Download or read book Kinematic Control of Redundant Robot Arms Using Neural Networks written by Shuai Li and published by John Wiley & Sons. This book was released on 2019-04-29 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents pioneering and comprehensive work on engaging movement in robotic arms, with a specific focus on neural networks This book presents and investigates different methods and schemes for the control of robotic arms whilst exploring the field from all angles. On a more specific level, it deals with the dynamic-neural-network based kinematic control of redundant robot arms by using theoretical tools and simulations. Kinematic Control of Redundant Robot Arms Using Neural Networks is divided into three parts: Neural Networks for Serial Robot Arm Control; Neural Networks for Parallel Robot Control; and Neural Networks for Cooperative Control. The book starts by covering zeroing neural networks for control, and follows up with chapters on adaptive dynamic programming neural networks for control; projection neural networks for robot arm control; and neural learning and control co-design for robot arm control. Next, it looks at robust neural controller design for robot arm control and teaches readers how to use neural networks to avoid robot singularity. It then instructs on neural network based Stewart platform control and neural network based learning and control co-design for Stewart platform control. The book finishes with a section on zeroing neural networks for robot arm motion generation. Provides comprehensive understanding on robot arm control aided with neural networks Presents neural network-based control techniques for single robot arms, parallel robot arms (Stewart platforms), and cooperative robot arms Provides a comparison of, and the advantages of, using neural networks for control purposes rather than traditional control based methods Includes simulation and modelling tasks (e.g., MATLAB) for onward application for research and engineering development By focusing on robot arm control aided by neural networks whilst examining central topics surrounding the field, Kinematic Control of Redundant Robot Arms Using Neural Networks is an excellent book for graduate students and academic and industrial researchers studying neural dynamics, neural networks, analog and digital circuits, mechatronics, and mechanical engineering.

Download or read book Learning Models to Control Redundancy in Robotics written by Camille Salaün and published by . This book was released on 2010 with total page 187 pages. Available in PDF, EPUB and Kindle. Book excerpt: La robotique de service est un domaine émergent où il est nécessaire de commander des robots en interaction forte avec leur environnement. Ce travail présente une méthode adaptative de commande combinant de l'apprentissage de modèles physiques et de la commande dans l'espace opérationnel de robots redondants. L'apprentissage des modèles cinématiques est obtenu soit par dérivation de modèles géométriques appris, soit par apprentissage direct. Ces modèles cinématiques, également appelés matrices Jacobiennes, peuvent être utilisés dans le calcul de pseudo-inverse ou de projecteurs pour la commande du robot. Cette combinaison de méthodes permet d'obtenir un contrôleur qui s'adapte à la géométrie du robot commandé. D'une façon similaire, il est également possible d'apprendre un modèle dynamique inverse du robot de manière à commander le robot en couple plutôt qu'en vitesse. Cela a pour avantage de pouvoir s'adapter aux modifications dynamiques qui s'appliquent sur le robot comme par exemple l'application d'une force extérieure ou l'ajout d'un poids. Les expériences menées dans le cadre de cette thèse montrent comment réaliser plusieurs tâches hiérarchiques ou comment s'adapter à des perturbations avec des modèles appris. Des application sur un robots réel ont également été menées afin de rendre compte de la plausibilité de l'approche proposée.

Download or read book AI based Robot Safe Learning and Control written by Xuefeng Zhou and published by Springer Nature. This book was released on 2020-06-02 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book mainly focuses on the safe control of robot manipulators. The control schemes are mainly developed based on dynamic neural network, which is an important theoretical branch of deep reinforcement learning. In order to enhance the safety performance of robot systems, the control strategies include adaptive tracking control for robots with model uncertainties, compliance control in uncertain environments, obstacle avoidance in dynamic workspace. The idea for this book on solving safe control of robot arms was conceived during the industrial applications and the research discussion in the laboratory. Most of the materials in this book are derived from the authors’ papers published in journals, such as IEEE Transactions on Industrial Electronics, neurocomputing, etc. This book can be used as a reference book for researcher and designer of the robotic systems and AI based controllers, and can also be used as a reference book for senior undergraduate and graduate students in colleges and universities.

