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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.
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 “benchmark” 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.
Obstacle Avoidance in Multi-robot Systems: Experiments in Parallel Genetic Algorithms offers a novel framework for solving the path planning problem for robot manipulators. Simple and efficient solutions are proposed for the path planning problem based on genetic algorithms. One of the attractive features of genetic algorithms is their ability to solve formidable problems in a robust and straightforward manner. Moreover, genetic algorithms are inherently parallel in nature, which makes them ideal candidates for parallel computing implementations.By combining the robustness of genetic algorithms with the power of parallel computers, this book provides an effective and practical approach to solving path planning problems. The book gives details of implementations that allow a better understanding of the complexities involved in the development of parallel path planning algorithms. The material presented is interdisciplinary in nature ? it combines topics from robotics, genetic algorithms, and parallel processing. The book can be used by practitioners and researchers in computer science and engineering.
This book starts with a short recapitulation on basic concepts, common to any types of robots (serial, tree structure, parallel, etc.), that are also necessary for computation of the dynamic models of parallel robots. Then, as dynamics requires the use of geometry and kinematics, the general equations of geometric and kinematic models of parallel robots are given. After, it is explained that parallel robot dynamic models can be obtained by decomposing the real robot into two virtual systems: a tree-structure robot (equivalent to the robot legs for which all joints would be actuated) plus a free body corresponding to the platform. Thus, the dynamics of rigid tree-structure robots is analyzed and algorithms to obtain their dynamic models in the most compact form are given. The dynamic model of the real rigid parallel robot is obtained by closing the loops through the use of the Lagrange multipliers. The problem of the dynamic model degeneracy near singularities is treated and optimal trajectory planning for crossing singularities is proposed. Lastly, the approach is extended to flexible parallel robots and the algorithms for computing their symbolic model in the most compact form are given. All theoretical developments are validated through experiments.
Parallel structures are more effective than serial ones for industrial automation applications that require high precision and stiffness, or a high load capacity relative to robot weight. Although many industrial applications have adopted parallel structures for their design, few textbooks introduce the analysis of such robots in terms of dynamics
The broadening of interest in parallel computing and transputers is reflected this book. Topics discussed include: concurrent programming; graphics and image processing; parallel applications; robotics; and control and software tools. The book also features a collection of abstracts of poster presentations.
Comprises papers based on an international conference held at Imperial College, London, July 1989. Topics covered include neural networks, robotics, image understanding, parallel implementations of logic languages, and parallel implementation of Lisp. Many of the papers here detail use of the INMOS transputer, and the Communicating Process Architecture on which INMOS was founded. But the theme is application of parallelism in a general way, especially in artificial intelligence.
The study of what can be computed by a team of autonomous mobile robots, originally started in robotics and AI, has become increasingly popular in theoretical computer science (especially in distributed computing), where it is now an integral part of the investigations on computability by mobile entities. The robots are identical computational entities located and able to move in a spatial universe; they operate without explicit communication and are usually unable to remember the past; they are extremely simple, with limited resources, and individually quite weak. However, collectively the robots are capable of performing complex tasks, and form a system with desirable fault-tolerant and self-stabilizing properties. The research has been concerned with the computational aspects of such systems. In particular, the focus has been on the minimal capabilities that the robots should have in order to solve a problem. This book focuses on the recent algorithmic results in the field of distributed computing by oblivious mobile robots (unable to remember the past). After introducing the computational model with its nuances, we focus on basic coordination problems: pattern formation, gathering, scattering, leader election, as well as on dynamic tasks such as flocking. For each of these problems, we provide a snapshot of the state of the art, reviewing the existing algorithmic results. In doing so, we outline solution techniques, and we analyze the impact of the different assumptions on the robots' computability power. Table of Contents: Introduction / Computational Models / Gathering and Convergence / Pattern Formation / Scatterings and Coverings / Flocking / Other Directions
Microprocessors play a dominant role in computer technology and have contributed uniquely in the development of many new concepts and design techniques for modem industrial systems. This contribution is excessively high in the area of robotic and manufacturing systems. However, it is the editor's feeling that a reference book describing this contribution in a cohesive way and covering the major hardware and software issues is lacking. The purpose of this book is exactly to fill in this gap through the collection and presentation of the experience of a number of experts and professionals working in different academic and industrial environments. The book is divided in three parts. Part 1 involves the first four chapters and deals with the utilization of microprocessors and digital signal processors ( DSPs ) for the computation of robot dynamics. The emphasis here is on parallel computation with particular problems attacked being task granularity, task allocation/scheduling and communication issues. Chapter I, by Zheng and Hemami, is concerned with the real-time multiprocessor computation of torques in robot control systems via the Newton-Euler equations. This reduces substantially the height of the evaluation tree which leads to more effective parallel processing. Chapter 2, by D'Hollander, examines thoroughly the automatic scheduling of the Newton-Euler inverse dynamic equations. The automatic program decomposition and scheduling techniques developed are embedded in a tool used to generate multiprocessor schedules from a high-level language program.
Robotic systems are characterized by the intersection of computer intelligence with the physical world. This blend of physical reasoning and computational intelligence is well illustrated by the Tetrobot study described in this book. Tetrobot: A Modular Approach to Reconfigurable Parallel Robotics describes a new approach to the design of robotic systems. The Tetrobot approach utilizes modular components which may be reconfigured into many different mechanisms which are suited to different applications. The Tetrobot system includes two unique contributions: a new mechanism (a multilink spherical joint design), and a new control architecture based on propagation of kinematic solutions through the structure. The resulting Tetrobot system consists of fundamental components which may be mechanically reassembled into any modular configuration, and the control architecture will provide position control of the resulting structure. A prototype Tetrobot system has been built and evaluated experimentally. Tetrobot arms, platforms, and walking machines have been built and controlled in a variety of motion and loading conditions. The Tetrobot system has applications in a variety of domains where reconfiguration, flexibility, load capacity, and failure recovery are important aspects of the task. A number of key research directions have been opened by the Tetrobot research activities. Continuing topics of interest include: development of a more distributed implementation of the computer control architecture, analysis of the dynamics of the Tetrobot system motion for improved control of high-speed motions, integration of sensor systems to control the motion and shape of the high-dimensionality systems, and exploration of self-reconfiguration of the system. Tetrobot: A Modular Approach to Reconfigurable Parallel Robotics will be of interest to research workers, specialists and professionals in the areas of robotics, mechanical systems and computer engineering.