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基于一种新型低成本便携式移动激光扫描系统的交通基础设施快速几何评估

Rapid Geometric Evaluation of Transportation Infrastructure Based on a Proposed Low-Cost Portable Mobile Laser Scanning System.

作者信息

Wang Haochen, Feng Dongming

机构信息

Key Laboratory of Concrete and Prestressed Concrete Structures of the Ministry of Education, Southeast University, Nanjing 210096, China.

School of Civil Engineering, Southeast University, Nanjing 210096, China.

出版信息

Sensors (Basel). 2024 Jan 10;24(2):425. doi: 10.3390/s24020425.

Abstract

Efficient geometric evaluation of roads and tunnels is crucial to traffic management, especially in post-disaster situations. This paper reports on a study of the geometric feature detection method based on multi-sensor mobile laser scanning (MLS) system data. A portable, low-cost system that can be mounted on vehicles and utilizes integrated laser scanning devices was developed. Coordinate systems and timestamps from numerous devices were merged to create 3D point clouds of objects being measured. Feature points reflecting the geometric information of measuring objects were retrieved based on changes in the point cloud's shape, which contributed to measuring the road width, vertical clearance, and tunnel cross section. Self-developed software was used to conduct the measuring procedure, and a real-time online visualized platform was designed to reconstruct 3D models of the measured objects, forming a 3D digital map carrying the obtained geometric information. Finally, a case study was carried out. The measurement results of several representative nodes are discussed here, verifying the robustness of the proposed system. In addition, the main sources of interference are also discussed.

摘要

道路和隧道的高效几何评估对交通管理至关重要,尤其是在灾后情况下。本文报道了一项基于多传感器移动激光扫描(MLS)系统数据的几何特征检测方法的研究。开发了一种可安装在车辆上并利用集成激光扫描设备的便携式低成本系统。合并来自众多设备的坐标系和时间戳,以创建被测物体的三维点云。基于点云形状的变化检索反映测量对象几何信息的特征点,这有助于测量道路宽度、净空高度和隧道横截面。使用自主开发的软件进行测量过程,并设计了一个实时在线可视化平台来重建被测物体的三维模型,形成一个承载所获几何信息的三维数字地图。最后进行了案例研究。这里讨论了几个代表性节点的测量结果,验证了所提系统的稳健性。此外,还讨论了主要干扰源

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8199/10821014/b1c7e9ebda8d/sensors-24-00425-g001.jpg

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