Workspace analysis of a parallel manipulator using multi-objective optimization and bio-inspired methods

Abstract

In robotic field, manipulators with parallel architecture have inherent advantages in relation to serial manipulators in various applications, such as high stiffness, accurate positioning and high movement velocities. In this context, the determination of volume position is one of the most important aspects considered during the manipulator project because it determines the geometrical limits of task that can be performed. In this contribution, Bio-inspired Optimization Methods (BiOM) are applied to solve a multi-objective problem that considers as objectives the maximization of volume position and the maximization of orientation workspace of CaPaMan (Cassino Parallel Manipulator). The strategy proposed consists in extension of the BiOM to problems with multiple objectives through the incorporation of two operators into the original algorithm: (i) the rank ordering, and (ii) the crowding distance. The results demonstrated that the proposed methodology represents an interesting approach to solve multi-objective problems in the robotic context.