The use of unmanned ground vehicles (mobile robots) and unmanned aerial vehicles (drones) in the civil infrastructure asset management sector: Applications, robotic platforms, sensors, and algorithms

The increasing computational power of machines and more affordable robotic hardware and software offer great opportunities for developing more advanced intelligent robotic systems to perform numerous tasks in the civil infrastructure sector (CIS). More specifically, unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) are the most commonly used robots for civil infrastructure-related applications. Existing synthesized information on the applications of UAVs and UGVs mainly focused on either a specifically narrow domain or broadly summarized the current practices of robots in the CIS without providing sufficient information about the relevant sensing devices and/or data processing techniques. Therefore, there is a need to widely review, synthesize, and analyze the applications of UAVs and UGVs as well as the associated methods (e.g., data sensing techniques and data analytic methods) in the broad CIS field. To this end, this paper provides a systematic review of UAVs-and UGVs-related studies conducted in the CIS in relation to their applications, the used robotic platforms, the employed sensors, and the implemented algorithms. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology (which is a commonly used framework to objectively perform systematic literature review) and a total of 95 articles identified from 15 purposively selected journals, this paper conducted a comprehensive systematic review of the uses of UAVs and UGVs in the CIS. Analysis was performed on the information extracted from these articles to (1) collect relevant, timely information and synthesize it into a cohesive summary of existing knowledge about the applications of UAVs and UGVs, (2) synthesize the current robotic platforms, performed tasks, major robotic accessories, and onboard sensing devices of UAVs and UGVs, (3) investigate existing techniques for sensing data analytics, and (4) outline the main challenges and potential opportunities for directing future studies and engineering practices in the CIS. While this paper serves as an expert reference and guide for both researchers and practitioners working in the smart, intelligent, and automated civil infrastructure domain, it also identifies the need for additional research and efforts to improve the uses of UAVs and UGVs and facilitating their developments in the CIS to improve and digitalize the built environment.