Development of an Autonomous Transportation Infrastructure Inspection System Based on Unmanned Aerial Vehicles
With transportation infrastructure in the United States aging and deteriorating, maintenance and inspection of the existing infrastructure become critical. Accurate and efficient inspections inform engineers/managers for better repair decisions/planning, load-rating, and effective management of limited resources. Current human-based infrastructure inspection may be costly, lack quantitative measures of damage, as well as pose a danger to inspectors. Thus, there is a need to develop more cost-effective, quantitative, and safe approaches for infrastructure inspection. In response to this need and recognizing the rapid technological improvement of UAV-based remote sensing, this project will explore the potential of UAV-based remote sensing technology in transportation infrastructure inspection with a focus on bridges. The ultimate goal of the study is to develop an autonomous and quantitative infrastructure inspection procedure that requires minimum human intervention. The three project objectives include: (1) Develop an automated process to identify different elements of a structure and establish an as-built element-wise building information model (BIM), (2) Develop an automated damage evaluation tool that can identify the type, location and amount of structural damage for each element; and (3) Develop a damage documentation tool that maps the identified element-wise damage to the corresponding bridge element in a BIM model.
Language
- English
Project
- Status: Active
- Funding: $116000
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Contract Numbers:
69A3551747108
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Sponsor Organizations:
Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC United States 20590 -
Managing Organizations:
North Dakota State University
Fargo, ND United States 58108 -
Project Managers:
Kline, Robin
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Performing Organizations:
Department of Civil and Environmental Engineering
Campus Delivery 1372
Fort Collins, CO United States 80523 -
Principal Investigators:
Guo, Yanlin
Atadero, Rebecca
van de Lindt, John
- Start Date: 20190226
- Expected Completion Date: 20220731
- Actual Completion Date: 0
- USDOT Program: University Transportation Centers Program
- Source Data: MPC-592
Subject/Index Terms
- TRT Terms: Bridges; Drones; Infrastructure; Inspection; Remote sensing
- Subject Areas: Bridges and other structures; Data and Information Technology; Highways; Maintenance and Preservation; Vehicles and Equipment;
Filing Info
- Accession Number: 01698546
- Record Type: Research project
- Source Agency: Mountain-Plains Consortium
- Contract Numbers: 69A3551747108
- Files: UTC, RiP
- Created Date: Mar 5 2019 2:08PM