三自由度DELTA机械臂良好条件工作空间的浮点遗传算法优化

V. G. Silva, M. Tavakoli, Lino Marques
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引用次数: 7

摘要

本文对三自由度Delta型机械臂的灵巧性优化进行了研究。并联机械手由三个相同的链条组成,并能在所有三个平移轴上移动。为了从灵巧度的角度对机械臂进行优化,采用浮点遗传算法(GA)进行全局搜索。该算法旨在最大化机械手在其工作空间上的全局条件指数(GCI),并提出最佳的设计参数,如连杆长度,从而获得更高的GCI,从而获得更好的灵巧性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimization of a Three Degrees of Freedom DELTA Manipulator for Well-Conditioned Workspace with a Floating Point Genetic Algorithm
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.
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