SCAPSO-based Inverse Kinematics Method and Its Application to Industrial Robotic Manipulator

Abstract

This paper proposes a sine-cosine particle swarm optimization algorithm (SCAPSO) to solve the inverse kinematics of robotic manipulator. Based on a Sine and Cosine function, a random perturbation is added to the classical particle swarm algorithm (PSO) to prevent premature convergence and falling into the local minima. After a certain number of iterations, several random solutions generated based on the sine and cosine function assist the algorithm to jump out of the local optimal solution if the fitness function value is not updated. The Sine Cosine algorithm(SCA) is capable of creating a balance between exploitation and exploration. The numerical experiments are obtained in MATLAB for the 6-DOF manipulator, and show that the algorithm is an effective method due to strong global search ability, faster convergence and high effectiveness.