https://scholars.lib.ntu.edu.tw/handle/123456789/577236
Title: | Bridge Inspection with Aerial Robots: Automating the Entire Pipeline of Visual Data Capture, 3D Mapping, Defect Detection, Analysis, and Reporting | Authors: | JACOB JE-CHIAN LIN Ibrahim A Sarwade S Golparvar-Fard M. |
Keywords: | Antennas; Bridges; Highway bridges; Inspection; Robot applications; Robots; Three dimensional computer graphics; Automatic data collection; Bridge inspection; Defect detection; Elevated structures; Highway structures; Integrated systems; Three-dimensional (3D) model; Visual qualities; Data acquisition | Issue Date: | 2021 | Journal Volume: | 35 | Journal Issue: | 2 | Source: | Journal of Computing in Civil Engineering | Abstract: | The aging of bridges coupled with increased vehicular traffic requires timely and accurate inspections for elevated highway structures. Recent studies have leveraged the advent of drones and computer vision to automatically conduct quick, safe, and effective inspections for elevated highway structures. However, such studies rarely offer insight or recommendations for an end-to-end integrated system that streamlines data collection, analytics, and reporting. Toward this goal, we present an end-to-end robotic bridge inspection system consisting of five tightly coupled methods to: (1) create automatic data collection missions; (2) assure visual quality of such missions; (3) reconstruct three-dimensional (3D) models of elevated structures; (4) detect and localize surface distresses in 3D; and (5) generate reports complying with highway agencies' requirements. We validate each developed method and the whole system on two representative inspection projects. Results show that our system can objectively satisfy requirements for data collection and provide up to 85.3% average precision over five defect types. We finally share lessons learned while deploying our system to 30 bridge inspection projects in the US and Japan, particularly for documenting, communicating, and following-up with bridge inspectors' recommendations. ? 2020 American Society of Civil Engineers. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097364626&doi=10.1061%2f%28ASCE%29CP.1943-5487.0000954&partnerID=40&md5=2e39ad246adf27617a9c1068080973a5 https://scholars.lib.ntu.edu.tw/handle/123456789/577236 |
ISSN: | 8873801 | DOI: | 10.1061/(ASCE)CP.1943-5487.0000954 |
Appears in Collections: | 微生物學科所 |
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