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Neural Networks Fundamentals In Mobile Robot Control Systems
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Book Synopsis Neural networks fundamentals in mobile robot control systems by : Михаил Медведев
Download or read book Neural networks fundamentals in mobile robot control systems written by Михаил Медведев and published by Litres. This book was released on 2022-01-29 with total page 146 pages. Available in PDF, EPUB and Kindle. Book excerpt: Включает полное и систематизированное изложение материала по учебной программе курса «Интеллектуальные системы управления роботами». Адресован студентам, обучающимся по программам бакалавриата и магистратуры по специальности «Мехатроника и робототехника» Института радиотехники и систем управления Южного федерального университета. Включает темы, посвященные введению в нейронные сети, их применению, основам обучения нейронных сетей, многослойным нейронным сетям с прямой связью, передовым методам обучения нейронных сетей и варианты индивидуальных упражнений.
Book Synopsis Neural Network Control Of Robot Manipulators And Non-Linear Systems by : F W Lewis
Download or read book Neural Network Control Of Robot Manipulators And Non-Linear Systems written by F W Lewis and published by CRC Press. This book was released on 1998-11-30 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: There has been great interest in "universal controllers" that mimic the functions of human processes to learn about the systems they are controlling on-line so that performance improves automatically. Neural network controllers are derived for robot manipulators in a variety of applications including position control, force control, link flexibility stabilization and the management of high-frequency joint and motor dynamics. The first chapter provides a background on neural networks and the second on dynamical systems and control. Chapter three introduces the robot control problem and standard techniques such as torque, adaptive and robust control. Subsequent chapters give design techniques and Stability Proofs For NN Controllers For Robot Arms, Practical Robotic systems with high frequency vibratory modes, force control and a general class of non-linear systems. The last chapters are devoted to discrete- time NN controllers. Throughout the text, worked examples are provided.
Book Synopsis Introduction to Mobile Robot Control by : Spyros G Tzafestas
Download or read book Introduction to Mobile Robot Control written by Spyros G Tzafestas and published by Elsevier. This book was released on 2013-10-03 with total page 718 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Mobile Robot Control provides a complete and concise study of modeling, control, and navigation methods for wheeled non-holonomic and omnidirectional mobile robots and manipulators. The book begins with a study of mobile robot drives and corresponding kinematic and dynamic models, and discusses the sensors used in mobile robotics. It then examines a variety of model-based, model-free, and vision-based controllers with unified proof of their stabilization and tracking performance, also addressing the problems of path, motion, and task planning, along with localization and mapping topics. The book provides a host of experimental results, a conceptual overview of systemic and software mobile robot control architectures, and a tour of the use of wheeled mobile robots and manipulators in industry and society. Introduction to Mobile Robot Control is an essential reference, and is also a textbook suitable as a supplement for many university robotics courses. It is accessible to all and can be used as a reference for professionals and researchers in the mobile robotics field. Clearly and authoritatively presents mobile robot concepts Richly illustrated throughout with figures and examples Key concepts demonstrated with a host of experimental and simulation examples No prior knowledge of the subject is required; each chapter commences with an introduction and background
Book Synopsis High-level Feedback Control With Neural Networks by : Young Ho Kim
Download or read book High-level Feedback Control With Neural Networks written by Young Ho Kim and published by World Scientific. This book was released on 1998-09-28 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: Complex industrial or robotic systems with uncertainty and disturbances are difficult to control. As system uncertainty or performance requirements increase, it becomes necessary to augment traditional feedback controllers with additional feedback loops that effectively “add intelligence” to the system. Some theories of artificial intelligence (AI) are now showing how complex machine systems should mimic human cognitive and biological processes to improve their capabilities for dealing with uncertainty.This book bridges the gap between feedback control and AI. It provides design techniques for “high-level” neural-network feedback-control topologies that contain servo-level feedback-control loops as well as AI decision and training at the higher levels. Several advanced feedback topologies containing neural networks are presented, including “dynamic output feedback”, “reinforcement learning” and “optimal design”, as well as a “fuzzy-logic reinforcement” controller. The control topologies are intuitive, yet are derived using sound mathematical principles where proofs of stability are given so that closed-loop performance can be relied upon in using these control systems. Computer-simulation examples are given to illustrate the performance.
