## 4 Recognition and Operation of Facade Protrusions
### Matching of Process Parameters
The size of the pixel equivalent is equal to the actual size of the real object divided by the pixel size of the object in the image, i.e., the actual physical size of a pixel. The formula for calculating the pixel equivalent is shown in Equation (2) [34]:

\[K=\frac{L_{r}}{L_{p}} \tag{2}\]

where \(L_{r}\) is the actual size of the object, \(L_{p}\) is the pixel size of the object in the image and \(K\) is pixel equivalent. The pixel equivalent can be calculated by fixing the camera imaging distance and measuring the pixel size of a standard size object in the image. In this paper, the pixel equivalent \(K=0.3885\text{mm}/pixel\) is obtained by averaging the measurements several times using a standard size block with micron-level accuracy as the calibration object. The distance of the missed spray area can therefore be obtained by multiplying the pixel distance by the pixel equivalent, as seen in Equation (3) as follows:

\[S=d_{\text{max}}\times K \tag{3}\]

where \(S\) is the actual distance of the missed spray and \(d_{\text{max}}\) is the maximum pixel distance of the missed spray. ### Parameter Adjustment

Wall-climbing robots can be affected by the environment, process parameter settings, structural accuracy and other factors during operation, resulting in the operation effect not meeting the expected requirements. In order to enable the wall-climbing robots to work continuously and efficiently under unmanned conditions, it is necessary to inspect the operation effect in real time and to make dynamic adjustments to the process parameters. The wall-climbing robot proposed in this paper has two main functions, namely rust removal and painting, with process parameters such as liquid pressure, gun swing angle and gun movement speed. For the rust removal operation, inspection errors and process parameters errors can result in insufficient liquid pressure and rust not being removed. The effect inspection \(img\_r\) returns the grey value of the image at the time and feeds the wall-climbing robot with the appropriate pressure parameters based on the size of the grey value, thus allowing the wall-climbing robot to work continuously on the facade protrusions as it moves. For the painting operation, the uniformity of the painting thickness and the accuracy of the painting path are important indicators of the painting operation. Due to the influence of the robot's movement errors, the painting problem can occur, and the swing angle may need to be adjusted so that it can cover the entire facade protrusion. The effect inspection _img_p_ returns the current distance and the position of the missed painting, and through the control motor, the wall-climbing robot dynamically adjusts the swing angle of the spray gun. The pseudocodes for parameter adjustment of rust removal and painting are given in Algorithm 3 and Algorithm 4, respectively:
```
Input: image of rust removal img_r, threshold of rust removal thres Output: process parameters \(P\), control command for the robot cmd
1:\(v\)\(\leftarrow\)0//Rust removal comparison value
2: Convert img_r to gray image gray
3: Obtain \(v\) according to equation(1)
4:cmd\(\leftarrow\)0
5:if\(v\) > thres then
6: Increase the pressure of a liquid in \(P\)
7: Reduce gun movement speed in \(P\)
8:else
9: Send a command cmd for the robot to move on
10:endif
11:return process parameters \(P\), control command cmd
```

**Algorithm 3** Dynamic adjustment of process parameters for rust removal

## 6 Experimental Results and Analysis

### Experimental Platform Construction and Preparation

As shown in Figure 6, the experimental prototype was installed using the Nvidia Jetson TX2 high-performance graphics processor with CUDA for high-performance-image processing work, taking into account the performance, portability and working environment. The camera was selected from the ZED binocular camera, which is versatile and powerful enough to carry out high-quality 3D video capture and can also be used for motion tracking, 3D mapping and other projects.