Forward Kinematics Based on Improved Genetic Algorithms of 6-DOF Parallel Robot

Abstract

The problem of forward kinematics is treated as optimization of multi-variable nonlinear equation group in this paper. Improved genetic algorithms are used to obtain optimum values, and a new grouping method is presented based on gray relative analysis. Seven groups of real values of the 6-DOF Stewart parallel platform are provided as examples. It is proved that the proposed method is simple, effective and useful in solving forward kinematics problems for parallel robots.