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Implementation of Genetic Algorithms Optimization Method for the Optimal Design of Parallel Micro Robot

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4 Author(s)
Stan, S. ; Tech. Univ. of Cluj-Napoca, Cluj-Napoca ; Maties, V. ; Balan, R. ; Lapusan, C.

This paper is aimed at presenting a study on the optimization of the Biglide mini parallel robot, which comprises two-degree-of-freedom (DOF) mini parallel robots with constant 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 robot. 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 The obtained results have shown that the use of GA in such kind of optimization problem enhances the quality of the optimization outcome, providing a better and more realistic support for the decision maker.

Published in:

Computational Intelligence for Measurement Systems and Applications, 2007. CIMSA 2007. IEEE International Conference on

Date of Conference:

27-29 June 2007