Robotics and unmanned aerial vehicles for smart structural health monitoring: A systematic review

Structural health monitoring (SHM) plays a vital role in maintaining the safety and function of civil infrastructure; however, conventional monitoring approaches typically rely heavily on manual access, fragmented data acquisition, and offline analysis, which limits efficiency and scalability. In recent years, robotic systems and unmanned aerial vehicles (UAVs) have gradually emerged as a highly promising method towards more automated and flexible SHM practices. This article synthesizes recent advances in robot- and UAV-based inspection across diverse infrastructure types, including bridges, buildings, dams, and underground spaces, examining their mobility characteristics, sensing configurations, and application scenarios. Particular attention is paid to algorithmic progress in autonomous navigation, defect detection, 3D reconstruction, and emerging edge-intelligence concepts that enable perception-driven inspection workflows. Based on the reviewed literature, key technical advantages and persistent limitations of current robotic and UAV platforms are identified, including challenges related to onboard intelligence, energy efficiency, environmental robustness, and operational integration. Finally, the article outlines future research directions toward intelligent, cooperative, and scalable mobile SHM systems, supporting the transition of robots and UAVs from data-acquisition tools to field-deployable inspection agents for resilient infrastructure management.