Book Synopsis Radial Basis Function (RBF) Neural Network Control for Mechanical Systems by : Jinkun Liu
Download or read book Radial Basis Function (RBF) Neural Network Control for Mechanical Systems written by Jinkun Liu and published by Springer Science & Business Media. This book was released on 2013-01-26 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: Radial Basis Function (RBF) Neural Network Control for Mechanical Systems is motivated by the need for systematic design approaches to stable adaptive control system design using neural network approximation-based techniques. The main objectives of the book are to introduce the concrete design methods and MATLAB simulation of stable adaptive RBF neural control strategies. In this book, a broad range of implementable neural network control design methods for mechanical systems are presented, such as robot manipulators, inverted pendulums, single link flexible joint robots, motors, etc. Advanced neural network controller design methods and their stability analysis are explored. The book provides readers with the fundamentals of neural network control system design. This book is intended for the researchers in the fields of neural adaptive control, mechanical systems, Matlab simulation, engineering design, robotics and automation. Jinkun Liu is a professor at Beijing University of Aeronautics and Astronautics.
Book Synopsis Neural Network Perception for Mobile Robot Guidance by : Dean A. Pomerleau
Download or read book Neural Network Perception for Mobile Robot Guidance written by Dean A. Pomerleau and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 199 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dean Pomerleau's trainable road tracker, ALVINN, is arguably the world's most famous neural net application. It currently holds the world's record for distance traveled by an autonomous robot without interruption: 21.2 miles along a highway, in traffic, at speedsofup to 55 miles per hour. Pomerleau's work has received worldwide attention, including articles in Business Week (March 2, 1992), Discover (July, 1992), and German and Japanese science magazines. It has been featured in two PBS series, "The Machine That Changed the World" and "By the Year 2000," and appeared in news segments on CNN, the Canadian news and entertainment program "Live It Up", and the Danish science program "Chaos". What makes ALVINN especially appealing is that it does not merely drive - it learns to drive, by watching a human driver for roughly five minutes. The training inputstothe neural networkare a video imageoftheroad ahead and thecurrentposition of the steering wheel. ALVINN has learned to drive on single lane, multi-lane, and unpaved roads. It rapidly adapts to other sensors: it learned to drive at night using laser reflectance imaging, and by using a laser rangefinder it learned to swerve to avoid obstacles and maintain a fixed distance from a row of parked cars. It has even learned to drive backwards.
Book Synopsis Unsupervised Neural Network for the Control of a Mobile Robot by : Eduardo Zalama
Download or read book Unsupervised Neural Network for the Control of a Mobile Robot written by Eduardo Zalama and published by . This book was released on 1993 with total page 8 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Model Abstraction in Dynamical Systems: Application to Mobile Robot Control by : Patricia Mellodge
Download or read book Model Abstraction in Dynamical Systems: Application to Mobile Robot Control written by Patricia Mellodge and published by Springer. This book was released on 2008-09-18 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt: The subject of this book is model abstraction of dynamical systems. The p- mary goal of the work embodied in this book is to design a controller for the mobile robotic car using abstraction. Abstraction provides a means to rep- sent the dynamics of a system using a simpler model while retaining important characteristics of the original system. A second goal of this work is to study the propagation of uncertain initial conditions in the framework of abstraction. The summation of this work is presented in this book. It includes the following: • An overview of the history and current research in mobile robotic control design. • A mathematical review that provides the tools used in this research area. • The development of the robotic car model and both controllers used in the new control design. • A review of abstraction and an extension of these ideas into new system relationship characterizations called traceability and -traceability. • A framework for designing controllers based on abstraction. • An open-loop control design with simulation results. • An investigation of system abstraction with uncertain initial conditions.
Book Synopsis Mobile Robot Control by a Biologically Inspired Neural Network Structure by : Raúl E. Torres Muñiz
Download or read book Mobile Robot Control by a Biologically Inspired Neural Network Structure written by Raúl E. Torres Muñiz and published by . This book was released on 1998 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Adaptive Kinematic Control of Mobile Robot Based on Neural Networks by : Al-Shibaany Zeyad Yousif Abdoon
Download or read book Adaptive Kinematic Control of Mobile Robot Based on Neural Networks written by Al-Shibaany Zeyad Yousif Abdoon and published by LAP Lambert Academic Publishing. This book was released on 2015-11-03 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: The applications of mobile robots have grown significantly during the last few years due to the fast development in sensors and microprocessors systems. These applications include material handling, hospital services, military applications ... etc. The need for a precise motion control becomes very crucial in order to support such applications. The adaptive motion control for mobile robot is one of the important areas of research. The design of an adaptive kinematic controller for a nonholonomic differential drive mobile robot based on neural network topology is considered in this work, and work is divided into three stages. Firstly, to identify the inverse kinematics behavior of the differential drive mobile robot system, the Multi-Layer Perceptron neural network has been used. The second stage is the simulation test to check the robustness of the controller. The final stage is the practical work. A National Instrument differential drive mobile robot platform has been used which is perfectly compatible with the LabVIEW2011 software. The controller is implemented in LabVIEW2011 and then deployed to the mobile robot kit through a wireless communication.
