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Multi-objective optimization of Stewart-Gough manipulator using global indices

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3 Author(s)
Lara-Molina, F.A. ; Mech. Eng. Sch., State Univ. of Campinas, Campinas, Brazil ; Rosario, J.M. ; Dumur, D.

The paper addresses the optimal design of parallel manipulators based on multi-objective optimization. The objective functions used are: Global Conditioning Index (GCI), Global Payload Index (GPI), and Global Gradient Index (GGI). These indices are evaluated over a required workspace which is contained in the complete workspace of the parallel manipulator. The objective functions are optimized simultaneously to improve dexterity over a required workspace, since single optimization of an objective function may not ensure an acceptable design. A Multi-Objective Evolution Algorithm (MOEA) based on the Control Elitist Non-dominated Sorting Genetic Algorithm (CENSGA) is used to find the Pareto front.

Published in:

Advanced Intelligent Mechatronics (AIM), 2011 IEEE/ASME International Conference on

Date of Conference:

3-7 July 2011