Adaptable Swarm Sensing in Coastal Waters: Design and Performance of the
µFloat System
Abstract
Buoyancy-controlled underwater floats have produced a wealth of in situ
observational data from the open ocean. When deployed in large numbers,
or ‘swarms’, floats offer a unique capacity to concurrently map 3D
fields of critical environmental variables, such as currents,
temperatures, and dissolved oxygen. This sensing paradigm is equally
relevant in coastal waters, yet remains under-utilized due to economic
and technical limitations of existing platforms. To address this gap, we
developed a swarm of 25 µFloats that can actuate vertically in the water
column by controlling their buoyancy, but are otherwise Lagrangian.
Underwater positioning is achieved by acoustic localization using
low-bandwidth communication with GPS-equipped surface buoys. The µFloat
features a high-volume buoyancy engine that provides a 9% density
change, enabling automatic ballasting and vertical control from fresh to
salt water (∼ 3% density change) with reserve capacity for external
sensors. In this paper, we present design specifications and field
benchmarks for buoyancy control and acoustic localization accuracy.
Results demonstrate depth-holding accuracy within ±0.2 m of target depth
in quiescent flow and ±0.5 m in energetic flows. Underwater localization
is accurate to within ±5 m during periods with sufficient connectivity,
with degradation in performance resulting from adverse sound speed
gradients and unfavorable surface buoy array geometry. Support for
auxiliary sensors (<10% float volume) without additional
control tuning is also demonstrated. Overall performance is discussed in
the context of potential use cases and demonstrated in a first-ever
swarm-based three-dimensional survey of tidal currents.