Book Synopsis Neural Networks in Robotics by : George Bekey
Download or read book Neural Networks in Robotics written by George Bekey and published by Springer Science & Business Media. This book was released on 1992-11-30 with total page 582 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural Networks in Robotics is the first book to present an integrated view of both the application of artificial neural networks to robot control and the neuromuscular models from which robots were created. The behavior of biological systems provides both the inspiration and the challenge for robotics. The goal is to build robots which can emulate the ability of living organisms to integrate perceptual inputs smoothly with motor responses, even in the presence of novel stimuli and changes in the environment. The ability of living systems to learn and to adapt provides the standard against which robotic systems are judged. In order to emulate these abilities, a number of investigators have attempted to create robot controllers which are modelled on known processes in the brain and musculo-skeletal system. Several of these models are described in this book. On the other hand, connectionist (artificial neural network) formulations are attractive for the computation of inverse kinematics and dynamics of robots, because they can be trained for this purpose without explicit programming. Some of the computational advantages and problems of this approach are also presented. For any serious student of robotics, Neural Networks in Robotics provides an indispensable reference to the work of major researchers in the field. Similarly, since robotics is an outstanding application area for artificial neural networks, Neural Networks in Robotics is equally important to workers in connectionism and to students for sensormonitor control in living systems.
Book Synopsis Computational Intelligence for Modelling, Control & Automation by : Masoud Mohammadian
Download or read book Computational Intelligence for Modelling, Control & Automation written by Masoud Mohammadian and published by IOS Press. This book was released on 1999 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reliable and straightforward, this text has helped thousands of students learn to write well. Jean Wyrick's rhetorically organized STEPS TO WRITING WELL WITH ADDITIONAL READINGS is known for its student-friendly tone and the clear way it presents the basics of essay writing in an easy-to-follow progression of useful lessons and activities. Through straightforward advice and thoughtful assignments, the text gives students the practice they need to approach writing well-constructed essays with confidence. With Wyrick's helpful instruction and the book's professional samples by both well-known classic and contemporary writers, STEPS TO WRITING WELL WITH ADDITIONAL READINGS sets students on a solid path to writing success. Everything students need to begin, organize, and revise writing--from choosing a topic to developing the essay to polishing prose--is right here In the ninth edition, Wyrick updates and refines the book's successful approach, adding useful new discussions, readings, exercises, essay assignments, and visual images for analysis.
Book Synopsis Robot Control using an Artificial Neural Network by : Olaf Wandel
Download or read book Robot Control using an Artificial Neural Network written by Olaf Wandel and published by diplom.de. This book was released on 2001-05-16 with total page 58 pages. Available in PDF, EPUB and Kindle. Book excerpt: Inhaltsangabe:Abstract: The aim of the project was to control three joints of an industrial robot in terms of its position, velocity and acceleration. The work considered the necessary hardware, principles of neural networks and controlling techniques. The hardware comprised of a robot with three DC-motors and three optical position encoders, a personal computer with a D/A card for voltage output to the robot and two D/D cards. One D/D card for receiving values from the optical encoders and one for timing. The basics of artificial neural network type perceptrons were described. The special features bias, output feedback, momentum term, adjustment of momentum factor and adjustment of learning rate for this artificial neural network type were considered. An introduction to learning and control structures using artificial neural networks were given. These were controller copying, direct modelling, direct inverse modelling, control with a model and an inverse model, forward and inverse modelling, control action feedback error learning, feedback error learning, learning and control using the plant s Jacobian. The conversion of two learning and control structures, direct inverse modelling and control action feedback error learning, was implemented in software using MS QuickBASIC 4.5 . One joint was controlled with a direct inverse model. One joint and all joints together were controlled with control action feedback error learning. The results of experiments with these learning and control structures were documented. Inhaltsverzeichnis:Table of Contents: 1.Introduction8 2.The hardware9 2.1The robot9 2.2The computer and the software11 2.3The PCL-726 D/A card11 2.4The D/D card11 2.5The PCL-812 D/D card12 2.6The G64 rack12 3.Neural networks13 3.1The neuron13 3.2Conversion of neural networks14 3.3Learning principles of neural networks17 3.4Special modifications to the neural network used19 3.5Learning capacity22 4.Teaching and control techniques23 5.The software28 5.1The teaching and control program28 5.1.1The direct inverse modelling and trajectory estimation program29 5.1.2The control action feedback error learning program30 6.Experiments with learning and control structures31 6.1Direct inverse modelling31 6.1.1Direct inverse modelling of the waist32 6.1.2Trajectory estimation for the waist34 6.2Control action feedback error learning (CAFEL)36 6.2.1Control action feedback error learning of the waist37 6.2.2Control action [...]
