A systematic evaluation and selection of UAS-enabled solutions for bridge inspection practices

Abstract

Unmanned Aerial System (UAS)-enabled bridge inspection technique, as a promising alternative to conventional practices, has drawn more interest in recent years. However, UAS performance metrics requirements imposed by bridge structure (e.g., turbulent flow characteristics around the bridge) and terrain characteristics (e.g., surface roughness, temperature, and humidity), have made the selection of the suitable UAS platform a challenging problem. Currently, there is no verified and comprehensive methodology for UAS-enabled bridge inspection practices; existing case-dependent solutions rely on general-purpose commercially available UAS platforms. There is no study to quantify the gap between the performance metrics of the commercially available UAS platforms to those required for the bridge inspection. The objective of this paper is to initiate the development of a framework to systematically select a commercially available UAS that is the most appropriate choice for bridge inspection. An Analytic Hierarchy Process (AHP) methodology is adopted for the multiple-criteria decision making (MCDM) and comparing the capabilities of multiple UAS platforms. The AHP methodology is applied to 32 criteria defined under Four major categories including flight performance, situational awareness, payload and sensor capabilities, and communication quality. The developed method is illustrated and applied to a set of UAS platforms. A pairwise comparison approach is conducted in a hierarchical manner at the category level, criterion level, and candidate platform level. The results from comparison tables that meet the required AHP consistency ratio threshold, result in the selection of the most suitable UAS for bridge inspection in the defined scenario.