Genetic design of 3D modular manipulators

Abstract

This paper proposes a method for task based design of modular robotic systems using genetic algorithms (GA). We introduce a 3D kinematic description for modular serial manipulators and a two-level GA to optimize their topology from task specifications. Revolute and prismatic joints are considered and the number of DOF is let to the GA to determine (allowing redundant manipulators). The upper-level GA is dedicated to the topology evolution and uses the lower-level GA to search for inverse kinematics problem solutions. The topology is evolved for adaptation to a global task constituted by several required end effector configurations (subtasks). The implemented GA optimizes several performance criteria under constraints. To illustrate the method capacities, an example is presented for a redundant manipulator in a cluttered workspace.