Download or read book Kinematic Control of Redundant Robot Arms Using Neural Networks written by Shuai Li and published by John Wiley & Sons. This book was released on 2019-02-11 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents pioneering and comprehensive work on engaging movement in robotic arms, with a specific focus on neural networks This book presents and investigates different methods and schemes for the control of robotic arms whilst exploring the field from all angles. On a more specific level, it deals with the dynamic-neural-network based kinematic control of redundant robot arms by using theoretical tools and simulations. Kinematic Control of Redundant Robot Arms Using Neural Networks is divided into three parts: Neural Networks for Serial Robot Arm Control; Neural Networks for Parallel Robot Control; and Neural Networks for Cooperative Control. The book starts by covering zeroing neural networks for control, and follows up with chapters on adaptive dynamic programming neural networks for control; projection neural networks for robot arm control; and neural learning and control co-design for robot arm control. Next, it looks at robust neural controller design for robot arm control and teaches readers how to use neural networks to avoid robot singularity. It then instructs on neural network based Stewart platform control and neural network based learning and control co-design for Stewart platform control. The book finishes with a section on zeroing neural networks for robot arm motion generation. Provides comprehensive understanding on robot arm control aided with neural networks Presents neural network-based control techniques for single robot arms, parallel robot arms (Stewart platforms), and cooperative robot arms Provides a comparison of, and the advantages of, using neural networks for control purposes rather than traditional control based methods Includes simulation and modelling tasks (e.g., MATLAB) for onward application for research and engineering development By focusing on robot arm control aided by neural networks whilst examining central topics surrounding the field, Kinematic Control of Redundant Robot Arms Using Neural Networks is an excellent book for graduate students and academic and industrial researchers studying neural dynamics, neural networks, analog and digital circuits, mechatronics, and mechanical engineering.

Download or read book Cartesian Impedance Control of Redundant and Flexible Joint Robots written by Christian Ott and published by Springer Science & Business Media. This book was released on 2008-07-22 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: By the dawn of the new millennium, robotics has undergone a major transf- mation in scope and dimensions. This expansion has been brought about by the maturity of the ?eld and the advances in its related technologies. From a largely dominant industrial focus, robotics has been rapidly expanding into the challenges of the human world. The new generation of robots is expected to safely and dependably co-habitat with humans in homes, workplaces, and c- munities, providing support in services, entertainment, education, healthcare, manufacturing, and assistance. Beyond its impact on physical robots, the body of knowledge robotics has produced is revealing a much wider rangeof applications reaching across diverse research areas and scienti?c disciplines, such as: biomechanics, haptics, n- rosciences, virtual simulation, animation, surgery, and sensor networks among others. In return, the challenges of the new emerging areas are proving an ab- dant source of stimulation and insights for the ?eld of robotics. It is indeed at the intersection of disciplines that the most striking advances happen. The goal of the series of Springer Tracts in Advanced Robotics (STAR) is to bring, in a timely fashion, the latest advances and developments in robotics on thebasisoftheirsigni?canceandquality.Itisourhopethatthewiderdissemi- tion of research developments will stimulate more exchanges and collaborations among the research community and contribute to further advancement of this rapidly growing ?eld.

Download or read book Robot Manipulator Redundancy Resolution written by Yunong Zhang and published by John Wiley & Sons. This book was released on 2017-11-13 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces a revolutionary, quadratic-programming based approach to solving long-standing problems in motion planning and control of redundant manipulators This book describes a novel quadratic programming approach to solving redundancy resolutions problems with redundant manipulators. Known as ``QP-unified motion planning and control of redundant manipulators'' theory, it systematically solves difficult optimization problems of inequality-constrained motion planning and control of redundant manipulators that have plagued robotics engineers and systems designers for more than a quarter century. An example of redundancy resolution could involve a robotic limb with six joints, or degrees of freedom (DOFs), with which to position an object. As only five numbers are required to specify the position and orientation of the object, the robot can move with one remaining DOF through practically infinite poses while performing a specified task. In this case redundancy resolution refers to the process of choosing an optimal pose from among that infinite set. A critical issue in robotic systems control, the redundancy resolution problem has been widely studied for decades, and numerous solutions have been proposed. This book investigates various approaches to motion planning and control of redundant robot manipulators and describes the most successful strategy thus far developed for resolving redundancy resolution problems. Provides a fully connected, systematic, methodological, consecutive, and easy approach to solving redundancy resolution problems Describes a new approach to the time-varying Jacobian matrix pseudoinversion, applied to the redundant-manipulator kinematic control Introduces The QP-based unification of robots' redundancy resolution Illustrates the effectiveness of the methods presented using a large number of computer simulation results based on PUMA560, PA10, and planar robot manipulators Provides technical details for all schemes and solvers presented, for readers to adopt and customize them for specific industrial applications Robot Manipulator Redundancy Resolution is must-reading for advanced undergraduates and graduate students of robotics, mechatronics, mechanical engineering, tracking control, neural dynamics/neural networks, numerical algorithms, computation and optimization, simulation and modelling, analog, and digital circuits. It is also a valuable working resource for practicing robotics engineers and systems designers and industrial researchers.

