Drone Path Planning for Bridge Substructure Inspection Considering GNSS Signal Shadowing

Drones are useful tools for performing tasks that are difficult for humans. Thus, they are being increasingly utilized in various fields. In smart construction, a range of methods, including robots and drones, has been proposed to inspect facilities and other similar structures. Global navigation satellite system (GNSS) shadowing can occur when large bridge substructures, which are difficult for humans to access, are inspected using drones because GNSS is a major component in drone operation. This study develops a path planning algorithm to address areas with GNSS shadowing. The operation mode of the drone is classified into waypoint selection based on the photography point algorithm (WPS-PPA) and GNSS non-shadowing area algorithm (WPS-GNSA). Both algorithms are experimentally compared for flight performance in the GNSS shadowing area. A field experiment was conducted by varying the distance between the drone and the bridge substructure and by comparing the success of the flights. In successful flights, the GNSS reception of WPS-GNSA reached 1.4 times that of WPS-PPA. Furthermore, even in failed flights, compared to the WPS-PPA algorithm, the WPS-GNSA algorithm continued flight until the GNSS signal further deteriorated. Accordingly, WPS-GNSA is more favorable than WPS-PPA for inspecting bridge substructures under GNSS signal shadowing.