This paper presents a modular software architecture that enables environmental-aware coordination of heterogeneous Autonomous Underwater Vehicles (AUVs) to improve underwater acoustic connectivity. The architecture combines a Robot Operating System 2 application layer with the DESERT Underwater communication framework through the rmw_desert middleware, and integrates a Robot Operating System 1 bridge to ensure interoperability with legacy vehicle front-seat controllers. This design enables fine-grained, cross-layer configurability of the communication stack and supports onboard processing of environmental measurements to inform adaptive communication behaviors. As a representative use case, this architecture is used to implement a lightweight depth-optimization strategy that exploits environmental awareness and AUV mobility to improve acoustic link performance. The complete software stack is validated through sea trials conducted off the Gulf of La Spezia in littoral water with an average depth of approximately 100m using a deployment involving three AUVs with distinct operational roles. Experimental results indicate that depth-adaptive repositioning yields measurable gains in packet reception at horizontal separation of approximately 1km, while differences are negligible at shorter ranges where the received signal energy remains above demodulation thresholds. Beyond link-level performance the sea trials confirm the feasibility, modularity, and practical deployability of the proposed architecture on existing AUV platforms.

翻译：本文提出一种模块化软件架构，通过环境感知协调异构自主水下航行器（AUV）以提升水声通信连通性。该架构通过rmw_desert中间件整合机器人操作系统2应用层与DESERT水下通信框架，并集成机器人操作系统1桥接器以兼容传统航行器前端控制器。此设计实现了通信协议栈细粒度跨层可配置性，并支持机载环境测量数据处理以驱动自适应通信行为。作为典型应用案例，本架构用于实现轻量级深度优化策略——利用环境感知与AUV移动性改善水声链路性能。完整软件栈通过斯佩齐亚湾近岸水域（平均深度约100米）的海试进行验证，部署了三艘功能分异的AUV。实验结果表明：在水平间距约1公里时，深度自适应重定位可显著提升数据包接收率；而在接收信号能量高于解调阈值的短距场景中性能差异可忽略。除链路层性能验证外，海试结果证实了所提架构在现有AUV平台上的可行性、模块化特性及实际部署能力。