Genetic-based fuzzy model for inverse kinematics solution of robotic manipulators

Abstract

A genetic-based method for the generation and adjustment of membership functions of fuzzy Jacobian sets for inverse kinematics solution of robotic manipulators is presented. The method produces an optimal membership function arrangement for the fuzzy Jacobian set. A simulation environment is developed which enables one to apply different parameters for flexible application of operators in the genetic algorithm during the process. Comparison results of the proposed approach and the available technique show that this method provides better results than the available one.