Genetic algorithm based redundancy resolution of robot manipulators

Abstract

This paper presents a genetic algorithm based approach to redundancy resolution of robot manipulators using self-motion topology knowledge. The genetic algorithm presented can work under joint limits and produces end-effector positions with negligible error. Any solution determined by the genetic algorithm is physically realizable, as demonstrated on a PUMA 700 robot manipulator which is configured as a redundant positional manipulator.