Large gear structure assembly method based on uncalibrated image visual servo guidance

被引:0
|
作者
Kong, Shengjie [1 ]
Huang, Xiang [1 ]
机构
[1] Nanjing Univ Aeronaut & Astronaut, Coll Mech & Elect Engn, Nanjing 210016, Peoples R China
来源
REVIEW OF SCIENTIFIC INSTRUMENTS | 2023年 / 94卷 / 12期
关键词
EXTREME LEARNING-MACHINE; COAXIAL ALIGNMENT METHOD; SYSTEM;
D O I
10.1063/5.0177035
中图分类号
TH7 [仪器、仪表];
学科分类号
0804 ; 080401 ; 081102 ;
摘要
The reliability of the transmission system hinges significantly on the assembly quality of its main component, the large gear structures. However, the traditional approach of employing manual lifting presents a host of challenges, such as high assembly complexity and lowered efficiency, rendering the overall assembly process notably arduous. In this study, a large gear structure assembly method based on uncalibrated image visual servo guidance is proposed. Comprising three modules, the approach involves constructing a task function for projective homography, estimating the image Jacobian matrix, and designing an adaptive servo controller. This methodology facilitates the mapping of changes in gear images to the motion of the end-effector in the parallel mechanism. Consequently, the system dynamically guides the end-effector to achieve the required attitude adjustments in the gear assembly in response to changes in the image features. Experimental results demonstrate that the method proposed surpasses alternative approaches, simultaneously exhibiting a significant enhancement in assembly efficiency. The method has a wide application prospect in the field of automated assembly of large gear structures.
引用
收藏
页数:13
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