Poster 20-10

[20-10] Development of Drone-Assisted Pavement Profile Mapping: Near-Surface Void Detection Application.

PI: Javier Irizarry

Co-PI(s): Tarek Rakha

Institution(s): Georgia Institute of Technology

Abstract

Near-surface voids can develop into potholes and spalling causing potential driving hazards. A UAS with dual camera sensors can efficiently collect infrared (IR) and visual (RGB) images. This research studied the application of Computer Vision and Deep Learning to analyze UAV-collected multi-spectrum images to detect areas with voids beneath pavement surfaces.

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