Kinematic Control of Redundant Robot Arms Using Neural Networks
Autor: | Shuai Li, Long Jin, Mohammed Aquil Mirza |
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EAN: | 9781119556992 |
eBook Format: | ePUB |
Sprache: | Englisch |
Produktart: | eBook |
Veröffentlichungsdatum: | 12.02.2019 |
Untertitel: | A Theoretical Study |
Kategorie: | |
Schlagworte: | <p>robotics; robot arm control; robot manipulator; mechatronics; Stewart platform; neural network; redundant manipulator; mobile manipulator; parallel manipulator; cable-driven manipulator; motor-actuated joints; kinematic control; robotic move |
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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.
SHUAI LI, PhD, is Assistant Professor in the Department of Computing at the Hong Kong Polytechnic University.
LONG JIN, PhD, is Postdoctoral Fellow in the Department of Computing at the Hong Kong Polytechnic University.
MOHAMMED AQUIL MIRZA, M.S., is a Doctorate Research Scholar with Hong Kong Polytechnic University.