Computational intelligence based approach for the joint trajectory generation of cooperative robotic systems

We discuss here the implementation aspects of recently developed tools of computational intelligence for tackling the issue of joint trajectory generation of a class of multi-joint cooperative robotic systems. This is closely related to the inverse kinematics problem which usually represents a heavy computational burden on the processing power of any complex robotic structure. High nonlinearities, heavy coupling between the degrees of freedom, and time variant configuration of the robot structure heavily contribute to these difficulties. Soft computing techniques have surged in recent years as effective computational tools for emulating the human capabilities when dealing with complex systems. Some of them are used here to synthesize approaches capable of substantially improving solving the inverse kinematics problem for a class of robotic systems and help generating the joint trajectories in a faster way