Optimal trajectory planning of a redundant manipulator using evolutionary programming

Abstract

A kinematically redundant robot manipulator has a lot of useful properties, such as avoiding singularities, obstacles and optimized motions, because the redundant manipulator has an infinite number of solutions of inverse kinematics. But, unfortunately it is very hard to get the solution of inverse kinematics when the manipulator is redundant. We propose two schemes which find the globally optimized solution of the redundant manipulator's inverse kinematics using evolutionary programming (EP). Evolutionary programming is a stochastic search method based on principles of evolution and heredity. The two schemes are mainly different in the chromosome representation method. The chromosome of the first scheme is composed of all joint angles while the chromosome of the second is composed of only redundant joint angles. To make a complete trajectory, interpolation is needed and the bound of interpolation error is calculated. We find the globally optimized trajectory of a 3-DOF RRR-type planar manipulator.