Intelligent Control of Robotic Systems

Inbunden, Engelska, 2020

AvLaxmidhar Behera,Swagat Kumar,Prem Kumar Patchaikani,Ranjith Ravindranathan Nair,Samrat Dutta,INDIA) Behera, Laxmidhar (Department of Electrical Engineering, Indian Institute of Technology, Kanpur,INDIA) Kumar, Swagat (TATA Consultancy Services, New Delhi,India) Patchaikani, Prem Kumar (General Electric, Bengaluru,India) Nair, Ranjith Ravindranathan (Department of Electronics & Communication Engineering, IIIT, Pune,India) Dutta, Samrat (TCS innovations Labs, Bangalore

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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.

Produktinformation

Utgivningsdatum2020-04-07
Mått156 x 234 x 40 mm
Vikt1 410 g
FormatInbunden
SpråkEngelska
Antal sidor674
FörlagTaylor & Francis Ltd
ISBN9781138597716

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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.

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