第26卷第7期 2018年7月
文章编号1004-924X(2018)07-1794-08
光学精密工程
Optics and Precision Engineering
Vol.26No.7
Jul.2018
基干3-CCD显微视觉的高精度靶位姿控制
宋薇*，宋志杰，章亚男，沈林勇
（上海大学机电工程与自动化学院，上海200072）
摘要：针对高功率激光物理装置中的靶自动准直实验平台，提出了一种基于三路显微视觉的高精度靶位姿控制方法。该方法采用基于图像的显微视觉控制策略，通过对送靶机构的主动运动控制，实现了图像雅可比矩阵的在线自标定；利用增量式PI控制方法对送靶机构进行控制，实现靶的快速定位及姿态调整。本文对比了基于图像的显微视觉控制和之前研究中所提出的基于位置的显微视觉控制两种方法。其中，基于图像的控制方法靶的定位误差为0.07um，姿态调整误差为0.02urad；而基于位置的控制方法靶的定位误差为0.16um，姿态调整误差为0.07urad。实验结果表明：基于图像的显微视觉控制方法对系统中的运动学误差、视觉标定误差等因素具有较好的鲁棒性，靶定位及姿态调整的精度高且稳定性好。
关键词：靶定位；姿态调整；图像雅克比矩阵；基于图像的视觉控制；显微视觉
中图分类号：TN248
文献标识码：Adoi:10.3788/0PE.20182607.1794
High-precision target pose adjustment based on
3-CCD microscope vision system
SONG Wei',SONG Zhi-jie,ZHANGYa-nan,SHEN Lin-yong
(School of MechatronicEngineering and Automation ShanghaiUniversity，Shanghai200072，China)*Corresponding author,E-mail:song_we@shu.edu.cn
Abstract : A 3-CCD microscope vision system is established to realize micro-target pose adjustment in a high-power laser device with high precision . Image-based visual control method is performed , and the image Jacobian matrix is derived online by using the active movement of the micro-target. The PI controller is used to adjust the micro-target's pose so that the image features are close to the objective position. In the experiments , we compare the image-based visual control method with the position based visual control method, which was proposed in our previous research by using a 3D posture description algorithm to control the micro-target to the desired pose. The precision of target positioning and orientation error for the image-based visual control method are O.07 μm and O.O2 qμrad, respectively , whereas the precision of target positioning and orientation error values for the position-based visual control method are O.16 μm and 0.07 μrad, respectively . The experimental results show that the image-based visual control method is robust for system errors such as kinematic and visual calibration errors . Thus, it possesses better precision and stability for target pose adjustment
收稿日期：2017-11-20；修订日期：2018-01-23.
基金项目：国家自然科学基金资助项目（No.61105029）