Neural Systems For Robotics
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Neural Systems For Robotics
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Author : Omid Omidvar
language : en
Publisher: Elsevier
Release Date : 2012-12-02
Neural Systems For Robotics written by Omid Omidvar and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-02 with Computers categories.
Neural Systems for Robotics represents the most up-to-date developments in the rapidly growing aplication area of neural networks, which is one of the hottest application areas for neural networks technology. The book not only contains a comprehensive study of neurocontrollers in complex Robotics systems, written by highly respected researchers in the field but outlines a novel approach to solving Robotics problems. The importance of neural networks in all aspects of Robot arm manipulators, neurocontrol, and Robotic systems is also given thorough and in-depth coverage. All researchers and students dealing with Robotics will find Neural Systems for Robotics of immense interest and assistance. Focuses on the use of neural networks in robotics-one of the hottest application areas for neural networks technology Represents the most up-to-date developments in this rapidly growing application area of neural networks Contains a new and novel approach to solving Robotics problems
Neural Network Control Of Robot Manipulators And Non Linear Systems
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Author : F W Lewis
language : en
Publisher: CRC Press
Release Date : 1998-11-30
Neural Network Control Of Robot Manipulators And Non Linear Systems written by F W Lewis and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-11-30 with Technology & Engineering categories.
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.
Deep Learning For Robot Perception And Cognition
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Author : Alexandros Iosifidis
language : en
Publisher: Academic Press
Release Date : 2022-02-04
Deep Learning For Robot Perception And Cognition written by Alexandros Iosifidis and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-04 with Technology & Engineering categories.
Deep Learning for Robot Perception and Cognition introduces a broad range of topics and methods in deep learning for robot perception and cognition together with end-to-end methodologies. The book provides the conceptual and mathematical background needed for approaching a large number of robot perception and cognition tasks from an end-to-end learning point-of-view. The book is suitable for students, university and industry researchers and practitioners in Robotic Vision, Intelligent Control, Mechatronics, Deep Learning, Robotic Perception and Cognition tasks. - Presents deep learning principles and methodologies - Explains the principles of applying end-to-end learning in robotics applications - Presents how to design and train deep learning models - Shows how to apply deep learning in robot vision tasks such as object recognition, image classification, video analysis, and more - Uses robotic simulation environments for training deep learning models - Applies deep learning methods for different tasks ranging from planning and navigation to biosignal analysis
Neural Systems For Control
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Author : Omid Omidvar
language : en
Publisher: Elsevier
Release Date : 1997-02-24
Neural Systems For Control written by Omid Omidvar and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997-02-24 with Computers categories.
Control problems offer an industrially important application and a guide to understanding control systems for those working in Neural Networks. Neural Systems for Control represents the most up-to-date developments in the rapidly growing aplication area of neural networks and focuses on research in natural and artifical neural systems directly applicable to control or making use of modern control theory. The book covers such important new developments in control systems such as intelligent sensors in semiconductor wafer manufacturing; the relation between muscles and cerebral neurons in speech recognition; online compensation of reconfigurable control for spacecraft aircraft and other systems; applications to rolling mills, robotics and process control; the usage of past output data to identify nonlinear systems by neural networks; neural approximate optimal control; model-free nonlinear control; and neural control based on a regulation of physiological investigation/blood pressure control. All researchers and students dealing with control systems will find the fascinating Neural Systems for Control of immense interest and assistance. - Focuses on research in natural and artifical neural systems directly applicable to contol or making use of modern control theory - Represents the most up-to-date developments in this rapidly growing application area of neural networks - Takes a new and novel approach to system identification and synthesis
Neural Networks In Robotics
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Author : George A. Bekey
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Neural Networks In Robotics written by George A. Bekey and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Technology & Engineering categories.
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.
Neural Networks For Robotics
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Author : Nancy Arana-Daniel
language : en
Publisher: CRC Press
Release Date : 2018-09-06
Neural Networks For Robotics written by Nancy Arana-Daniel and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-06 with Technology & Engineering categories.
The book offers an insight on artificial neural networks for giving a robot a high level of autonomous tasks, such as navigation, cost mapping, object recognition, intelligent control of ground and aerial robots, and clustering, with real-time implementations. The reader will learn various methodologies that can be used to solve each stage on autonomous navigation for robots, from object recognition, clustering of obstacles, cost mapping of environments, path planning, and vision to low level control. These methodologies include real-life scenarios to implement a wide range of artificial neural network architectures. Includes real-time examples for various robotic platforms. Discusses real-time implementation for land and aerial robots. Presents solutions for problems encountered in autonomous navigation. Explores the mathematical preliminaries needed to understand the proposed methodologies. Integrates computing, communications, control, sensing, planning, and other techniques by means of artificial neural networks for robotics.
