Inverse Kinematic Solutions Using Artificial Neural Networks

Abstract

Inverse Kinematics solutions are needed for control of robotic manipulators for successful task execution. It is the process of obtaining the required manipulator joint angle values for a given desired end point position and orientation. In general the process of obtaining these joint angle values is a complex process that may require some higher computational power in the hardware. Mainly there are three traditional methods used to solve inverse kinematics problem, namely; geometric methods, algebraic methods and iterative methods. Apart from these traditional techniques researchers have looked into the use of Artificial Neural Networks (ANNs). In this paper we re-visit these non-traditional techniques and compare the advantages and disadvantages of each method.