# Digital-Twin-Based System for Foam Cleaning Robots in Spent Fuel Pools
## 6 Experimental Validation and Analysis
### Conclusions  
The essence of digital twinning remains rooted in simulation, offering significant advancements in the service capabilities and levels of various application domains. It is a prevailing trend that will shape the future, with theoretical research and technological applications extending beyond manufacturing to encompass agriculture, urban planning, construction, power systems, and numerous other fields. This paper established a digital twin model for a depleted fuel pool foam cleaning robot, encompassing the physical robot's modeling, simulation, and twinning mapping, as well as of the operational environment. This enabled data transfer between the physical and virtual robots, facilitating the execution of detection tasks in the virtual environment. Furthermore, the paper enhanced the full-coverage path planning and achieved precise obstacle avoidance for the robot. Ultimately, a depleted fuel pool foam cleaning robot system was constructed based on digital twinning. The primary contributions of this paper are outlined below:  
(1) Substantial improvements were made to the practical application of the full-coverage path planning algorithm, resulting in enhanced cleaning efficiency and reduced energy consumption for the robot.  
(2) Using the digital twin platform for obstacle localization and detection, while simultaneously transmitting obstacle information to the robot in real-time to assist in obstacle avoidance, enhanced the stability and safety of the robot's cleaning operations, considering the limitations of robot power and computational capacity.  
(3) Performing a virtual-physical fusion through digital twinning enabled real-time monitoring of the robot's motion status, facilitating users in obtaining information regarding the robot's movements.  
However, the digital twinning approach proposed in this paper still has several limitations. Our future work will encompass the following: (1) Enhancing the accuracy of data collection through methods such as deep learning and image recognition. (2) Further refining the modeling of work scenarios, robot structures, and kinematic models to make the virtual space more closely resemble real-world operations.  
Methodology, M.L. and F.C.; Validation, M.L.; Resources, F.C.; Data curation W.Z.; Writing--original draft, M.L.; Writing--review and editing, W.Z.; Project administration, M.L. and W.Z. All authors have read and agreed to the published version of the manuscript.  
This research was funded by \"Development of Underwater Acoustic Transducer Based on Two-Dimensional Curved Surface Composite Materials\" grant number. 61871043.  
Not applicable.  
Due to the nature of this research, participants of this study did not agree for their data to be shared publicly, so supporting data is not available.  
The authors declare no conflict of interest.  
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Time Point/s**} & \multicolumn{3}{c}{**The Physical Robot’s Position**} & \multicolumn{3}{c}{**The Virtual Robot’s Position**} & \multicolumn{3}{c}{**Margin of Error\%**} \\  & \multicolumn{3}{c}{**Coordinates and Motion Direction**} & \multicolumn{3}{c}{**Coordinates and Motion Direction**} & \multicolumn{3}{c}{**Margin of Error\%**} \\ \cline{2-10}  & **Horizontal/m** & **Vertical/m** & **Angle/(\({}^{\circ}\))** & **Horizontal/m** & **Vertical/m** & **Angle/(\({}^{\circ}\))** & **Horizontal** & **Vertical** & **Angle** \\ \hline \(t1=200\) & \(3.262\) & \(4.266\) & \(24.63\) & \(3.266\) & \(4.263\) & \(24.59\) & \(0.122\) & \(-0.070\) & \(-0.162\) \\ \(t2=500\) & \(6.371\) & \(6.537\) & \(-86.18\) & \(6.371\) & \(6.531\) & \(-86.29\) & \(0\) & \(-0.092\) & \(0.128\) \\ \(t3=800\) & \(8.116\) & \(2.485\) & \(133.26\) & \(8.120\) & \(2.485\) & \(133.13\) & \(0.049\) & \(0\) & \(-0.098\) \\ \(t4=1100\) & \(11.482\) & \(7.774\) & \(73.89\) & \(11.486\) & \(7.779\) & \(73.96\) & \(0.035\) & \(0.064\) & \(0.095\) \\ \hline \hline \end{tabular}
\end{table}
Table 3: Digital twin robot monitoring synchronization experiment.