  Many aquatic organisms are able to track ambient flow disturbances and locate
their source. These tasks are particularly challenging because they require the
organism to sense local flow information and respond accordingly. Details of
how these capabilities emerge from the interplay between neural control and
mechano-sensory modalities remain elusive. Inspired by these organisms, we
develop a mathematical model of a mobile sensor designed to find the source of
a periodic flow disturbance. The sensor locally extracts the direction of
propagation of the flow signal and adjusts its heading accordingly. We show, in
a simplified flow field and under certain conditions on the controller, that
the mobile sensor converges unconditionally to the source of the flow field.
Then, through carefully-conducted numerical simulations of flow past an
oscillating airfoil, we assess the behavior of the mobile sensor in complex
flows and demonstrate its efficacy in tracking the flow signal and locating the
airfoil. The proposed sensory and control strategy is relevant to the design of
bio-inspired underwater robots, but the general idea of orienting opposite to
the direction of information propagation can be applied more broadly in optimal
sensor placements and climate models.
