Optimization of a Three Degrees of Freedom DELTA Manipulator for Well-Conditioned Workspace with a Floating Point Genetic Algorithm

Vitor Gaspar Silva, Mahmoud Tavakoli and Lino Marques
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Vitor Gaspar Silva: Department of Electrical and Computer Engineering, University of Coimbra, Coimbra, Portugal
Mahmoud Tavakoli: Department of Electrical and Computer Engineering, University of Coimbra, Coimbra, Portugal
Lino Marques: Department of Electrical and Computer Engineering, University of Coimbra, Coimbra, Portugal

International Journal of Natural Computing Research (IJNCR), 2014, vol. 4, issue 4, 1-14

Abstract: This paper demonstrates dexterity optimization of a three degrees of freedom (3 DOF) Delta manipulator. The parallel manipulator consists of three identical chains and is able to move on all three translational axes. In order to optimize the manipulator in term of dexterity, a floating point Genetic Algorithm (GA) global search method was applied. This algorithm intends to maximize the Global Condition Index (GCI) of the manipulator over its workspace and to propose the best design parameters such as the length of the links which result in a higher GCI and thus a better dexterity.

Date: 2014
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