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1.中国科学院 微电子研究所,北京 100029
2.中国科学院大学,北京 100049
3.南京航空航天大学 自动化学院,江苏 南京 211106
[ "高豆豆(1994-),女,河北衡水人,博士研究生,工程师,2016年、2019年于北京航空航天大学分别获得学士和硕士学位,主要从事精密测量及机器视觉的研究。E-mail: gaodoudou@ime.ac.c" ]
[ "董登峰(1981-),男,河南商丘人,博士,研究员,硕士生导师,2004年于郑州大学获得学士学位,2012年于北京航空航天大学获得博士学位,主要从事光学精密测量、AI识别方法、智能跟踪控制、视觉伺服控制系统等方面的研究。E-mail: dongdengfeng@ime.ac.cn" ]
纸质出版日期:2024-04-10,
收稿日期:2023-09-16,
修回日期:2023-10-10,
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高豆豆,董登峰,邱启帆等.面向激光跟踪测量的大范围高精度姿态测量[J].光学精密工程,2024,32(07):976-986.
GAO Doudou,DONG Dengfeng,QIU Qifan,et al.Large range automatic attitude measurement method for laser tracking measurement[J].Optics and Precision Engineering,2024,32(07):976-986.
高豆豆,董登峰,邱启帆等.面向激光跟踪测量的大范围高精度姿态测量[J].光学精密工程,2024,32(07):976-986. DOI: 10.37188/OPE.20243207.0976.
GAO Doudou,DONG Dengfeng,QIU Qifan,et al.Large range automatic attitude measurement method for laser tracking measurement[J].Optics and Precision Engineering,2024,32(07):976-986. DOI: 10.37188/OPE.20243207.0976.
针对我国高端制造业对高精度空间六自由度测量系统的迫切需求,提出一种面向激光跟踪测量的基于单目视觉的大范围全自动高精度姿态测量方法。阐述了面向激光跟踪测量的姿态测量系统构成、合作靶标硬件设计,并建立了姿态测量数学模型;其次,分析了自适应清晰成像的姿态测量模块特性,基于光学畸变模型与张正友标定法建立了实时相机成像模型,动态校正特征点像素坐标模型,提升了特征点的提取精度;之后,结合合作靶标几何特性、EPnP算法、SoftPOSIT算法提出一种改进的姿态测量方法,建立了姿态测量系统的自动监测纠错机制,实现测量范围内任意动态位姿的自动测量。最后,利用二维精密转台搭载合作靶标对激光跟踪测量的姿态测量系统进行精度测试。实验结果表明:在3~10 m,方位角/俯仰角为±30°、滚动角为±180°内,适配有14个特征点的合作靶标,姿态测量精度优于0.049°;适配有10个特征点的合作靶标,姿态测量精度优于0.065°。此方法普适性强,对合作靶标特征点布局约束较小,可以满足高端制造业激光跟踪测量的精密测量需求。
Considering the critical need for a high-precision
six-degree-of-freedom measurement system in China's advanced manufacturing sector
this study introduces a novel approach for large-scale
high-accuracy attitude measurement utilizing a monocular vision module for laser tracking. Initially
the paper outlines the hardware configuration of the laser tracking measurement system
encompassing both the attitude measurement system and the cooperative target
and establishes a mathematical model to define spatial attitude angles accurately. It then delves into the adaptive clear imaging features of the attitude measurement module. By leveraging an optical distortion model and Zhengyou Zhang's calibration algorithm
it crafts a real-time camera imaging model that dynamically adjusts the pixel coordinates of feature points
enhancing the precision of feature point extraction. This is further refined by integrating the geometric traits of the cooperative target with the EPnP and SoftPOSIT algorithms
leading to a sophisticated attitude measurement technique complemented by an automatic monitoring and error correction mechanism. This dual approach enables precise automatic measurement across any attitude within the specified distance and measurement range. The system's accuracy was validated through experiments using a two-dimensional precision turntable equipped with a cooperative target
showing an impressive attitude measurement accuracy within a 3-10 m range
with yaw and pitch angles within ±30° and roll angle within ±180°. Specifically
accuracy was better than 0.049° with a 14-feature-point cooperative target and better than 0.065° with a 10-feature-point target. These findings underscore the superiority of this method over other recent laser tracking measurement techniques
highlighting its broad applicability and minimal constraints on the cooperative target's feature point configuration
thus fulfilling the precision measurement demands of high-end manufacturing's laser tracking and measurement.
激光跟踪测量单目视觉自适应测量姿态测量
laser tracking measurementmonocular visionadaptive measurementattitude measurement
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