MPC
Project Details

Title:	Development of Unmanned Aerial Vehicle (UAV) Bridge Inspection Procedures
Principal Investigators:	Yanlin Guo, Rebecca Atadero, and John W. van de Lindt
University:	Colorado State University
Status:	Completed
Year:	2017
Grant #:	69A3551747108 (FAST Act)
Project #:	MPC-535
RH Display ID:	15695
Keywords:	bridges, data collection, drones, feasibility analysis, guidelines, inspection, mathematical models, remote sensing

Abstract

This research is expected to provide the bridge management sectors (e.g. state DOTs) with a highly efficient, cost-effective, quantitative and safe proof-of-concept for bridge inspection. The ultimate goal of this research theme is to develop an automated and quantitative bridge inspection procedure that requires minimum human intervention. The automated procedure includes data (images) acquisition using the UAV, 3D reconstruction of surface models of bridges, identification, localization and quantification of structural damage and documentation of the geo-referenced bridge inspection data in database. This end goal will be achieved in two phases of studies. The first phase is the feasibility study, while the second phase is the development of machine learning tools to fully automate the data post-processing and damage identification process. This proposal will address the first phase of this research theme.

Project Deliverables

• [Final Report] A Streamlined Bridge Inspection Framework Utilizing Unmanned Aerial Vehicles — MPC-21-443
  • View Research Brief

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