Book Synopsis Adaptive Neural Network Control Of Robotic Manipulators by : Sam Shuzhi Ge
Download or read book Adaptive Neural Network Control Of Robotic Manipulators written by Sam Shuzhi Ge and published by World Scientific. This book was released on 1998-12-04 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recently, there has been considerable research interest in neural network control of robots, and satisfactory results have been obtained in solving some of the special issues associated with the problems of robot control in an “on-and-off” fashion. This book is dedicated to issues on adaptive control of robots based on neural networks. The text has been carefully tailored to (i) give a comprehensive study of robot dynamics, (ii) present structured network models for robots, and (iii) provide systematic approaches for neural network based adaptive controller design for rigid robots, flexible joint robots, and robots in constraint motion. Rigorous proof of the stability properties of adaptive neural network controllers is provided. Simulation examples are also presented to verify the effectiveness of the controllers, and practical implementation issues associated with the controllers are also discussed.
Book Synopsis Dynamic Neural Networks for Robot Systems: Data-Driven and Model-Based Applications by : Long Jin
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.
Book Synopsis Wheeled Mobile Robotics by : Gregor Klancar
Download or read book Wheeled Mobile Robotics written by Gregor Klancar and published by Butterworth-Heinemann. This book was released on 2017-02-02 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: Wheeled Mobile Robotics: From Fundamentals Towards Autonomous Systemscovers the main topics from the wide area of mobile robotics, explaining all applied theory and application. The book gives the reader a good foundation, enabling them to continue to more advanced topics. Several examples are included for better understanding, many of them accompanied by short MATLAB® script code making it easy to reuse in practical work. The book includes several examples of discussed methods and projects for wheeled mobile robots and some advanced methods for their control and localization. It is an ideal resource for those seeking an understanding of robotics, mechanics, and control, and for engineers and researchers in industrial and other specialized research institutions in the field of wheeled mobile robotics. Beginners with basic math knowledge will benefit from the examples, and engineers with an understanding of basic system theory and control will find it easy to follow the more demanding fundamental parts and advanced methods explained. Offers comprehensive coverage of the essentials of the field that are suitable for both academics and practitioners Includes several examples of the application of algorithms in simulations and real laboratory projects Presents foundation in mobile robotics theory before continuing with more advanced topics Self-sufficient to beginner readers, covering all important topics in the mobile robotics field Contains specific topics on modeling, control, sensing, path planning, localization, design architectures, and multi-agent systems
Book Synopsis Intelligent Autonomous Systems 12 by : Sukhan Lee
Download or read book Intelligent Autonomous Systems 12 written by Sukhan Lee and published by Springer Science & Business Media. This book was released on 2012-11-02 with total page 861 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligent autonomous systems are emerged as a key enabler for the creation of a new paradigm of services to humankind, as seen by the recent advancement of autonomous cars licensed for driving in our streets, of unmanned aerial and underwater vehicles carrying out hazardous tasks on-site, and of space robots engaged in scientific as well as operational missions, to list only a few. This book aims at serving the researchers and practitioners in related fields with a timely dissemination of the recent progress on intelligent autonomous systems, based on a collection of papers presented at the 12th International Conference on Intelligent Autonomous Systems, held in Jeju, Korea, June 26-29, 2012. With the theme of “Intelligence and Autonomy for the Service to Humankind, the conference has covered such diverse areas as autonomous ground, aerial, and underwater vehicles, intelligent transportation systems, personal/domestic service robots, professional service robots for surgery/rehabilitation, rescue/security and space applications, and intelligent autonomous systems for manufacturing and healthcare. This volume 1 includes contributions devoted to Autonomous Ground Vehicles and Mobile Manipulators, as well as Unmanned Aerial and Underwater Vehicles and Bio-inspired Robotics.
