# Intention Recognition for Multiple AUVs in a Collaborative Search Mission
## 3 Description of the Intent Recognition Problem in AUV Collaborative Search Mission
### AUV Intention Characteristics  
The intent of AUVs is manifested through their actions and states, with the mapping from behavior and state to intent being determined by the collaborative search decision-making process. As such, it is imperative to first identify the factors that influence this decision-making process. Building on our prior work [44], we identify several key factors in the positioning phase, including the distance to the positioning point, the success rate of the received data, the distance to the parent node in the communication topology (PNCT), and the number of companions. In the tracking phase, the principal factors include the distance to the target, current detection errors, and the variance of detection errors over time. If these factors are obtained in a timely manner, the intentions of other AUVs can be predicted using the same decision-making method, facilitating adjustments to the collaborative strategy. However, due to the inherent characteristics of underwater acoustic communication, such as significant delays and packet loss, the transmission of this information may become unreliable. As a result, intention recognition is crucial for predicting the intentions of other AUVs.  
Intent recognition necessitates the fusion and analysis of information obtained from sensors, making the selection of appropriate feature inputs for the model crucial. The aforementioned factors are key contributors to intent recognition, but certain information, such as packet loss rate and detection error, exhibits significant temporal variation and has a more direct impact on intent. These factors can adversely affect the intent recognition of AUVs under conditions of high latency and packet loss. Therefore, we ultimately select the following information as inputs for the model: distance to the positioning point, distance to the PNCT, relative direction to the positioning point, relative direction to the PNCT, number of companions, and the average detection error. By integrating and analyzing these factors, we can more accurately capture the key elements influencing the variation in AUV intentions, thereby improving the accuracy and robustness of intent recognition. Table 2 further lists the specific meanings and related descriptions of each AUV intent feature indicator.  
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt}} \hline \hline
**Characteristic** & **Description** \\ \hline Distance to the positioning point & This distance reflects the overall progress of the search mission: As the AUV approaches the positioning point, it indicates that the search mission is nearing completion; once the positioning point is reached, the system will transition to the next phase of the mission or execute new instructions. \\ \hline Distance to the PNCT & This distance reflects the current communication status: The farther the distance from the PNCT, the poorer the communication quality. In this case, the AUV is more likely to prioritize “communication” to ensure stable data transmission and network security. \\ \hline Relative direction to the positioning point & It is determined by the deviation between the current heading of the AUV and the positioning point, providing an intuitive reflection of whether the AUV is moving toward the positioning point and the strength of its movement intention. \\ \hline \hline \end{tabular}
\end{table}
Table 2: The specific meanings and related descriptions of AUV intention characteristics.