Adaptive Neural Network Control Of Robotic Manipulators
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Author : Shuzhi S. Ge
language : en
Publisher: World Scientific Series In Robotics And Intelligent Systems
Release Date : 1998
Adaptive Neural Network Control Of Robotic Manipulators written by Shuzhi S. Ge and has been published by World Scientific Series In Robotics And Intelligent Systems this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Technology & Engineering categories.
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.
Applications Of Neural Adaptive Control Technology
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Author : Jens Kalkkuhl
language : en
Publisher: World Scientific
Release Date : 1997
Applications Of Neural Adaptive Control Technology written by Jens Kalkkuhl and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with Technology & Engineering categories.
This book presents the results of the second workshop on Neural Adaptive Control Technology, NACT II, held on September 9-10, 1996, in Berlin. The workshop was organised in connection with a three-year European-Union-funded Basic Research Project in the ESPRIT framework, called NACT, a collaboration between Daimler-Benz (Germany) and the University of Glasgow (Scotland).The NACT project, which began on 1 April 1994, is a study of the fundamental properties of neural-network-based adaptive control systems. Where possible, links with traditional adaptive control systems are exploited. A major aim is to develop a systematic engineering procedure for designing neural controllers for nonlinear dynamic systems. The techniques developed are being evaluated on concrete industrial problems from within the Daimler-Benz group of companies.The aim of the workshop was to bring together selected invited specialists in the fields of adaptive control, nonlinear systems and neural networks. The first workshop (NACT I) took place in Glasgow in May 1995 and was mainly devoted to theoretical issues of neural adaptive control. Besides monitoring further development of theory, the NACT II workshop was focused on industrial applications and software tools. This context dictated the focus of the book and guided the editors in the choice of the papers and their subsequent reshaping into substantive book chapters. Thus, with the project having progressed into its applications stage, emphasis is put on the transfer of theory of neural adaptive engineering into industrial practice. The contributors are therefore both renowned academics and practitioners from major industrial users of neurocontrol.
Applied Neural Networks In The Ai Era From Theory To Real World Impact
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Author : Benziane, Sarah
language : en
Publisher: IGI Global
Release Date : 2025-06-11
Applied Neural Networks In The Ai Era From Theory To Real World Impact written by Benziane, Sarah and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-11 with Computers categories.
In the era of artificial intelligence (AI), applied neural networks transition from theoretical constructs to powerful tools driving innovation across sectors. Neural networks can learn patterns, make predictions, and adapt to complex data. From powering image and speech recognition systems to enabling autonomous vehicles and enhancing medical diagnostics, their impact is continually expanding. Advances in computational power, big data, and algorithmic design accelerate this transformation, making neural networks critical to AI applications. As these models become integrated into everyday technologies, further research into their design, limitations, and ethical implications becomes pivotal. Applied Neural Networks in the AI Era: From Theory to Real-World Impact explores the integration of intelligent technologies into neural networks. It examines the application of neural networks in various sectors, including transportation, medicine, computing, etc. This book covers topics such as biology, cloud computing, and smart robotics, and is a useful resource for engineers, business owners, academicians, researchers, and computer scientists.
Closing The Loop Around Neural Systems
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Author : Steve M Potter
language : en
Publisher: Frontiers Media SA
Release Date : 2014-12-03
Closing The Loop Around Neural Systems written by Steve M Potter and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-03 with Neurophysiology categories.
Closed-loop neurophysiology has been accelerated by recent software and hardware developments and by the emergence of novel tools to control neuronal activity with spatial and temporal precision, in which stimuli are delivered in real time based on recordings or behavior. Real-time stimulation feedback enables a wide range of innovative studies of information processing and plasticity in neuronal networks. This Research Topic e-Book comprises 16 Original Research Articles, seven Methods Articles, and seven Reviews, Mini- Reviews, and Perspectives, all peer-reviewed and published in Frontiers in Neural Circuits. The contributions deal with closed loop neurophysiology experiments at a variety of levels of neural circuit complexity. Some include modeling and theoretical analyses. New enabling technologies and techniques are described. Novel work is presented from experiments in vitro, in vivo, and in humans, along with their clinical and technological implications for improving the human condition.