Fuzzy enhanced advanced genetic algorithm for robot trajectory optimization

Abstract

This paper presents a novel general method for computing optimal motions of an industrial robot manipulator (7 dof seriel link robot). The optimization model considers the nonlinear manipulator dynamics, actuator constraints and joint limits. The problem has 2 objective functions, 147 variables and 42 constraints. Fuzzy enhanced advanced Genetic Algorithm namely Fuzzy Differential Evolution Algorithm (FuDE) has been used for the optimization. The trajectories are defined by cubic B-spline functions. The results obtained from FuDE are analyzed.