Fusion of terrestrial and UAV-based point clouds for precision mapping and infrastructure inspection

融合地面和无人机点云，用于精确测绘和基础设施检查

• 批准号: 530963-2018
• 负责人: ElRabbany, Ahmed
• 金额: $ 1.82万
• 依托单位: Ryerson University
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=650129
• 关键词: Fusion; terrestrial; UAV; based; point

At present, either of the terrestrial laser scanners (TLS) or unmanned aerial vehicle (UAV)-based**LiDAR/camera systems are used for precision mapping and infrastructure inspection. Unfortunately, however,**both systems suffer from drawbacks, including the lower spatial resolution and complexity of sensor**integration of the UAV-based systems and the mobility and inability to scan dangerous-to-reach areas of TLS.**This research project aims to optimally fuse the point cloud data from both of the TLS and UAV-based**LiDAR/camera systems, which has the potential to overcome the drawbacks of either system alone.**The research will first select various sites representing different operational scenarios (e.g., bridges, dense**vegetation, buildings) for data collection with both of the FARO TLS and UAV-based systems. A number of**ground control points and targets will be established to enhance the image acquisition and accuracy of the point**cloud registration. As a low-cost digital camera will be used onboard the UAV, an accurate and efficient**camera calibration method for all possible operational scenarios will be developed, including the determination**interior orientation elements and distortion parameters. As well, LiDAR data will be corrected for both of the**geometric and radiometric effects. Trimble POSPac UAV software package will be used for post-processing of**the GNSS/MEMS IMU data and for geo-referencing of the imaging and LiDAR data. Pix4D and Autodesk**ReCap Pro software packages will be used to verify the image registration, along with MATLAB and**CloudCompare software. Both of the TLS and UAV-based point cloud data will finally be used to create a**complete 3D model of the scanned structure and surroundings.**The outcome of this research will significantly improve the efficiency of the field workflow, improve the**positioning accuracy, and enhance the inspection and risk assessment procedures of Canada's infrastructure.**This in turn helps making informed decision about infrastructure service and repair.

目前，地面激光扫描仪（TLS）或基于无人机（UAV）的**LiDAR/相机系统用于精确测绘和基础设施检查。然而不幸的是，**这两种系统都有缺点，包括空间分辨率较低和传感器复杂性**基于无人机的系统集成以及 TLS 的移动性和无法扫描危险到达区域的能力。**这项研究该项目旨在以最佳方式融合来自 TLS 和基于无人机的**LiDAR/相机系统的点云数据，这有可能单独克服任一系统的缺点。**该研究将首先选择代表不同操作的不同站点场景（例如，桥梁、茂密**植被、建筑物），用于使用 FARO TLS 和基于无人机的系统收集数据。将建立多个**地面控制点和目标，以提高图像采集和点云配准的准确性。由于无人机上将使用低成本数码相机，因此将开发一种适用于所有可能操作场景的准确、高效的**相机校准方法，包括确定**内部方向元素和畸变参数。此外，LiDAR 数据还将针对**几何和辐射效应进行校正。 Trimble POSPac UAV 软件包将用于 GNSS/MEMS IMU 数据的后处理以及成像和 LiDAR 数据的地理参考。 Pix4D 和 Autodesk**ReCap Pro 软件包以及 MATLAB 和 **CloudCompare 软件将用于验证图像配准。 TLS 和基于无人机的点云数据最终将用于创建**扫描结构和周围环境的完整 3D 模型。**这项研究的成果将显着提高现场工作流程的效率，提高* *定位准确性，并加强加拿大基础设施的检查和风险评估程序。**这反过来有助于就基础设施服务和维修做出明智的决策。