# A Survey on Unmanned Surface Vehicles for Disaster Robotics: Main Challenges and Directions
## 5 USV Applications for Preventive Maintenance and Disaster Response
### Structure Inspection for Preventive Maintenance  
Robotic inspection has gained visibility in civil engineering [45], an area not traditionally connected to robotics. Its applications with regards to disasters can be classified by the management phase in which they occur: in the preparedness and mitigation phases, before a disaster, structure inspection is performed to aid preventive maintenance of buildings and infrastructure, potentially minimizing damages and losses in the event of a disaster. Historically, USVs for preventive structure inspection was first proposed to the application of bridge scour assessment, a task typically performed by a team of divers and engineers, using manual cameras, human vision and touch [173]. According to the United States Department of Transportation [174], scour is the erosion of stream-beds or bank material due to water flow from natural currents, or debris brought by disaster events (e.g., storms, tsunamis or floods). When it happens around a pier, bridge, or other manned structure, it can open gaps in the bed supporting the structure, risking its collapse and turning it into hazardous environment for the inspection crew. [PERSON] and [PERSON] [175] proposed a USV which successfully assisted teams performing bridge scour assessment in six flood events. Apart from bridge scour assessment, USVs are also used to verify structural health in above-water or partially submerged constructions, with 3D reconstruction [176; 177; 178; 179; 180; 181; 182], for example, where USVs collect sensor data from a structure (e.g., camera images, sonar distances), reconstructing the structure for offline inspection. In this application, [PERSON] et al. [176] use a USV to capture 3D LiDAR sensor data of oil rigs and dams to perform the subsequent reconstruction for preventive inspection. The authors tested the USV in the Singapore Strait, where several structures were reconstructed from the captured data. One of the challenges for accurate 3D reconstruction is that precise localization is necessary when collecting data, typically not available using only GPS sensors, as shadowing effects and line-of-sight occlusion significantly affect the localization accuracy. [PERSON] [177] solves this problem with a new framework for 3D SLAM, which combines data from above and below the water surface (i.e., a heterogeneous environment). The framework is integrated and tested in a USV capable of robust mapping and reconstruction of 3D marine structures. Likewise, [PERSON] et al. [178; 179] use USVs to scan both above and below the water surface, to perform 3D reconstruction of partially submerged marine constructions. The solution uses the Iterative Closest Point (ICP) algorithm, with data from a Velodyne LiDAR (model HDL-64E S2) and a BlueView side-scanner sonar (model MB2250), to reconstruct the above and below-water parts of a jetty in Selat Pauh, a small island on the Singapore Sea. The authors note that powerful water currents change the unmanned vehicle's roll and pitch motions, sometimes causing outlier data in the LiDAR scans, which must be previously filtered. [PERSON] et al. [180; 181; 182] perform 3D reconstruction of bridges and semi-submerged offshore platforms. In [180; 181], the authors use the ICP algorithm along with data from cameras, Inertial Measurement Units (IMU), GPS, and LiDARs installed on a Kayak-based USV, to reconstruct above-water bridges in the Bang-Dong reservoir, in Korea. As a limitation, the 3D reconstruction is sensitive to navigation and positioning errors, as GPS accuracy is affected below bridges. In [180], the authors fuse data from a USV's sensor array, including 2D and 3D LiDAR, IMU, GPS, and underwater sonar sensors, to reconstruct the hull of a semi-submersible offshore platform in Okpo, Korea. To avoid the reconstruction sensitivity to localization errors, the USV performs local navigation, relative to the planar hull structure, dismissing the need for high GPS accuracy. More recently, [PERSON] et al.