Low-Cost Uas Photogrammetry for Road Infrastructures’ Inspection

Abstract

Abstract. All over the world, road infrastructures are getting closer to their life cycle and need to be constantly inspected: a consistent number of bridges are structurally deficient, and the risk of collapse can no longer be excluded. In contrast with the past, the interest in structure durability has recently grown rapidly. In order to make bridges durable, it is necessary to carry out ordinary maintenance, preceded by inspection activities, which can be traditionally divided in two categories: destructive and non-destructive (NDT). All the NDT inspections (visual, IR thermography, GPR) can be conducted by using UAS (Unmanned Aerial Systems), a technology that makes bridges inspections quicker, cheaper, objective and repeatable. This study presents the visual inspection and survey of two bridges by using a UAS DJI Mavic 2 Pro, equipped with a 20Mpixel Hasselblad camera that records 60fps 4K video and a 10bit radiometric resolution. Starting from the acquired data, a 3D model of each structure was built by using Structure from Motion (SfM) principles and software. To validate the two models, each of them characterized by a centimetric accuracy, the UAS camera generated cloud of points and was co-registered with the point cloud of a terrestrial laser-scanner using Ground Control Points (GCPs). To make this, CloudCompare comparison software was used; the plugin M3C2 automatically calculates the distance between the points of two compared clouds. Finally, some general rules concerning the UAS main characteristics for inspection of bridges and software for data processing are proposed.

Quality Assessment of DJI Zenmuse L1 and P1 LiDAR and Photogrammetric Systems: Metric and Statistics Analysis with the Integration of Trimble SX10 Data

“…However, a small note should be made regarding the economic aspect. Despite the actual panorama of aerial payloads being characterised by low-budget instruments [20][21][22][23][24], the L1 and P1 are not low-cost solutions, even if some payload sensors for UAVs/UASs have seen reductions in their prices allowing for new possibilities and strategies in surveying. In fact, in some cases the sensors' price can be a real drawback for surveys and research, also determining the outcome of projects.…”

Uav Photogrammetry for Metric Evaluation of Concrete Bridge Cracks

“…For the latter case, a total station can be employed to derive GCPs world coordinates on hardly accessible bridges. Alternatively, a UAV-based photogrammetric model of the whole structure, with a sufficiently high image Ground Sample Distance (GSD), can be built with a traditional SfM workflow (Pinto et al, 2020). Distinctive features can be extracted from the photogrammetric model and used as GCPs.…”

“…Several example of usage of UAVs for crack investigation and metric reconstruction can be found in recent literature (Rau et al, 2017, Kim et al, 2017, Liu et al, 2019. Moreover, UAVs, combined with modern photogrammetry and Structure-from-Motion (SfM), allowed for building accurate 3D models, mesh models, orthophotos of observed infrastructure (Hackl et al, 2018, Pinto et al, 2020. Recently, Kim et al (2022) developed a compact and lightweight stereo-system, composed of one wide-angle lens and a telephoto lens, to accurately quantify cracks and with the aim of mounting it onboard UAVs for largescale infrastructure monitoring.…”

Integration of Uav-Lidar and Uav-Photogrammetry for Infrastructure Monitoring and Bridge Assessment

“…Fixed-angle cameras installed on the structure combined with 360-degrees optical devices mounted on moving vehicles on top of the bridge are affected by several limitations like visual obstructions (Chen et al, 2019). In recent years, Unmanned Aerial Vehicles (UAVs) have paved the way for low-cost non-destructive tests for bridge inspections and monitoring (Pinto et al, 2020). Innovative techniques represent valid alternatives compared to less safe and more expensive traditional methods, especially under extreme conditions (Belcore et al, 2021).…”