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ABSTRACT Drones are increasingly used during routine inspections of bridges to improve data consistency, work efficiency, inspector safety, and cost effectiveness. Most drones, however, are operated manually within a visual line of sight and thus unable to inspect long-span bridges that are not completely visible to operators. In this paper, aerial nondestructive evaluation (aNDE) will be envisioned for elevated structures such as bridges, buildings, dams, nuclear power plants, and tunnels. To enable aerial nondestructive testing (aNDT), a human-robot system will be created to integrate haptic sensing and dexterous manipulation into a drone or a structural crawler in augmented/virtual reality (AR/VR) for beyond-visual-line-of-sight (BVLOS) inspection of bridges. Some of the technical challenges and potential solutions associated with aNDT&E will be presented. Example applications of the advanced technologies will be demonstrated in simulated bridge decks with stipulated conditions. The developed human-robot system can transform current on-site inspection to future tele-inspection, minimizing impact to traffic passing over the bridges. The automated tele-inspection can save as much as 75% in time and 95% in cost. KEYWORDS: robotic platform, aerial nondestructive testing and evaluation, beyond-visual-line-of-sight inspection, augmented reality Introduction In the United States, currently there are more than 617 000 bridges in the National Bridge Inventory. According to the 2021 American Society of Civil Engineers (ASCE) Infrastructure Report Card, more than 42% of the bridges were at least 50 years old (the design life for most existing highway bridges), and 7.5% of the bridges were considered structurally deficient or in “poor” condition (ASCE 2021). These structurally deficient bridges supported 178 million trips every day, a potential safety concern. Overall, the bridges were rated C, with A being excel- lent and F being a complete failure. Other types of elevated infrastructure, such as dams, levees, transits, and school build- ings, are even worse in their existing conditions. The current practice of visual inspection is required bien- nially. Bridge inspection often requires the use of heavy lifting and access equipment, thus increasing operation time and direct costs. When access to the inspected area must be made from bridge decks, the indirect costs associated with road closure multiply. In such a case, both travelers and inspec- tors are subject to a safety concern on high-volume highways. Moreover, visual inspection is quite subjective and often inconsistent (Moore et al. 2001). It is only capable of detecting damage when it has advanced to become visually apparent. It is thus of economic, psychological, and social importance to develop an alternative platform for faster, safer, cheaper, and more consistent bridge inspection with minimum impact on traffic flow. In November 2012, a robot-assisted bridge inspection tool, referred to as RABIT, was developed as a product of the Federal Highway Administration (FHWA) Long-term Bridge Performance Program (LTBPP) and applied to survey bridge decks (Gucunski et al. 2013 La et al. 2013). The RABIT was equipped with six nondestructive evaluation (NDE) devices and cameras: (a) impact echo for delamination detection (b) ultrasonic surface wave for concrete quality evaluation (c) ground penetrating radar (GPR) for object mapping and deck deterioration assessment (d) electrical resistivity for concrete corrosive environment characterization and (e) two high-resolution, panoramic cameras for deck and surrounding area imaging. To extend autonomous inspection from deck elements to an entire bridge, the INSPIRE University Transportation Center (UTC) led by Missouri University of Science and Technology (Missouri S&T) has been developing advanced technolo- gies to aid in next-generation bridge inspection and mainte- nance. Once integrated, the overall system with the advanced AERIAL NONDESTRUCTIVE TESTING AND EVALUATION ( aNDT&E) GENDA CHEN*†, LIUJUN LI†, HAIBIN ZHANG†, ZHENHUA SHI†, AND BO SHANG† * Department of Civil, Architectural, and Environmental Engineering, Center for Intelligent Infrastructure, Missouri University of Science and Technology 1-573-341-4462 gchen@mst.edu † Department of Civil, Architectural, and Environmental Engineering, Center for Intelligent Infrastructure, Missouri University of Science and Technology Materials Evaluation 81 (1): 67–73 https://doi.org/10.32548/2023.me-04300 ©2023 American Society for Nondestructive Testing J A N U A R Y 2 0 2 3 • M AT E R I A L S E V A L U AT I O N 67 2301 ME Jan New.indd 67 12/20/22 8:15 AM