Parameter Identification of a Hybrid Redundant Robot by using Differential Evolution Algorithm

In this paper, a hybrid redundant robot IWR (Intersector Welding Robot) which possesses ten degrees of freedom (DOF) where 6-DOF in parallel and additional redundant 4-DOF in serial is proposed. To improve the accuracy of the robot, the kinematic errors caused by the manufacturing and assembly processes have to be compensated or limited to a minimum value. However, currently, there is no effective instrument which capable of measuring the symmetrical errors of the corresponding joints and link lengths after the structure has been assembled. Therefore, calibration and identification of these unknown parameters is utmost important and necessary to the systematic accuracy. This paper presents a calibration method for identifying the unknown parameters by using differential evolution (DE) algorithm, which has proven to be an efficient, effective and robust optimization method to solve the global optimization problems. The DE algorithm will guarantee the fast convergence and accurate solutions regardless of the initial conditions of the parameters. Based on the inverse kinematic error model of the robot, the simulation of the actual robot is achieved by introducing random geometric errors and measurement poses which representing their relative physical behavior. Moreover, through computer simulation, the validity and effectiveness of the DE algorithm for the parameter identification of the proposed application has also been examined.