Modeling and Analysis of the Stiffness Distribution of Host–Parasite Robots
Wei Wei, Ganwei Cai, Junjie Gong, Sixu Peng
- 发表年份
- 2021
- 引用次数
- 7
- 访问权限
- 开放获取
摘要
The stiffness distribution (SD) of robot has a great influence on the robot pose accuracy, but the calculation efficiency and accuracy of stiffness distribution are still low. This study presents a finite element fitting method with an extremely small number of computational cells. It was developed based on experimental results of robot stiffness. This method can be employed to establish single- and multi-source fitted SD (FSD) (S-FSD and M-FSD) models for host–parasite (H–P) robots. The computational efficiency and correctness of the FSD models were verified by case studies. The configurations of six evolutionary mechanisms of an H–P robot were subjected to an SD analysis. A comparison of the six configurations shows that adding parasitic branched chains can improve the SD of the H–P robot to varying degrees. In particular, the most notable improvement was for H–P mechanism. Specifically, by averaging the stiffness of all positions, the average-stiffnesses of H–P mechanism in the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$x$ </tex-math></inline-formula> -, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$y$ </tex-math></inline-formula> -, and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$z$ </tex-math></inline-formula> -directions were 104.10%, 1427.78%, and 1101.62% of those of the host mechanism, respectively. In the SD diagram, the medium- and high-stiffness regions of mechanism F are large and distributed in a banded pattern between the highest pose point and the furthest pose point, whereas its low-stiffness region is small and concentrated near the nearest pose point.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991