Download or read book Advances in Modelling and Control of Soft Robots written by Concepción A. Monje and published by Frontiers Media SA. This book was released on 2021-07-14 with total page 175 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Control of Redundant Robot Manipulators written by Rajni V. Patel and published by Springer Science & Business Media. This book was released on 2005-05-04 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph provides a comprehensive and thorough treatment of the problem of controlling a redundant robot manipulator. It presents the latest research from the field with a good balance between theory and practice. All theoretical developments are verified both via simulation and experimental work on an actual prototype redundant robot manipulator. This book is the first text aimed at graduate students and researchers working in the area of redundant manipulators giving a comprehensive coverage of control of redundant robot manipulators from the viewpoint of theory and experimentation.

Download or read book Highly Redundant Sensing in Robotic Systems written by Julius T. Tou and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: Design of intelligent robots is one of the most important endeavors in robotics research today. The key to intelligent robot design lies in sensory systems for robotic control and manipulation. In an unstructural environment, robotic sensing translates measurements and characteristics of the environment and working objects into useful information. A robotic system is usually equipped with a variety of sensors to perform redundant sensing and achieve data fusion. This book contains revised versions of papers presented at a NATO Advanced Research Workshop held in Florida in September 1989 within the activities of the NATO Special Programme on Sensory Systems for Robotic Control. The fundamental issues addressed in this volume were: - Theory and techniques, including knowledge-based systems, geometrical fusion, Boolean fusion, probabilistic fusion, feature-based fusion, error-estimation approach, and Markov process modeling. - General concepts, including microscopic redundancy at the sensory element level, macroscopic redundancy at the sensory system level, parallel redundancy, and standby redundancy. - Implementation and application, including robotic control, sensory technology, robotic assembly, robot fingers, sensory signal processing, sensory system integration, and PAPIA architecture. - Biological analogies, including neural nets, pattern recognition, low-level fusion, and motor learning.

Download or read book Intelligent Control of Robotic Systems written by Laxmidhar Behera and published by CRC Press. This book was released on 2020-04-07 with total page 675 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Dynamic Neural Networks for Robot Systems Data Driven and Model Based Applications written by Long Jin and published by Frontiers Media SA. This book was released on 2024-07-24 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural network control has been a research hotspot in academic fields due to the strong ability of computation. One of its wildly applied fields is robotics. In recent years, plenty of researchers have devised different types of dynamic neural network (DNN) to address complex control issues in robotics fields in reality. Redundant manipulators are no doubt indispensable devices in industrial production. There are various works on the redundancy resolution of redundant manipulators in performing a given task with the manipulator model information known. However, it becomes knotty for researchers to precisely control redundant manipulators with unknown model to complete a cyclic-motion generation CMG task, to some extent. It is worthwhile to investigate the data-driven scheme and the corresponding novel dynamic neural network (DNN), which exploits learning and control simultaneously. Therefore, it is of great significance to further research the special control features and solve challenging issues to improve control performance from several perspectives, such as accuracy, robustness, and solving speed.

Download or read book Advances in Robot Control written by Sadao Kawamura and published by Springer Science & Business Media. This book was released on 2007-07-17 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume surveys three decades of modern robot control theory and describes how the work of Suguru Arimoto shaped its development. Twelve survey articles written by experts associated with Suguru Arimoto at various stages in his career treat the subject comprehensively. This book provides an important reference for graduate students and researchers, as well as for mathematicians, engineers and scientists whose work involves robot control theory.

Download or read book Human in the Loop Robot Control and Learning written by Luka Peternel and published by Frontiers Media SA. This book was released on 2020-01-22 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the past years there has been considerable effort to move robots from industrial environments to our daily lives where they can collaborate and interact with humans to improve our life quality. One of the key challenges in this direction is to make a suitable robot control system that can adapt to humans and interactively learn from humans to facilitate the efficient and safe co-existence of the two. The applications of such robotic systems include: service robotics and physical human-robot collaboration, assistive and rehabilitation robotics, semi-autonomous cars, etc. To achieve the goal of integrating robotic systems into these applications, several important research directions must be explored. One such direction is the study of skill transfer, where a human operator’s skilled executions are used to obtain an autonomous controller. Another important direction is shared control, where a robotic controller and humans control the same body, tool, mechanism, car, etc. Shared control, in turn invokes very rich research questions such as co-adaptation between the human and the robot, where the two agents can benefit from each other’s skills or must adapt to each other’s behavior to achieve effective cooperative task executions. The aim of this Research Topic is to help bridge the gap between the state-of-the-art and above-mentioned goals through novel multidisciplinary approaches in human-in-the-loop robot control and learning.

