# Intention Recognition for Multiple AUVs in a Collaborative Search Mission
## 5 Numerical Experimental Analysis
### Comparative Analysis with Traditional Collaborative Search Methods  
To validate the performance of the proposed decision consensus-based intent recognition method in collaborative search missions, we designed a comparative experiment to compare this method with the collaborative search method discussed in [44]. We designed two typical experimental scenarios to test the search efficiency and mission completion  
Figure 10: The loss variation during the training process for different methods. capabilities of the method under different communication topology conditions (as shown in Figure 11):  
Scenario A: Good Communication Topology Conditions  
Scenario A simulates a collaborative search environment with favorable communication conditions. Under the initial conditions, the communication topology between the AUVs is fully connected, allowing each AUV to exchange state information in real time with all other AUVs. The objective of this scenario is to compare the efficiency of the two methods in completing the search mission, with the mission completion time being the primary evaluation metric. By testing the mission duration of both methods, we can assess the advantage of the proposed method in optimizing search paths and improving mission efficiency. Scenario B: Extreme Communication Topology Conditions  
Scenario B simulates an extreme environment under sparse communication conditions. In this scenario, the communication topology between the AUVs is limited, and information exchange can only occur between nodes within the local neighborhood range. This setting simulates real-world situations where communication may be interrupted or constrained. The goal is to evaluate the differences between the two methods in prediction and decision-making capabilities, particularly in maintaining mission completion rates and search efficiency when communication is incomplete. By testing the mission success rate and search efficiency of both methods, we analyzed the robustness and adaptability of the proposed method under extreme conditions. In the experiment, all models were tested under the same initial conditions, with evaluation metrics including search time and mission success rate. As shown in Table 8, the time taken to reach the target location using the two methods is 4219 s and 3140.5 s, respectively. The proposed method reduces the mission completion time by approximately 25.6%, demonstrating a significant improvement in efficiency. At each sampling moment, we calculated the total distance of all AUVs to their respective positioning points to quantify the progress of the collaborative search mission. The specific calculation method is as follows:  
\[\text{total DPP}=\sum_{i=1}^{n}\lVert Coord\_AUV_{i}-Coord\_PP_{i}\rVert \tag{6}\]  
Figure 11: The initial states of the two typical simulation scenarios. (**a**) Scenario A. (**b**) Scenario B. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Method** & **Without IR** & **Proposed** \\ \hline Arrival Time (s) & 4219 & 3140.5 \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Time for all AUVs to reach the positioning point in Scenario A.  
where \(n\) represents the number of AUVs, \(Coord\_AUV_{i}\) represents the coordinates of \(AUV_{i}\), and \(Coord\_PP_{i}\) represents the coordinates of their corresponding occupying sites. We visualized the results of the two methods in a graph, as shown in Figure 12. The plot illustrates the decline in total DPP over time, where the method proposed in this paper (with IR) achieves a faster reduction compared to the method without IR. This demonstrates that IR enhances the efficiency of collaborative search by enabling AUVs to reach their target positions more quickly. As shown in Figure 13, the simulation comparison results for Scenario A clearly demonstrate the advantages of the proposed CBIR method in collaborative search missions. From Figure 13a, it can be observed that the AUV's search path exhibits considerable redundant movement.