宇航计测技术 ›› 2024, Vol. 44 ›› Issue (6): 56-63.doi: 10.12060/j.issn.1000-7202.2024.06.06

• 量值传递技术 • 上一篇    下一篇

基于对象空间采样的三维激光投影校准方法

赵西富1,崔海华1,*,张益华1,王嘉瑞1,杨锋2,雷杨2   

  1. 1.南京航空航天大学机电学院,南京 210016;2.中航西安飞机工业集团股份有限公司,西安 710089
  • 出版日期:2024-12-15 发布日期:2025-01-21
  • 作者简介:赵西富(2000-),男,在读硕士研究生,主要研究方向:视觉辅助下的投影定位。
  • 基金资助:
    国家重点研发计划(2021YFB3401700);中央高校基本科研业务费专项资金资助(56XCA2403107)

Calibration Method of 3D Laser Projection Based on Object Spatial Sampling

ZHAO Xifu1,CUI Haihua1,*,ZHANG Yihua1,WANG Jiarui1,YANG Feng2,LEI Yang2   

  1. 1.College of Mechanical and Electrical Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China ;2.AVIC Xi’an Aircraft Industrial Corporation Co.,Ltd,Xi’an 710089,China
  • Online:2024-12-15 Published:2025-01-21

摘要: 为提高三维激光投影系统现场使用的灵活性和快速性,提出了一种基于对象空间采样的三维激光投影系统校准方法。该方法直接将待投影对象上的一点经过透视变换映射到单目相机的像素平面,再利用待投影对象空间采样所获取到的相机像素平面与振镜数字量平面之间的单应性矩阵,得到该点所对应的数字量控制信号。通过拍摄两张图像便可实现整个三维激光投影系统的校准。试验结果表明,利用该方法,投影系统校准时间小于5 min,在3 m范围内投影定位误差小于±0.4 mm,满足工业场景的应用需求。同时,该方法对于大型待投影对象中多台振镜的协同工作有重要意义。

关键词: 机器视觉, 透视变换, 平面单应性变换, 图像处理, 位姿估计

Abstract: In order to improve the flexibility and rapidity of 3D laser projection system,a calibration method of 3D laser projection system based on object spatial sampling is proposed.A point on the object to be projected is directly mapped to the pixel plane of the monocular camera through perspective transformation,and then the homography matrix between the camera pixel plane and the digital quantity plane of the galvanometer is used to obtain the corresponding digital quantity control signal of the point.The whole 3D laser projection system can be calibrated by taking two images.The experimental results show that the calibration time of the projection system calibrated by this method is less than 5 min,and the projection positioning error is less than ±0.4 mm in the range of 3 m,which meets the application requirements of industrial scenarios.Meanwhile,the method is meaningful for the cooperative work of multiple galvanometers in large objects to be projected.

Key words: Machine vision, Perspective transformation, Planar homography transformation, Image processing, Pose estimation

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