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Processing of mobile laser scanning data for large‐scale deformation monitoring of anchored retaining structures along highways

Slaven Kalenjuk, Werner Lienhart, Matthias Rebhan

2021Computer-Aided Civil and Infrastructure Engineering40 citationsDOIOpen Access PDF

Abstract

In times of steadily increasing traffic loads and extreme weather phenomena, the safe maintenance of infrastructure poses a difficult challenge to operators, especially when a vast number of aged structures exists and fundamental data is missing. This paper addresses the demand for cost-efficient deformation monitoring of anchored retaining structures along public roads. The principal idea is to process laser scans of a motor-vehicle-based mobile mapping system with a high degree of automation. Starting with scene interpretation, our processing pipeline extracts the retaining wall from the rest of the point cloud, segments the anchored elements, and computes their deformations. This method requires, however, correcting for positioning errors to obtain accurate results. We exploit the high data redundancy of road patches and line markings for alignment. Due to the high degree of automation, computations scale to large numbers of point clouds and run in a repeatable manner. Even when traveling along highways with up to 100 km/h, we achieve repeatable accuracies for tilting and lateral displacements that compare to traditional, labor-intense surveying methods.

Topics & Concepts

Redundancy (engineering)Point cloudAutomationExploitComputer scienceComputationLaser scanningData redundancyData processingPipeline (software)Real-time computingCloud computingComputer visionEngineeringLaserMechanical engineeringAlgorithmComputer securityDatabasePhysicsOpticsProgramming languageOperating system3D Surveying and Cultural HeritageRemote Sensing and LiDAR ApplicationsInfrastructure Maintenance and Monitoring
Processing of mobile laser scanning data for large‐scale deformation monitoring of anchored retaining structures along highways | Litcius