field

A comprehensive review of the principles and dynamics of robotic systems Dynamics and Control of Robotic Systems offers a systematic and thorough theoretical background for the study of the dynamics and control of robotic systems. The authors—noted experts in the field—highlight the underlying principles of dynamics and control that can be employed in a variety of contemporary applications. The book contains a detailed presentation of the precepts of robotics and provides methodologies that are relevant to realistic robotic systems. The robotic systems represented include wide range examples from classical industrial manipulators, humanoid robots to robotic surgical assistants, space vehicles, and computer controlled milling machines. The book puts the emphasis on the systematic application of the underlying principles and show how the computational and analytical tools such as MATLAB, Mathematica, and Maple enable students to focus on robotics’ principles and theory. Dynamics and Control of Robotic Systems contains an extensive collection of examples and problems and: Puts the focus on the fundamentals of kinematics and dynamics as applied to robotic systems Presents the techniques of analytical mechanics of robotics Includes a review of advanced topics such as the recursive order N formulation Contains a wide array of design and analysis problems for robotic systems Written for students of robotics, Dynamics and Control of Robotic Systems offers a comprehensive review of the underlying principles and methods of the science of robotics.

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.

Niku offers comprehensive, yet concise coverage of robotics that will appeal to engineers. Robotic applications are drawn from a wide variety of fields. Emphasis is placed on design along with analysis and modeling. Kinematics and dynamics are covered extensively in an accessible style. Vision systems are discussed in detail, which is a cutting-edge area in robotics. Engineers will also find a running design project that reinforces the concepts by having them apply what they’ve learned.

Based on the author's wide-ranging experience as a robot user, supplier and consultant, Implementation of Robot Systems will enable you to approach the use of robots in your plant or facility armed with the right knowledge base and awareness of critical factors to take into account.This book starts with the basics of typical applications and robot capabilities before covering all stages of successful robot integration. Potential problems and pitfalls are flagged and worked through so that you can learn from others' mistakes and plan proactively with possible issues in mind.Taking in content from the author's graduate level teaching of automation and robotics for engineering in business and his consultancy as part of a UK Government program to help companies advance their technologies and practices in the area, Implementation of Robot Systems blends technical information with critical financial and business considerations to help you stay ahead of the competition. - Includes case studies of typical robot capabilities and use across a range of industries, with real-world installation examples and problems encountered - Provides step-by-step coverage of the various stages required to achieve successful implementation, including system design, financial justification, working with suppliers and project management - Offers no-nonsense advice on the pitfalls and issues to anticipate, along with guidance on how to avoid or resolve them for cost and time-effective solutions

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.

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.