Intelligent Control of Robotic Systems
1st Edition
Published on 7. April 2020
Book
Hardback
674 pages
978-1-138-59771-6 (ISBN)
Description
This book illustrates basic principles, along with the development of the advanced algorithms, to realize smart robotic systems. It speaks to strategies by which a robot (manipulators, mobile robot, quadrotor) can learn its own kinematics and dynamics from data. In this context, two major issues have been dealt with; namely, stability of the systems and experimental validations. Learning algorithms and techniques as covered in this book easily extend to other robotic systems as well. The book contains MATLAB- based examples and c-codes under robot operating systems (ROS) for experimental validation so that readers can replicate these algorithms in robotics platforms.
More details
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
Illustrations
702 s/w Abbildungen, 31 s/w Tabellen
31 Tables, black and white; 702 Illustrations, black and white
Dimensions
Height: 240 mm
Width: 161 mm
Thickness: 40 mm
Weight
1165 gr
ISBN-13
978-1-138-59771-6 (9781138597716)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Laxmidhar Behera | Swagat Kumar | Prem Kumar Patchaikani
Intelligent Control of Robotic Systems
E-Book
04/2020
1st Edition
CRC Press
€257.99
Available for download
Laxmidhar Behera | Swagat Kumar | Prem Kumar Patchaikani
Intelligent Control of Robotic Systems
E-Book
04/2020
1st Edition
CRC Press
€257.99
Available for download
Persons
Laxmidhar Behera, Swagat Kumar, Prem Kumar Patchaikani, Ranjith Ravindranathan Nair, Samrat Dutta
Content
1. Introduction Part 1: Manipulators 2. Kinematic and Dynamic Models of Robot Manipulators 3. Hand-eye Coordination of a Robotic Arm using KSOM Network 4. Model-based Visual Servoing of a 7 DOF Manipulator 5. Learning-Based Visual Servoing 6. Visual Servoing using an Adaptive Distributed Takagi-Sugeno (T-S) Fuzzy Model 7. Kinematic Control using Single Network Adaptive Critic 8. Dynamic Control using Single Network Adaptive Critic 9. Imitation Learning 10. Visual Perception 11. Vision-Based Grasping 12. Warehouse Automation: An Example Part 2: Mobile Robotics 13. Introduction to Mobile Robotics and Control 14. Multi-robot Formation 15. Event Triggered Multi-Robot Consensus 16. Human Tracking Algorithm using SURF Based Dynamic Object Model. Exercises. Bibliography. Index.