Intelligent Control of Robotic Systems 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: 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 examples in MATLAB under robot operating systems (ROS) for experimental validation so that readers can replicate these algorithms in robotics platforms.
The book uses MATLAB code throughout, and also uses the genetic algorithm solver (GA) from the Global Optimization Toolbox.