# A Review of Detection Technologies for Underwater Cracks on Concrete Dam Surfaces
## 3 Dam Crack Detection Based on Underwater Robots
### Application of Underwater Robots in Dam Crack Detection  
In recent years, more and more underwater robots have been used in the underwater detection of hydraulic engineering. A variety of advanced underwater detection robots have been developed to provide economical, safe, and efficient solutions for the underwater inspection of large-scale hydraulic engineering facilities. [PERSON] et al. [59] designed and  
Figure 4: Underwater robot demonstration: (**a**) “Jiaolong” HOV [58]; (**b**) AUV; (**c**) ROV. Figure 3: Classification of underwater robots. built the \"Yulong\" dam maintenance submersible for underwater dam damage detection. The submersible can carry technicians to the site to identify defects and detect surface defects of the dam, grasp the underwater conditions of the dam in real time, and obtain comprehensive information on the dam surface in a timely manner. [PERSON] et al. [60] proposed an automated solution for the visual inspection of hydropower dams, which uses AUV to detect dam walls automatically, shoot images and collect navigation information at the same time, and generate high-quality geographic reference photos to realize systematic inspection. [PERSON] et al. [61] demonstrated an AUV system for a dam underwater inspection task to detect and measure cracks in hydropower dams. HOV and AUV have broad application prospects in underwater detection, but ROV power is supplied by the umbilical cable, and the working time is not limited. The ROV structure is mainly frame-based, and the portable equipment can be used in various occasions. Therefore, ROV meets the needs of most water conservancy and hydropower engineering inspections due to its advantages of good real-time performance, strong stability, and long battery life. In practical applications, ROV is the main model for the underwater detection of water conservancy and hydropower projects [32; 57]. [PERSON] et al. [44] used ROV to carry cameras, sonar, laser, and other sensors for the non-destructive detection of underwater concrete structures, and verified the feasibility of non-destructive detection of underwater structures through experiments. [PERSON] et al. [62] developed a hybrid AUV/ROV called TriMARES for the inspection and regular monitoring of large dam reservoirs in Brazil. [PERSON] et al. [63] proposed Anchor Driver 5.2 for dam detection, using an ROV with a camera for visual measurement of underwater concrete structures, and conducted a field experiment in the Amagase Dam of Japan. [PERSON] et al. [64] developed an underwater detection system consisting of an unmanned surface vehicle (USV) and an ROV suspended underwater to obtain the location of the measured point without using any high-cost equipment. [PERSON] et al. [65] applied ROV, sonar, and GPS to track and detect the inclined dam wall with full coverage. [PERSON] et al. [66] designed an underwater hybrid robot detection system composed of a crawler robot and an underwater robot, which realized vision-based surface crack detection and the estimation of robot position and attitude. [PERSON] et al. [67] developed an underwater detection robot for the detection of underwater structures such as dams, which can perform video capturing, indirect measurement using a laser, depth and heading keeping, and other functions; it has been applied in actual dam detection, proving its effectiveness. It is obvious that the development of underwater robots provides a safe, efficient, and economical platform for the detection of underwater structures such as dams. As an underwater mobile carrier, the underwater robot can be equipped with cameras or sonar to easily acquire a large number of underwater dam surface images and detect cracks on the underwater images based on digital image processing methods. However, the current research is still in the stage of data collection by various sensors installed on the underwater robot and detection by the above-water inspectors; the detection is not systematic enough and the degree of intelligence is not enough.