Potentialities of Optimal Design Methods for the Development of Mini Parallel Robots Using Genetic Algorithms

Abstract

This paper is aimed at presenting a study on the optimization of the Biglide and Bipod mini parallel robots, which comprises two-degree-of-freedom (DOF) mini parallel robots with constant and variable struts. The robot workspace is characterized and the inverse kinematics equation is obtained. In the paper, design optimization is implemented with Genetic Algorithms (GA) for optimization considering transmission quality index, design space and workspace. Here, intended to show the advantages of using the GA, we applied it to a multicriteria optimization problem of 2 DOF mini parallel robots. Genetic algorithms (GA) are so far generally the best and most robust kind of evolutionary algorithms. A GA has a number of advantages. It can quickly scan a vast solution set. Bad proposals do not affect the end solution negatively as they are simply discarded. It's also proposed an algorithm that is also useful when the aim is to find only a representative subset of all Pareto-optimal solutions.