Vertical Profiling in Estuaries Using AUV Networks

This paper presents a field-validated framework for cooperative environmental monitoring using a network of micro-autonomous underwater vehicles (AUVs) deployed in the Delaware River, PA. Leveraging the Jaia Robotics LLC Hydro platform (Jaiabot)—low-cost, micro-sized, high-speed aquatic drones designed for data collection and payload delivery—the system performs vertical profiling of environmental parameters such as temperature and salinity through coordinated multi-robot formation control and cooperative sensor fusion. Building on control and estimation architectures previously introduced by the authors, this work integrates a navigation function-based formation controller for confined aquatic environments, a reconfigured dive controller to eliminate depth overshoot, and a geometry-aware cooperative Kalman filter for distributed scalar field estimation into a unified system. The integrated framework is demonstrated through synchronized multi-depth dives across river cross-sections under real-world conditions, revealing spatial temperature gradients and validating the robustness of the control and estimation architecture. These results mark the first deployment of vertically coordinated, formation-controlled AUV sensing with precise relative positioning in a dynamic estuarine setting, offering a scalable, autonomous approach to real-time water quality assessment.