Optimal Flow Sensing for Schooling Swimmers

Weber, Pascal; Arampatzis, Georgios; Novati, Guido; Verma, Siddhartha; Papadimitriou, Costas; Koumoutsakos, Petros

doi:10.3390/biomimetics5010010

Cited by 18 publications

(12 citation statements)

References 76 publications

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“…Local vorticity could be computed from several velocity sensors. Not considered here are distributed sensing schemes, such as distributed pressure or shear sensors, which can be effective for flow sensing and identification 17 . Coupling optimal flow sensor distribution (e.g.…”

Section: Resultsmentioning

confidence: 99%

“…Some seal species can orient themselves and hunt in total darkness by detecting currents with their whiskers 16 . Additionally, a numerical study of fish schooling demonstrated how surface pressure gradient and shear stress sensors on a downstream fish can determine the locations of upstream fish, thus enabling energy-efficient schooling behavior 17 .…”

Section: Introductionmentioning

confidence: 99%

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Learning efficient navigation in vortical flow fields

et al. 2021

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Efficient point-to-point navigation in the presence of a background flow field is important for robotic applications such as ocean surveying. In such applications, robots may only have knowledge of their immediate surroundings or be faced with time-varying currents, which limits the use of optimal control techniques. Here, we apply a recently introduced Reinforcement Learning algorithm to discover time-efficient navigation policies to steer a fixed-speed swimmer through unsteady two-dimensional flow fields. The algorithm entails inputting environmental cues into a deep neural network that determines the swimmer’s actions, and deploying Remember and Forget Experience Replay. We find that the resulting swimmers successfully exploit the background flow to reach the target, but that this success depends on the sensed environmental cue. Surprisingly, a velocity sensing approach significantly outperformed a bio-mimetic vorticity sensing approach, and achieved a near 100% success rate in reaching the target locations while approaching the time-efficiency of optimal navigation trajectories.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Learning efficient navigation in vortical flow fields

et al. 2021

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“…Artificial lateral lines with biomimetic neuromasts have been developed and applied to bioinspired swimming robots (Fan et al, 2002;Yang et al, 2010;Xu and Mohseni, 2017;Liu et al, 2020). Optimal sensor locations for artificial swimmers have been also investigated to improve the efficiency (Verma et al, 2019;Weber et al, 2020), especially when the number of biomimetic neuromasts is limited. The sensing of external hydrodynamic stress may improve the control robustness in single-fish self-organized undulatory swimming (Thandiackal et al, 2021), as well as the propulsive efficiency (Tytell et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

Hydrodynamical Fingerprint of a Neighbour in a Fish Lateral Line

Kolomenskiy

et al. 2022

Front. Robot. AI

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For fish, swimming in group may be favorable to individuals. Several works reported that in a fish school, individuals sense and adjust their relative position to prevent collisions and maintain the group formation. Also, from a hydrodynamic perspective, relative-position and kinematic synchronisation between adjacent fish may considerably influence their swimming performance. Fish may sense the relative-position and tail-beat phase difference with their neighbors using both vision and the lateral-line system, however, when swimming in dark or turbid environments, visual information may become unavailable. To understand how lateral-line sensing can enable fish to judge the relative-position and phase-difference with their neighbors, in this study, based on a verified three-dimensional computational fluid dynamics approach, we simulated two fish swimming adjacently with various configurations. The lateral-line signal was obtained by sampling the surface hydrodynamic stress. The sensed signal was processed by Fast Fourier Transform (FFT), which is robust to turbulence and environmental flow. By examining the lateral-line pressure and shear-stress signals in the frequency domain, various states of the neighboring fish were parametrically identified. Our results reveal that the FFT-processed lateral-line signals in one fish may potentially reflect the relative-position, phase-differences, and the tail-beat frequency of its neighbor. Our results shed light on the fluid dynamical aspects of the lateral-line sensing mechanism used by fish. Furthermore, the presented approach based on FFT is especially suitable for applications in bioinspired swimming robotics. We provide suggestions for the design of artificial systems consisting of multiple stress sensors for robotic fish to improve their performance in collective operation.

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“…For a grid search, the associated computational cost is and thus grows exponentially with the number of tests. This curse of dimensionality is avoided by using a sequential optimization method ( 23, 31, 32 ) to approximate the global optimum by iteratively solving where s = ( k, t ) is the location and time to be estimated sequentially starting with n = 1 and …”

Section: Supplementary Materials Formentioning

confidence: 99%

Optimal Testing Strategy for the Identification of COVID-19 Infections

Chatzimanolakis

Weber

Arampatzis

et al. 2020

Preprint

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The systematic identification of infectious, yet unreported, individuals is critical for the containment of the COVID-19 pandemic. We present a strategy for identifying the location, timing and extent of testing that maximizes information gain for such infections. The optimal testing strategy relies on Bayesian experimental design and forecasting epidemic models that account for time dependent interventions. It is applicable at the onset and spreading of the epidemic and can forewarn for a possible recurrence of the disease after relaxation of interventions. We examine its application in Switzerland and show that it can provide timely and systematic guidance for the effective identification of infectious individuals with finite testing resources. The methodology and the open source code are readily adaptable to countries around the world.

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Optimal Flow Sensing for Schooling Swimmers

Cited by 18 publications

References 76 publications

Learning efficient navigation in vortical flow fields

Learning efficient navigation in vortical flow fields

Hydrodynamical Fingerprint of a Neighbour in a Fish Lateral Line

Optimal Testing Strategy for the Identification of COVID-19 Infections

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