# Automated Docking System for LNG Loading Arm Based on Machine Vision and Multi-Sensor Fusion
## 3 Design of a Vision-Based Deep Learning Loading-Arm Positioning System
### Monocular Camera Localization Experiment  
The purpose of this experiment is to verify the localization accuracy of the monocular camera under the tilted viewing angle. The camera is mounted on a fixed tripod, and its mounting angle can be flexibly adjusted according to the needs to capture the images of the target object at different distances and under the movement of X and Y directions, and the experimental scene is shown in Figure 16. By adjusting the camera angle to simulate a tilted-view scene, the positioning error of the target object is analyzed to evaluate the applicability and accuracy of the system in real complex environments.  
The experimental environment of this study is shown in Table 3. In the experiments, the target objects were placed within the range from 0.2 m to 1.7 m from the camera, and they were placed along the straight-line direction at intervals of 0.1 m. The tilt angle of the camera was fixed at 50\({}^{\circ}\). During the image acquisition phase, the camera is kept fixed; multiple images (usually 3-5 images) are taken for each target object, and the best one is selected for image processing. Using the geometric constraint method and the coordinate conversion formula in Section 3.3.3, the measured coordinates of the target object in the image are extracted, and the actual coordinates of the target object are recorded at the  
Figure 16: Schematic diagram of an experiment.  
same time. According to the error calculation formula, the error rate is calculated and recorded in Table 4, and the changes in the external environment are monitored throughout the experiment, and any abnormalities that may affect the results should be recorded in a timely manner.  
The experimental results show that the error rates in the X, Y, and Z directions have their own characteristics. The error rates in the X-axis direction range from 0.67% to 6.00%, with an average error of 1.33%. Although the errors of most measurement points are within a reasonable range, the error rates of the 9 th and 11 th measurements are obviously high, reaching 6.00%, which may be due to the decrease in the feature recognition of the target object during the movement of the X-axis or the interference of external factors (such as slight vibration and airflow), indicating that the stability of the system needs to be further improved in certain situations. In contrast, the error rate in the Y-axis direction has a smaller range, from 0.10% to 1.00%, with an average error of 0.60%. The lower and less fluctuating error rate indicates that the system is less affected by external disturbances during Y-axis imaging and shows higher stability, especially for applications that require moderate Y-axis accuracy. In the Z-axis direction, the error rate is maintained between 0.71% and 0.95%, with an average error of 0.71%, and the error fluctuation remains stable as the measurement distance increases from 0.2 m to 1.7 m. This indicates that the system has good adaptability in the Z-axis direction, but further verification of its accuracy performance for longer distances is needed. Overall, the accuracy and stability of the system in the Y and Z directions are satisfactory, while individual anomalies in the X direction indicate the need to optimize the resistance to specific disturbances in order to improve the overall stability of the measurements.