Competition Based Neural Networks With Robotic Applications
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| Author | : Shuai Li |
| Publisher | : Springer |
| Total Pages | : 132 |
| Release | : 2017-05-30 |
| Genre | : Technology & Engineering |
| ISBN | : 9811049475 |
Focused on solving competition-based problems, this book designs, proposes, develops, analyzes and simulates various neural network models depicted in centralized and distributed manners. Specifically, it defines four different classes of centralized models for investigating the resultant competition in a group of multiple agents. With regard to distributed competition with limited communication among agents, the book presents the first distributed WTA (Winners Take All) protocol, which it subsequently extends to the distributed coordination control of multiple robots. Illustrations, tables, and various simulative examples, as well as a healthy mix of plain and professional language, are used to explain the concepts and complex principles involved. Thus, the book provides readers in neurocomputing and robotics with a deeper understanding of the neural network approach to competition-based problem-solving, offers them an accessible introduction to modeling technology and the distributed coordination control of redundant robots, and equips them to use these technologies and approaches to solve concrete scientific and engineering problems.
| Author | : Long Jin |
| Publisher | : Frontiers Media SA |
| Total Pages | : 301 |
| Release | : 2024-07-24 |
| Genre | : Science |
| ISBN | : 2832552013 |
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.
| Author | : Shuai Li |
| Publisher | : John Wiley & Sons |
| Total Pages | : 300 |
| Release | : 2019-02-12 |
| Genre | : Technology & Engineering |
| ISBN | : 1119556996 |
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.
| Author | : M. Arif Wani |
| Publisher | : Springer Nature |
| Total Pages | : 184 |
| Release | : 2020-02-28 |
| Genre | : Technology & Engineering |
| ISBN | : 9811518165 |
This book presents a compilation of selected papers from the 17th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2018), focusing on use of deep learning technology in application like game playing, medical applications, video analytics, regression/classification, object detection/recognition and robotic control in industrial environments. It highlights novel ways of using deep neural networks to solve real-world problems, and also offers insights into deep learning architectures and algorithms, making it an essential reference guide for academic researchers, professionals, software engineers in industry, and innovative product developers.
| Author | : Huajin Tang |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 310 |
| Release | : 2007-03-12 |
| Genre | : Computers |
| ISBN | : 3540692258 |
Neural Networks: Computational Models and Applications presents important theoretical and practical issues in neural networks, including the learning algorithms of feed-forward neural networks, various dynamical properties of recurrent neural networks, winner-take-all networks and their applications in broad manifolds of computational intelligence: pattern recognition, uniform approximation, constrained optimization, NP-hard problems, and image segmentation. The book offers a compact, insightful understanding of the broad and rapidly growing neural networks domain.
| Author | : Jinwhan Kim |
| Publisher | : Springer Nature |
| Total Pages | : 619 |
| Release | : 2022-03-31 |
| Genre | : Technology & Engineering |
| ISBN | : 3030976726 |
This book aims at serving the researchers and practitioners in related fields with a timely dissemination of the recent progress on robotics and artificial intelligence. This book is based on a collection of papers presented at the 9th International Conference on Robot Intelligence Technology and Applications (RiTA), held at KAIST in Daejeon, Korea, in a hybrid format, on December 16–17, 2021. Humankind is getting through the third year of COVID-19 pandemic. While this pandemic has made everyone’s life so challenging, it has also expedited transition of our everyday lives into a new form, often called “the new normal.” Although many people often use the terminology, perhaps we still do not have a consensus about what it is and what is should be like. One thing that is clear is that robotics and artificial intelligence technologies are playing critical roles in this phase transition of our everyday lives. We see last-mile delivery robots on the street, AI-embedded service robots in the restaurants, uninhabited shops, non-face-to-face medical services, conferences and talks in metaverses and AI-based online education programs. For better readability, the total of 53 papers are grouped into four chapters: Chapter I: Motion Planning and Control; Chapter II: Design and Robot Application; Chapter III: Sensing, Perception and Recognition; and Chapter IV: Cognition, Autonomy and Intelligence. For those who have research on robot intelligence technology, we believe this book will help them understand the recent robot technologies and applications and enhance their study.
| Author | : Amit Joshi |
| Publisher | : Springer Nature |
| Total Pages | : 1128 |
| Release | : 2021-07-26 |
| Genre | : Technology & Engineering |
| ISBN | : 9811607397 |
This book contains the best selected research papers presented at ICTCS 2020: Fifth International Conference on Information and Communication Technology for Competitive Strategies. The conference was held at Jaipur, Rajasthan, India, during 11–12 December 2020. The book covers state-of-the-art as well as emerging topics pertaining to ICT and effective strategies for its implementation for engineering and managerial applications. This book contains papers mainly focused on ICT for computation, algorithms and data analytics, and IT security.
| Author | : George Bekey |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 582 |
| Release | : 1992-11-30 |
| Genre | : Technology & Engineering |
| ISBN | : 9780792392682 |
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.
| Author | : Jong-Hwan Kim |
| Publisher | : Springer |
| Total Pages | : 594 |
| Release | : 2016-07-08 |
| Genre | : Technology & Engineering |
| ISBN | : 3319312936 |
This book covers all aspects of robot intelligence from perception at sensor level and reasoning at cognitive level to behavior planning at execution level for each low level segment of the machine. It also presents the technologies for cognitive reasoning, social interaction with humans, behavior generation, ability to cooperate with other robots, ambience awareness, and an artificial genome that can be passed on to other robots. These technologies are to materialize cognitive intelligence, social intelligence, behavioral intelligence, collective intelligence, ambient intelligence and genetic intelligence. The book aims at serving researchers and practitioners with a timely dissemination of the recent progress on robot intelligence technology and its applications, based on a collection of papers presented at the 4th International Conference on Robot Intelligence Technology and Applications (RiTA), held in Bucheon, Korea, December 14 - 16, 2015. For better readability, this edition has the total of 49 articles grouped into 3 chapters: Chapter I: Ambient, Behavioral, Cognitive, Collective, and Social Robot Intelligence, Chapter II: Computational Intelligence and Intelligent Design for Advanced Robotics, Chapter III: Applications of Robot Intelligence Technology .
| Author | : Richard Alami |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 483 |
| Release | : 2008-01-24 |
| Genre | : Technology & Engineering |
| ISBN | : 4431358730 |
DARS is now a well-established conference that gathers every two years the main researchers in Distributed Robotics systems. Even if the field is growing, it has been maintained a one-track conference in order to enforce effective exchanges between the main researchers in the field. It now a well-established tradition to publish the main contributions as a book from Springer. There are already 5 books entitled "Distributed Autonomous Robotic Systems" 1 to 5.
