Speeding Up and Slowing Down Algorithms Supported by Acoustic Sensing in the Underwater Environment

This paper introduces an acoustic sensing-based speeding up and slowing down (SU-SD) algorithm for a fleet of underwater robots. Each robot transmits a series of acoustic pulses from a single transducer according to a pre-defined schedule. In a bi-static setup, all robots receive acoustic signals via a hydrophone array for navigation and coordination. Robots estimate angles of arrival from their neighbors through beam-forming techniques. Ranging is achieved by measuring the one-way travel time via the matched-filtering process. Each robot adjusts its number of transmitted pulses based on the quantization level of its measurement. This approach enables decentralized operation, with robots independently analyzing acoustic signals. Velocity adjustments are made based on variations in the number of acoustic pulses detected. Swarm cohesion is maintained through relative acoustic ranging between neighboring agents. Unlike the original SU-SD implementations that rely on global information exchange, our approach uses solely acoustic sensing for both relative localization and inter-robot spacing. Computer simulations using our developed software package, muNet-AUVSim, evaluate the algorithm with detailed vehicle dynamics and hydrodynamic damping models in ocean-like conditions. A group of five autonomous underwater vehicles (AUVs) is tested in source localization of a pollution plume under varying SUSD algorithm parameters. Results demonstrate that the swarms effectively converge on pollution sources while maintaining formation stability.