We address the synthesis of distributed control policies to enable a swarm of homogeneous mobile sensors to maintain a desired spatial distribution in a geophysical flow environment, or workspace. In this article, we assume the mobile sensors (or robots) have a "map" of the environment denoting the locations of the Lagrangian coherent structures or LCS boundaries. Using this information, we design agent-level hybrid control policies that leverage the surrounding fluid dynamics and inherent environmental noise to enable the team to maintain a desired distribution in the workspace. We discuss the stability properties of the ensemble dynamics of the distributed control policies. Since realistic quasi-geostrophic ocean models predict double-gyre flow solutions, we use a wind-driven multi-gyre flow model to verify the feasibility of the proposed distributed control strategy and compare the proposed control strategy with a baseline deterministic allocation strategy. Lastly, we validate the control strategy using actual flow data obtained by our coherent structure experimental testbed

In this paper, we describe the development of an experimental testbed capable of producing controllable ocean-like flows in a laboratory setting. The objective is to develop a testbed to evaluate multi-robot strategies for tracking manifolds and Lagrangian coherent structures (LCS) in the ocean. Recent theoretical results have shown that LCS coincide with minimum energy and minimum time optimal paths for autonomous vehicles in the ocean. Furthermore, knowledge of these structures enables the prediction and estimation of the underlying fluid dynamics. The testbed is a scaled flow tank capable of generating complex and controlled quasi-2D flow fields that exhibit wind-driven double-gyre flows. Particle image velocimetry (PIV) is used to extract the 2D surface velocities and the data is then processed to verify the existence of manifolds and Lagrangian coherent structures in the flow. The velocity data is then used to evaluate our previously proposed multi-robot LCS tracking strategy in simulation.

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