Competition-Based Neural Networks with Robotic Applications - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Competition-Based Neural Networks with Robotic Applications write by Shuai Li. This book was released on 2017-05-30. Competition-Based Neural Networks with Robotic Applications available in PDF, EPUB and Kindle. 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.
Dynamic Neural Networks for Robot Systems: Data-Driven and Model-Based Applications
Dynamic Neural Networks for Robot Systems: Data-Driven and Model-Based Applications - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Dynamic Neural Networks for Robot Systems: Data-Driven and Model-Based Applications write by Long Jin. This book was released on 2024-07-24. Dynamic Neural Networks for Robot Systems: Data-Driven and Model-Based Applications available in PDF, EPUB and Kindle. 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.
Neural Network Perception for Mobile Robot Guidance
Neural Network Perception for Mobile Robot Guidance - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Neural Network Perception for Mobile Robot Guidance write by Dean A. Pomerleau. This book was released on 2012-12-06. Neural Network Perception for Mobile Robot Guidance available in PDF, EPUB and Kindle. 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.
Kinematic Control of Redundant Robot Arms Using Neural Networks
Kinematic Control of Redundant Robot Arms Using Neural Networks - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Kinematic Control of Redundant Robot Arms Using Neural Networks write by Shuai Li. This book was released on 2019-02-11. Kinematic Control of Redundant Robot Arms Using Neural Networks available in PDF, EPUB and Kindle. 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.
Advances in Robots Trajectories Learning via Fast Neural Networks
Advances in Robots Trajectories Learning via Fast Neural Networks - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Advances in Robots Trajectories Learning via Fast Neural Networks write by Jose De Jesus Rubio. This book was released on 2021-05-14. Advances in Robots Trajectories Learning via Fast Neural Networks available in PDF, EPUB and Kindle.
