Total system error analysis of UAV-CRP technology for monitoring transportation infrastructure assets

Abstract

Infrastructure forms the backbone of a nation's economy, and there is a growing demand for a technology that offers quick, safe, and reliable infrastructure performance monitoring data, which would lead to proactive maintenance or repairs of the infrastructure to ensure its quality performance as per the original design. The increase in the applications of unmanned aerial vehicles (UAVs) or drones for such monitoring purposes have been propelled by advancements in aerial vehicle platforms and image-analyses software. Evaluating UAVs for high-quality infrastructure-distress data monitoring has been a major focus for this research. Photogrammetry is the science of measuring distances from two or multiple images of an object and close range photogrammetry (CRP) can be accomplished by using an optical camera mounted on a UAV platform and taking the images of the infrastructure object. This technology, hereafter termed as UAV-CRP technology, utilizes UAVs coupled with high quality camera lens and a global navigation satellite system (GNSS) device to collect high quality data with fewer ground control points (GCPs). The various pieces of equipment need to have their aerial technology compatibility tested in different environmental conditions and evaluate the imagery that is used for image analyses and interpretations. A comprehensive set of calibration checks were executed using the total system comprising of UAV and accessories to evaluate the imagery quality level of transportation and geotechnical infrastructure data. All the checks performed ensured that the data obtained from the UAV-CRP technology meets the quality requirements for infrastructure data. A case study of pavement infrastructure data was provided to validate the high accuracy UAV-CRP data obtained following the guidelines developed in this paper.