We present the design and validation of the multi-robot coherent structure testbed (mCoSTe). The mCoSTe is an experimental testbed that is used to evaluate the performance of manifold and coherent structure tracking strategies by a team of autonomous surface vehicles in two-dimensional flows. It consists of a fleet of micro-autonomous surface vehicles (mASVs) equipped with onboard flow sensors and three experimental flow tanks: a Low Reynolds number (LoRe) Tank, a High Reynolds number (HiRe) Tank, and a Multi-Robot (MR) Tank. Each of the flow tanks are capable of producing controllable ocean-like flows in a laboratory setting. Flows in the HiRe and MR tanks are generated using a grid of independently controlled vortex driving cylinders. We show how the HiRe tank is capable of producing repeatable and controllable coherent structures in 2D by analyzing the surface flows using a a combination of Finite-Time Lyapunov Exponents (FTLE) and Dynamic Mode Decomposition (DMD). Using these results, a scaled flow is replicated in the MR Tank for experimental validation of robotic tracking strategies. Building upon our existing work, robotic tracking of manifolds and coherent structures in 2D flows is achieved through local sampling of the flow field using each vehicles onboard flow sensors. We describe the design and development of the mASVs and the onboard flow sensor and present experimental results to show the validity of our designs.

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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