Download or read book Advanced Dynamics Modeling Duality and Control of Robotic Systems written by Edward Y.L. Gu and published by CRC Press. This book was released on 2021-09-24 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides detailed fundamental theoretical reviews and preparations necessary for developing advanced dynamics modeling and control strategies for various types of robotic systems. This research book specifically addresses and discusses the uniqueness issue of representing orientation or rotation, and further proposes an innovative isometric embedding approach. The novel approach can not only reduce the dynamic formulation for robotic systems into a compact form, but it also offers a new way to realize the orientational trajectory-tracking control procedures. In addition, the book gives a comprehensive introduction to fundamentals of mathematics and physics that are required for modeling robot dynamics and developing effective control algorithms. Many computer simulations and realistic 3D animations to verify the new theories and algorithms are included in the book as well. It also presents and discusses the principle of duality involved in robot kinematics, statics, and dynamics. The duality principle can guide the dynamics modeling and analysis into a right direction for a variety of robotic systems in different types from open serial-chain to closed parallel-chain mechanisms. It intends to serve as a diversified research reference to a wide range of audience, including undergraduate juniors and seniors, graduate students, researchers, and engineers interested in the areas of robotics, control and applications.

Download or read book Computational and Robotic Models of the Hierarchical Organization of Behavior written by Gianluca Baldassarre and published by Springer Science & Business Media. This book was released on 2013-11-19 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: Current robots and other artificial systems are typically able to accomplish only one single task. Overcoming this limitation requires the development of control architectures and learning algorithms that can support the acquisition and deployment of several different skills, which in turn seems to require a modular and hierarchical organization. In this way, different modules can acquire different skills without catastrophic interference, and higher-level components of the system can solve complex tasks by exploiting the skills encapsulated in the lower-level modules. While machine learning and robotics recognize the fundamental importance of the hierarchical organization of behavior for building robots that scale up to solve complex tasks, research in psychology and neuroscience shows increasing evidence that modularity and hierarchy are pivotal organization principles of behavior and of the brain. They might even lead to the cumulative acquisition of an ever-increasing number of skills, which seems to be a characteristic of mammals, and humans in particular. This book is a comprehensive overview of the state of the art on the modeling of the hierarchical organization of behavior in animals, and on its exploitation in robot controllers. The book perspective is highly interdisciplinary, featuring models belonging to all relevant areas, including machine learning, robotics, neural networks, and computational modeling in psychology and neuroscience. The book chapters review the authors' most recent contributions to the investigation of hierarchical behavior, and highlight the open questions and most promising research directions. As the contributing authors are among the pioneers carrying out fundamental work on this topic, the book covers the most important and topical issues in the field from a computationally informed, theoretically oriented perspective. The book will be of benefit to academic and industrial researchers and graduate students in related disciplines.

Download or read book Automated On line Diagnosis and Control Configuration in Robotic Systems Using Model Based Analytical Redundancy written by Vitaly M. Kmelnitsky and published by . This book was released on 2002 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Springer Handbook of Robotics written by Bruno Siciliano and published by Springer. This book was released on 2016-07-27 with total page 2259 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second edition of this handbook provides a state-of-the-art overview on the various aspects in the rapidly developing field of robotics. Reaching for the human frontier, robotics is vigorously engaged in the growing challenges of new emerging domains. Interacting, exploring, and working with humans, the new generation of robots will increasingly touch people and their lives. The credible prospect of practical robots among humans is the result of the scientific endeavour of a half a century of robotic developments that established robotics as a modern scientific discipline. The ongoing vibrant expansion and strong growth of the field during the last decade has fueled this second edition of the Springer Handbook of Robotics. The first edition of the handbook soon became a landmark in robotics publishing and won the American Association of Publishers PROSE Award for Excellence in Physical Sciences & Mathematics as well as the organization’s Award for Engineering & Technology. The second edition of the handbook, edited by two internationally renowned scientists with the support of an outstanding team of seven part editors and more than 200 authors, continues to be an authoritative reference for robotics researchers, newcomers to the field, and scholars from related disciplines. The contents have been restructured to achieve four main objectives: the enlargement of foundational topics for robotics, the enlightenment of design of various types of robotic systems, the extension of the treatment on robots moving in the environment, and the enrichment of advanced robotics applications. Further to an extensive update, fifteen new chapters have been introduced on emerging topics, and a new generation of authors have joined the handbook’s team. A novel addition to the second edition is a comprehensive collection of multimedia references to more than 700 videos, which bring valuable insight into the contents. The videos can be viewed directly augmented into the text with a smartphone or tablet using a unique and specially designed app. Springer Handbook of Robotics Multimedia Extension Portal: http://handbookofrobotics.org/