掘锚一体机将煤巷掘进和永久支护功能有效结合，大幅提升了掘进效率。目前大多数掘锚一体机钻锚作业的定位基本需要人工完成，存在定位精度和效率低等问题，严重影响掘锚一体机的智能化程度和巷道支护质量。本文针对煤矿巷道掘锚一体机定位难题，提出了掘锚一体机捷联惯导与双目视觉组合定位方法，旨在实现掘锚一体机的自动精准定位。

针对煤矿井下无BD和GPS、巷道空间受限且环境复杂、单一传感器定位难精度低等问题，综合分析了掘锚一体机定位需求与巷道特征，提出了捷联惯导与双目视觉组合的掘锚一体机定位方案。

针对煤矿井下照度低、粉尘高、环境复杂等因素严重影响双目视觉成像质量的问题，提出了一种双目视觉立体匹配视差图获取方法。分析了巷道坐标系-锚杆坐标系-相机坐标系的转换关系，建立了基于巷道特征的分布式锚杆多目标视差原理模型；结合双目立体校正技术对双目图像进行立体校正；基于Census变换算法，提出了改进的绝对像素差Census变换算法，有效提高了图像质量与匹配精度。

针对掘锚一体机在行驶过程中存在行驶位移检测精度低的问题，提出了掘锚一体机双目视觉机身行驶位移检测方法。研究了一种基于双目视觉的已支护锚杆特征点提取方法，获取锚杆视差图的感兴趣区域，采用Sobel算子检测锚杆轮廓；采用组合外接矩形算法，提取图像中的锚杆特征点；建立双目视觉行驶位移检测模型求解掘锚一体机的行驶位移，实现了掘锚一体机行驶位移的精确测量。

针对“惯导+双目视觉”掘锚一体机精准定位信息融合难题，建立了“惯导+双目视觉”的掘锚一体机位姿测量模型，提出了基于误差状态卡尔曼滤波的“惯导+双目视觉”数据融合算法以及掘锚一体机精确定位方法。仿真实验结果表明，该方法能够实现掘锚一体机精准定位。

最后，搭建了“惯导+双目视觉”的掘锚一体机组合定位实验平台，验证“惯导+双目视觉”组合定位方法的有效性与可行性。实验结果表明：本文所研究的组合定位方法能够有效修正单一惯导产生的位姿累积误差，具有较高的定位精度，能够满足煤矿巷道掘锚一体机定位要求。

The digging and anchor integrated machine effectively combines the functions of coal mine roadway driving and permanent support, greatly improving the driving efficiency. At present, most of the positioning of the anchor drilling operation of the digging and anchor integrated machine requires manual completion, which has problems such as low positioning accuracy and low positioning efficiency, seriously affecting the intelligence level of the digging and anchor integrated machine and the quality of roadway support. In this thesis, aiming at the positioning problem of the driving and anchoring machine in coal mine roadway, a combined positioning method of strapdown inertial navigation and binocular vision is proposed to realize the automatic and accurate positioning of the driving and anchoring machine.

Aiming at the problems of coal mines without BD and GPS, limited coal mine roadway space and complex environment, and low positioning accuracy with a single sensor, a comprehensive analysis was conducted on the positioning requirements and coal mine roadway characteristics of the digging and anchor integrated machine, a positioning scheme for the digging and anchor integrated machine combining strapdown inertial navigation and binocular vision is proposed.

Aiming at the serious impact of factors such as low illumination, high dust, and complex environment in coal mine roadway on the quality of binocular visual imaging, a positioning method of binocular stereo matching disparity map acquisition method is proposed. Analyzed the transformation relationship between the coal mine roadway coordinate system, anchor rod coordinate system, and camera coordinate system, and established a distributed anchor rod multi-objective parallax principle model based on coal mine roadway features; Combining binocular stereo correction technology to perform stereo correction on binocular images; Based on the Census transform algorithm, an improved absolute pixel difference Census transform algorithm is proposed, which effectively improves image quality and matching accuracy.

Aiming at the problem of low detection accuracy of travel displacement during the driving process of the digging and anchor integrated machine, a positioning method of binocular vision method for detecting the travel displacement of the digging and anchor integrated machine is proposed. A feature point extraction method for supported anchor rods based on binocular vision was studied to obtain the region of interest of the anchor rod disparity map, using the Sobel operator to detect the contour of the anchor rods; Using the combined bounding rectangle algorithm to extract anchor feature points in the image; Establish a binocular vision driving displacement detection model to solve the driving displacement of the anchor excavator, and achieve accurate measurement of the driving displacement of the anchor excavator.

Aiming at the problem of precise positioning information fusion for the "inertial navigation+binocular vision" digging and anchor integrated machine, establish a pose measurement model for the "inertial navigation+binocular vision" anchor and digging integrated machine. A positioning method of data fusion algorithm based on error state Kalman filtering for the "inertial navigation+binocular vision" and a precise positioning method for the digging and anchor integrated machine is proposed. The simulation experimental results show that this method can achieve precise positioning of the digging and anchor integrated machine.

Finally, building the combined positioning experimental platform of "inertial navigation+binocular vision" for the digging and anchor integrated machine, and verifying the effectiveness and feasibility of the combined positioning method. The experimental results show that the combined positioning method can effectively correct the cumulative error of a single inertial navigation system, it has high positioning accuracy and can meet the positioning requirements of the coal mine roadway excavation anchor integrated machine.

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