Automatic calibration method for station transfer in tunneling equipment positioning system based on binocular vision

doi:10.3785/j.issn.1006-754X.2025.04.111

Chinese Journal of Engineering Design

2025, Vol. 32

Issue (1): 1-10 DOI: 10.3785/j.issn.1006-754X.2025.04.111

Theory and Method of Mechanical Design

Automatic calibration method for station transfer in tunneling equipment positioning system based on binocular vision

Xuhui ZHANG^1,²(

),Junhao YANG¹,Wenjuan YANG^1,²,Chao ZHANG¹,Xin CHEN¹,Jicheng WAN¹,Yanhui LIU¹,Yue WANG¹

^1.College of Mechanical Engineering, Xi'an University of Science and Technology, Xi'an 710054, China
^2.Shaanxi Key Laboratory of Intelligent Detection and Control for Mining Electromechanical Equipment, Xi'an 710054, China

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Abstract

Stable and continuous visual posture measurement data is of great significance for improving the work efficiency of coal-mine tunneling equipment. Currently, posture measurement methods for tunneling equipment based on visual information face issues such as cumbersome calibration process of cooperative target during station transfer and inability to perform automatic continuous measurements. Aiming at this problem, an automatic calibration method for station transfer based on binocular vision is proposed. Firstly, the HSV (hue, saturation, value) color segmentation and point-line feature extraction technology were employed to process the red features of the cooperative target, so as to obtain the image information of the cooperative target. Then, a calibration solution model for station transfer was designed, and the binocular vision measurement method was used to obtain the spatial parameters of the cooperative target. Finally, based on the characteristic that the relative position between the camera and the cooperative target was unchanged during the calibration process, the L-M (Levenberg-Marquardt) algorithm was used to optimize the spatial parameters of the cooperative target, and the optimization results were applied to the visual positioning system to complete the calibration for station transfer. The experimental results showed that the position measurement error of the tunneling equipment body after the calibration for station transfer was within 50 mm, and the attitude angle measurement error was within 0.6°. The proposed automatic calibration method for station transfer based on binocular vision meets the accuracy requirements of the visual positioning system for coal-mine tunneling equipment, which can provide theoretical support for the research of rapid tunneling technology.

Key words： visual measurement automatic calibration cooperation target feature extraction solution model

Received: 19 February 2024 Published: 04 March 2025

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	Xuhui ZHANG
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	Chao ZHANG
	Xin CHEN
	Jicheng WAN
	Yanhui LIU
	Yue WANG

Cite this article:

Xuhui ZHANG,Junhao YANG,Wenjuan YANG,Chao ZHANG,Xin CHEN,Jicheng WAN,Yanhui LIU,Yue WANG. Automatic calibration method for station transfer in tunneling equipment positioning system based on binocular vision. Chinese Journal of Engineering Design, 2025, 32(1): 1-10.

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https://www.zjujournals.com/gcsjxb/10.3785/j.issn.1006-754X.2025.04.111 OR https://www.zjujournals.com/gcsjxb/Y2025/V32/I1/1

基于双目视觉的掘进装备定位系统移站自主标定方法

稳定、连续的视觉位姿测量数据对提高煤矿掘进装备的工作效率具有重要意义。目前，基于视觉信息的掘进装备位姿测量方法存在合作标靶移站后标定过程烦琐、无法自动连续测量的问题。针对这一难题，提出了一种基于双目视觉的移站自主标定方法。首先，采用HSV（hue, saturation, value，色调、饱和度、明度）颜色分割和点线特征提取技术，针对合作标靶的红色特征进行处理，以获取合作标靶图像信息。然后，设计移站标定解算模型，利用双目视觉测量方法获取合作标靶的空间参数。最后，根据标定过程中相机与合作标靶的相对位置不变的特点，利用L-M（Levenberg-Marquardt）算法优化合作标靶的空间参数，并将优化结果应用于视觉定位系统，以完成移站标定。实验结果表明：移站标定后掘进装备机身的位置测量误差均在50 mm以内，姿态角测量误差均在0.6°以内。所提出的基于双目视觉的移站自主标定方法满足煤矿掘进装备视觉定位系统的精度要求，可为快速掘进技术的研究提供理论支持。

关键词： 视觉测量, 自主标定, 合作标靶, 特征提取, 解算模型

Fig.1 Schematic of station transfer process of visual positioning system for tunneling equipment

Fig.2 Automatic calibration principle for station transfer in visual positioning system of tunneling equipment

Fig.3 Automatic calibration flow for station transfer in visual positioning system of tunneling equipment

Fig.4 Point and line feature extraction process of cooperative target image

Fig.5 Preprocessing process of cooperative target image

Fig.6 Laser spot center extraction result

Fig.7 Laser beam center line extraction result

Fig.8 Schematic diagram of laser spot and laser beam projection

Fig.9 Solution model of space direction vector of laser beam center line

Fig.10 L-M algorithm flow

Fig.11 Automatic calibration experiment platform for station transfer in visual positioning system of tunneling equipment

Fig.12 Calibration experimental results for station transfer

Table 1 Partial posture measurement data of tunneling equipment body

Fig.13 Posture measurement error of tunneling equipment body


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