Inverse kinematics solution of a five joint robot using feed forward and Radial Basis Function Neural Network

Abstract

Robotics provides new innovations to the industrial revolution and the more recent information revolution. Inverse kinematics computation is one of the main problems in robotics research and its complexity increases by rising the degrees of freedom the manipulator. The inverse kinematics problem for a robotic manipulator is obtained for the required manipulator joint values for a given desired end point position and orientation. The Artificial Neural Network is an algorithm which works similarly as the biological neuron. In this paper the Neural Network ideas such as feed forward and Radial Basis Functions algorithms are proposed to solve the inverse kinematics problem of five degree of freedom robot end effector.