@article{gao_design_2010,
	title = {Design, analysis, and stiffness optimization of a three degree of freedom parallel manipulator},
	volume = {28},
	issn = {1469-8668, 0263-5747},
	url = {https://www.cambridge.org/core/journals/robotica/article/design-analysis-and-stiffness-optimization-of-a-three-degree-of-freedom-parallel-manipulator/A2E0BE8F9F42B30A65AA94FF4D5ABC07},
	doi = {10.1017/S0263574709005657},
	abstract = {SUMMARYThis paper proposed a novel three degree of freedom (DOF) parallel manipulator—two translations and one rotation. The mobility study and inverse kinematic analysis are conducted, and a CAD model is presented showing the design features. The optimization techniques based on artificial intelligence approaches are investigated to improve the system stiffness of the proposed 3-DOF parallel manipulator. Genetic algorithms and artificial neural networks are implemented as the intelligent optimization methods for the stiffness synthesis. The mean value and the standard deviation of the global stiffness distribution are proposed as the design indices. Both the single objective and multi-objective optimization issues are addressed. The effectiveness of this methodology is validated with Matlab.},
	number = {3},
	urldate = {2017-08-22TZ},
	journal = {Robotica},
	author = {Gao, Zhen and Zhang, Dan and Hu, Xiaolin and Ge, Yunjian},
	month = may,
	year = {2010},
	keywords = {Artificial intelligence approaches, Parallelogram structure, Stiffness optimization, degree of freedom, parallel manipulator},
	pages = {349--357}
}

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