We propose a novel subsurface pipeline mapping and 3D reconstruction method by fusing ground-penetrating radar (GPR) scans and camera images. To facilitate the simultaneous detection of multiple pipelines, we model the GPR sensing process and prove hyperbola response for general scanning with nonperpendicular angles. Furthermore, we fuse visual simultaneous localization and mapping outputs, encoder readings with GPR scans to classify hyperbolas into different pipeline groups. We extensively apply the J-linkage method and maximum likelihood estimation with error analysis to improve algorithm robustness and accuracy. As a result, we optimally estimate the radii and locations of all pipelines. We have implemented our method and tested it in physical experiments with representative pipeline configurations. Two different kinds of 3-m-long pipes are used, with radii being 4.62 and 3.02 cm, respectively. The results show that our method successfully reconstructs all subsurface pipes. Moreover, the average estimation errors for two orientation angles of pipelines are 1.73° and 0.73°, respectively. The average localization error is 4.47 cm. Note to Practitioners—Automatic and accurate underground pipeline mapping technology is very important in civil construction projects. Lack of 3D utility pipeline maps may lead to accidental damage in civil construction and maintenance. Although ground-penetrating radar (GPR-based pipeline mapping methods have been studied for several years, these methods require the perpendicular scanning with respect to the pipe, which is impossible to guarantee in practice since the orientations of pipelines are unknown. Furthermore, these traditional methods can only estimate one pipeline at a time in a survey area and require prior knowledge of pipe diameter. We propose a robotic subsurface pipeline mapping method with a GPR and a camera to handle difficult factors such as multiple pipes, unknown pipeline orientation, and unknown pipeline diameters. Hence, we can perform GPR scanning along any generic linear trajectories. Our method has been tested in physical experiments with representative pipeline configurations. The results are sufficiently accurate, and it proves that our method can be an effective technology to reconstruct the underground pipelines.

中文翻译：

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通过融合探地雷达和相机实现自动地下管道测绘


我们通过融合探地雷达 (GPR) 扫描和摄像机图像，提出了一种新颖的地下管道测绘和 3D 重建方法。为了便于同时检测多个管道，我们对探地雷达传感过程进行了建模，并证明了非垂直角度一般扫描的双曲线响应。此外，我们将视觉同步定位和映射输出、编码器读数与 GPR 扫描融合，将双曲线分类为不同的管道组。我们广泛应用 J-linkage 方法和带有误差分析的最大似然估计来提高算法的鲁棒性和准确性。因此，我们可以最佳地估计所有管道的半径和位置。我们已经实施了我们的方法，并在具有代表性的管道配置的物理实验中对其进行了测试。使用两种不同的3米长管道，半径分别为4.62和3.02厘米。结果表明，我们的方法成功重建了所有地下管道。此外，管道两个方位角的平均估计误差分别为1.73°和0.73°。平均定位误差为4.47 cm。从业者须知——自动、准确的地下管线测绘技术在土木建筑项目中非常重要。缺乏 3D 公用设施管道图可能会导致土建和维护中的意外损坏。虽然探地雷达（基于探地雷达的管道测绘方法）已经研究了好几年，但这些方法需要相对于管道进行垂直扫描，而由于管道的方向未知，这在实践中无法保证。 此外，这些传统方法一次只能估计勘测区域中的一根管道，并且需要事先了解管道直径。我们提出了一种带有探地雷达和摄像机的机器人地下管道测绘方法，以处理多个管道、未知管道方向和未知管道直径等困难因素。因此，我们可以沿着任何通用的线性轨迹进行探地雷达扫描。我们的方法已经在具有代表性的管道配置的物理实验中进行了测试。结果足够准确，证明我们的方法可以成为重建地下管道的有效技术。