Design optimization of a Delta-like parallel robot through global stiffness performance evaluation
Eric Courteille, Dominique Deblaise, Patrick Maurine
- 发表年份
- 2009
- 引用次数
- 64
摘要
This paper presents the design optimization of a Delta-like robot manipulator with respect to multiple global stiffness objectives. For this purpose, a systematic elasto-geometrical modeling method is used to derive the analytical manipulator stiffness models by taking into account their link and joint compliances. The models are then involved within a statistically sensitivity analysis of the influence of the geometric parameters on four global indices that describe the structure stiffness over the workspace. Multi-Objective Genetic Algorithm, i.e. Pareto-optimization, is taken as the appropriate framework for the definition and the solution of the addressed multi-objective optimization problem. Our approach is original in the sense that it is systematic and it can be applied to any serial and parallel manipulators for which stiffness is a critical issue.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002