Touchless underwater wall-distance sensing via active proprioception of a robotic flapper.

In this work, we explored a bioinspired method for underwater object sensing based on active proprioception. We investigated whether the fluid flows generated by a robotic flapper, while interacting with an underwater wall, can encode the distance information between the wall and the flapper, and how to decode this information using the proprioception within the flapper. Such touchless wall-distance sensing is enabled by the active motion of a flapping plate, which injects self-generated flow to the fluid environment, thus representing a form of active sensing. Specifically, we trained a long short-term memory (LSTM) neural network to predict the wall distance based on the force and torque measured at the base of the flapping plate. In addition, we varied the Rossby number (Ro, or the aspect ratio of the plate) and the dimensionless flapping amplitude (A∗) to investigate how the rotational effects and unsteadiness of self-generated flow respectively affect the accuracy of the wall-distance prediction. Our results show that the median prediction error is within 5% of the plate length for all the wall-distances investigated (up to 40 cm or approximately 2-3 plate lengths depending on theRo); therefore, confirming that the self-generated flow can enable underwater perception. In addition, we show that stronger rotational effects at lowerRolead to higher prediction accuracy, while flow unsteadiness (A∗) only has moderate effects. Lastly, analysis based on SHapley Additive exPlanations (SHAP) indicate that temporal features that are most prominent at stroke reversals likely promotes the wall-distance prediction.

Flow Interactions Between Low Aspect Ratio Hydrofoils in In-line and Staggered Arrangements.

Many species of fish gather in dense collectives or schools where there are significant flow interactions from their shed wakes. Commonly, these swimmers shed a classic reverse von Kármán wake, however, schooling eels produce a bifurcated wake topology with two vortex rings shed per oscillation cycle. To examine the schooling interactions of a hydrofoil with a bifurcated wake topology, we present tomographic particle image velocimetry (tomo PIV) measurements of the flow interactions and direct force measurements of the performance of two low-aspect-ratio hydrofoils ( = 0 . 5 ) in an in-line and a staggered arrangement. Surprisingly, when the leader and follower are interacting in either arrangement there are only minor alterations to the flowfields beyond the superposition of the flowfields produced by the isolated leader and follower. Motivated by this finding, Garrick's linear theory, a linear unsteady hydrofoil theory based on a potential flow assumption, was adapted to predict the lift and thrust performance of the follower. Here, the follower hydrofoil interacting with the leader's wake is considered as the superposition of an isolated pitching foil with a time-varying cross-stream velocity derived from the wake flow measurements of the isolated leader. Linear theory predictions accurately capture the time-averaged lift force and some of the major peaks in thrust derived from the follower interacting with the leader's wake in a staggered arrangement. The thrust peaks that are not predicted by linear theory are likely driven by spatial variations in the flowfield acting on the follower or nonlinear flow interactions; neither of which are accounted for in the simple theory. This suggests that unsteady potential flow theory that does account for spatial variations in the flowfield acting on a hydrofoil can provide a relatively simple framework to understand and model the flow interactions that occur in schooling fish. Additionally, schooling eels can derive thrust and efficiency increases of 63-80% in either a in-line or a staggered arrangement where the follower is between two branched momentum jets or with one momentum jet branch directly impinging on it, respectively.