Hydrodynamic object recognition using pressure sensing

Abstract

Hydrodynamic sensing is instrumental to fish and some amphibians. It also represents, for underwater vehicles, an alternative way of sensing the fluid environment when visual and acoustic sensing are limited. To assess the effectiveness of hydrodynamic sensing and gain insight into its capabilities and limitations, we investigated the forward and inverse problem of detection and identification, using the hydrodynamic pressure in the neighbourhood, of a stationary obstacle described using a general shape representation. Based on conformal mapping and a general normalization procedure, our obstacle representation accounts for all specific features of progressive perceptual hydrodynamic imaging reported experimentally. Size, location and shape are encoded separately. The shape representation rests upon an asymptotic series which embodies the progressive character of hydrodynamic imaging through pressure sensing. A dynamic filtering method is used to invert noisy nonlinear pressure signals for the shape parameters. The results highlight the dependence of the sensitivity of hydrodynamic sensing not only on the relative distance to the disturbance but also its bearing.

Performance analysis for lateral-line-inspired sensor arrays

“…As seen in the parameterization by Bouffanais et al [6], the shape of a cylinder can be easily expressed as a series of perturbations of increasing complexity based on a conformal map. As the complexity increases, the order of the pole needed to represent the perturbation in potential flow also increases, resulting in a faster decay of the pressure generated by the perturbation.…”

“…Larger fish, potentially predatory, are not well modeled by small oscillatory dipoles and instead would be better approximated by blunt moving objects. Experiments by Vogel and Bleckmann [80] Two studies ( [70] and [6]) have considered parameterizations of the shape of an arbitrary object suitable for modeling flow and pressure distributions in potential flow. The authors have used these parameterizations to demonstrate how a simulated fish swimming in a potential flow could identify the shape of an object by swimming past or around it.…”

Biomimetic Survival Hydrodynamics and Flow Sensing

“…shown that a body moving in prescribed motion around another body can use distributed measurements over some time to create a complete map of the flow, provided the two bodies are in relatively close proximity, of the order of one body length or less (Sichert, Bamler & van Hemmen 2009;Bouffanais, Weymouth & Yue 2010); the presence of an external flow makes identification easier. Bouffanais, Weymouth & Yue (2010) analyzed the mapping of the environment via pressure signals in two ways, first to determine the pressure signal of a given obstacle shape and then to find the location and shape of a body given its pressure signal.…”

“…Bouffanais, Weymouth & Yue (2010) analyzed the mapping of the environment via pressure signals in two ways, first to determine the pressure signal of a given obstacle shape and then to find the location and shape of a body given its pressure signal. They found that insufficient information is provided about the shape by a pressure signal at a single location.…”

A fish perspective: detecting flow features while moving using an artificial lateral line in steady and unsteady flow

“…The sensing of the turbulent wake behind a cylinder using a virtual sensor has been described previously by Akanyeti et al [10], and object identification using pressure sensors has been completed for static arrays [11][12][13]. Further wake navigation algorithms have been previously developed based on the predicted pressure signal [14]. Research by Venturelli et al [15] sampled a KVS using two symmetric linear lateral lines running on either side of a three-dimensional 'boat-shaped' craft, as an analogue of the posterior lateral line.…”