Inspired by the multi-head attention (MHA) mechanism in natural language processing, this letter proposes an iterative single-head attention (ISHA) mechanism for multi-UAV path planning. The ISHA mechanism is run by a communication helper collecting the state embeddings of UAVs and distributing an attention score vector to each UAV. The attention scores computed by ISHA identify how many interactions with other UAVs should be considered in each UAV’s control decision-making. Simulation results corroborate that the ISHA-based communication and control framework achieves faster travel with lower inter-UAV collision risks than an MHA-aided baseline, particularly under limited communication resources.

中文翻译：

---

基于注意力的多无人机路径规划通信与控制

受自然语言处理中的多头注意力（MHA）机制的启发，这封信提出了一种用于多无人机路径规划的迭代单头注意力（ISHA）机制。ISHA 机制由一个通信助手运行，该通信助手收集 UAV 的状态嵌入并将注意力得分向量分配给每个 UAV。ISHA 计算的注意力分数确定了在每个无人机的控制决策中应考虑与其他无人机的交互次数。仿真结果证实，与 MHA 辅助基线相比，基于 ISHA 的通信和控制框架能够实现更快的飞行，同时降低无人机间的碰撞风险，尤其是在通信资源有限的情况下。