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，陆地激光扫描仪（TLS）或无人机（UAV）基于**的**激光镜/相机系统用于精确映射和基础架构检查。然而，不幸的是，**这两个系统都有缺点，包括传感器的空间分辨率和复杂性**基于无人机的系统的整合以及动机性和无法扫描TLS的危险区域。代表不同的操作场景（例如，桥梁，密集的**植被，建筑物）的各种站点，用于数据收集，以及FARO TLS和基于无人机的系统。将建立许多**地面控制点和目标，以增强点**云注册的图像采集和准确性。由于将在无人机上使用低成本数码相机，因此将开发出一种准确有效的**摄像头校准方法，用于所有可能的操作场景，包括确定**内部方向元素和失真参数。同样，**几何和辐射效应都将校正LiDAR数据。 Trimble POSPAC无人机软件包将用于** GNSS/MEMS IMU数据的后处理以及成像和激光雷达数据的地理参考。 PIX4D和AUTODESK ** RECAP PRO软件包将与MATLAB和** CloudCompare软件一起验证图像注册。最终将使用基于TLS和UAV的点云数据来创建一个完整的3D结构和周围环境的3D模型。