Unmanned aerial vehicle (UAV) research sponsored by the US Forest Service resulted in the first bridge inspection and a hyper-detailed three dimensional model for bridge inspections in the United States. This project resulted in an NSF Innovation Corps starting a small business with our research partner at George Mason University.
Unmanned aerial vehicles are now a viable option for augmenting bridge inspections. Utilizing an integrated combination of a UAV and computer vision can decrease costs, expedite inspections and facilitate bridge access. Any such inspection must consider the design of the UAV, the choice of cameras, data acquisition, geometrical resolution, safety regulations and pilot protocols.
The Placer River Trail Bridge in Alaska recently served as a test bed for a UAV inspection methodology that integrates these considerations. The end goal was to produce a three-dimensional (3D) model of the bridge using UAV captured images and a hierarchical Dense Structure-from-Motion algorithm. To maximize the quality of the model and its benefits to inspectors, this goal guided UAV design and mission planning.
The resulting inspection methodology integrates UAV design, data capture and data analysis together to provide an optimized 3D model. This model provides inspection documentation while enabling the monitoring of defects. The developed methodology is presented in the accompanying paper, as well as analyses of the 3D models.
The results are compared against models generated through laser scanning. The findings demonstrate that the UAV inspection methodology provided superior 3D models with the accuracy to resolve defects and support the needs of infrastructure managers.
Contact: SNAP Data Team
Project Status: Completed
- George Mason University
- United States Forest Service