Circularly coded targets are widely used in 3D measurement, target tracking, augmented reality, and other fields as feature points to be measured. The traditional coded target recognition algorithm is easily affected by illumination changes and excessive shooting angles, and the recognition accuracy is significantly reduced. Therefore, a new coded target recognition algorithm is required to reduce the effects of illumination and angle on the recognition process. The influence of illumination on the recognition of coding targets was analyzed in depth, and the advantages and disadvantages of traditional algorithms are discussed. A new adaptive threshold image segmentation method was designed, which, in contrast to traditional algorithms, incorporates the feature information of coding targets in the determination of the image segmentation threshold. The experimental results show that this method significantly reduces the influence of illumination variations and cluttered backgrounds on image segmentation. Similarly, the influence of different angles on the recognition process of coding targets was studied. The coding target is decoded by radial sampling of the dense point network, which can effectively reduce the influence of angle on the recognition process and improve the recognition accuracy of coding targets and the robustness of the algorithm. In addition, further experiments verified that the proposed detection and recognition algorithm can better extract and identify with high positioning accuracy and decoding success rate. It can achieve accurate positioning even in complex environments and meet the needs of industrial measurements.
KEYWORDS: Receivers, 3D scanning, 3D metrology, Aluminium phosphide, Laser systems engineering, 3D modeling, Photodetectors, Optical engineering, Laser soldering, 3D tracking
Aiming at the problem of constraints between reconstruction range and splicing accuracy when 3D reconstruction is carried out on large-scale equipment in aerospace and other fields, we investigate the combined 3D scanning measurement method based on the guidance of the all-space laser positioning system (ALPS) on the basis of analyzing the fusion of the ALPS and scanning target. The method establishes a global 3D scanning measurement model based on multiple measurement points by Creo and simulates and analyzes the data with MATLAB, then designs the structure of the circumferential combined photoelectric receiver by combining with the receiving characteristics of photodetectors for laser signals in the full-space field, and then completes the optimal layout design of the receiver based on the accessibility. Finally, a 30 m×30 m experimental platform for the fusion of ALPS and scanning target is constructed, and the measured standard bat and Zeiss standard ball are used as the measured objects to verify the feasibility of the research method. The simulation and experimental results show that the optimal number of receivers needed for the global measurement system is N=6, the measurement accuracy is better than 0.5 mm, and the repeatability measurement accuracy is up to 0.02 mm, which provides a basis for the 3D scanning of large-scale equipment.
Accurate laser positioning system (ALPS) is widely used in large space indoor dynamic positioning. To improve the positioning accuracy and refresh frequency, the inertial measurement unit (IMU) with a high frame rate is used for fusion, so it is necessary to calibrate the external parameters of ALPS and IMU. Based on the analysis of the calculation process and error description of traditional calibration, we propose a calibration method of spatial multipose transformation (SMT). In this calibration method, the target plate performs multiple attitude transformations to obtain the attitude data and process its error. Then, the Lodrigues matrix is introduced in the solution process to reduce the dimension of unknown variables in the equation, and it is optimized combined with SVD decomposition. At the same time, to further adapt to the application of fusion, a more intuitive error description method is proposed to evaluate the influence of calibration results on fusion accuracy. The simulation experiments indicate that the proposed method enables the calibration error to have accuracy within 0.02 mm. Furthermore, the results of the validation experiments show that the proposed calibration solution method improves in accuracy and robustness with respect to the conventional method. It provides a technical basis for realizing higher precision indoor dynamic positioning applications in large space.
An accurate large-scale positioning system is a high-precision distributed large-scale dimensional metrology system that is widely used in smart manufacturing and assembly applications. The system comprises multiple transmitters with locations and orientations that are typically calibrated based on auxiliary measurement equipment. However, the calibration method is complicated and time consuming. We propose a rapid and flexible calibration method based on the highly precise three-dimensional coordinate control network established by a calibration bar with an accuracy of ± 0.005 mm, including both estimation and optimization algorithms. Exploratory experiments were performed to validate the feasibility of the proposed calibration method. The results demonstrate that the proposed calibration method enables the repeated measurement errors to be maintained at <0.05 mm in X and Y and <0.04 mm in Z. The standard deviation after calibration was 0.18 mm in comparison with the laser tracker.
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