Underwater tracking of a moving dipole source using an artificial lateral line: algorithm and experimental validation with ionic polymer–metal composite flow sensors

This paper introduces the near-field detection system of an underwater robot based on the fish lateral line. Inspired by the perception mechanism of fish’s lateral line, the aim is to add near-field detection functionality to an underwater vehicle. To mimic the fish’s lateral line, an array of pressure sensors is developed and installed on the surface of the underwater vehicle. A vibrating sphere is simulated as an underwater pressure source, and the moving mechanism is built to drive the sphere to vibrate at a certain frequency near the lateral line. The calculation of the near-field pressure generated by the vibrating sphere is derived by linearizing the kinematics and dynamics conditions of the free surface wave equation. Structurally, the geometry shape of the detection system is printed by a 3D printer. The pressure data are sent to the computer and analyzed immediately to obtain information of the pressure source. Through the experiment, the variation law of the pressure is generated when the source vibrates near the body, and is consistent with the simulation results of the derived pressure calculation formula. It is found that the direction of the near-field pressure source can distinguished. The pressure amplitude of the sampled signals are extracted to be prepared for the next step to estimate the vertical distance between the center of the pressure source and the lateral line.

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“…which is widely adopted in [26][27][28]. Substituting the parameters into Equation (3), the velocity potential φ is given by:…”

Section: Design Of Control Systemmentioning

confidence: 99%

Underwater Robot Detection System Based on Fish’s Lateral Line

Tang

Wang

et al. 2019

Electronics

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“…These vibration-detecting sensors would be crucial for navigation, detection, and tracking in low-light conditions, or in scenarios where the use of onboard lights or sonar is undesirable, either for maintaining stealth, or for minimally intrusive observation of animals. Current prototypes of such artificial sensors are based on arrays of pressure transducers (Fernandez et al 2011;Venturelli et al 2012;Xu & Mohseni 2017), and mechanically deforming hair-like structures (Yang et al 2006;Tao & Yu 2012;Abdulsadda & Tan 2013;Dagamseh et al 2013;DeVries et al 2015;Triantafyllou et al 2016).…”

Section: Introductionmentioning

confidence: 99%

Optimal sensor placement for artificial swimmers

et al. 2019

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Natural swimmers rely for their survival on sensors that gather information from the environment and guide their actions. The spatial organization of these sensors, such as the visual fish system and lateral line, suggests evolutionary selection, but their optimality remains an open question. Here, we identify sensor configurations that enable swimmers to maximize the information gathered from their surrounding flow field. We examine twodimensional, self-propelled and stationary swimmers that are exposed to disturbances generated by oscillating, rotating and D-shaped cylinders. We combine simulations of the Navier-Stokes equations with Bayesian experimental design to determine the optimal arrangements of shear and pressure sensors that best identify the locations of the disturbance-generating sources. We find a marked tendency for shear stress sensors to be located in the head and the tail of the swimmer, while they are absent from the midsection. In turn, we find a high density of pressure sensors in the head along with a uniform distribution along the entire body. The resulting optimal sensor arrangements resemble neuromast distributions observed in fish and provide evidence for optimality in sensor distribution for natural swimmers. † Email address for correspondence: petros@ethz.ch arXiv:1906.07585v1 [physics.flu-dyn]

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“…The capacitive detection principle was also used to fabricate bioinspired sensors based on fish SNs that contained an SU-8 hair cell [46,62]. Some flow sensors are based on the piezo-electric or depolarization detection principle [47,[63][64][65][66]. These hair cell-inspired sensors were made from ionic polymer-metal composites (IPMCs).…”

Section: Biomimetic Flow Sensors: State Of the Artmentioning

confidence: 99%

Micro-Machined Flow Sensors Mimicking Lateral Line Canal Neuromasts

et al. 2015

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Fish sense water motions with their lateral line.The lateral line is a sensory system that contains up to several thousand mechanoreceptors, called neuromasts. Neuromasts occur freestanding on the skin and in subepidermal canals. We developed arrays of flow sensors based on lateral line canal neuromasts using a biomimetic approach. Each flow sensor was equipped with a PDMS (polydimethylsiloxane) lamella integrated into a canal system by means of thick-and thin-film technology. Our artificial lateral line system can estimate bulk flow velocity from the spatio-temporal propagation of flow fluctuations. Based on the modular sensor design, we were able to detect flow rates in an industrial application of tap water flow metering. Our sensory system withstood water pressures of up to six bar. We used finite element modeling to study the fluid flow inside the canal system and how this flow depends on canal dimensions. In a second set of experiments, we separated the flow sensors from the main stream by means of a flexible membrane. Nevertheless, these biomimetic neuromasts were still able to sense flow fluctuations. Fluid separation is a prerequisite for flow measurements in medical and pharmaceutical applications.

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Underwater tracking of a moving dipole source using an artificial lateral line: algorithm and experimental validation with ionic polymer–metal composite flow sensors

Cited by 54 publications

References 67 publications

Underwater Robot Detection System Based on Fish’s Lateral Line

Underwater Robot Detection System Based on Fish’s Lateral Line

Optimal sensor placement for artificial swimmers

Micro-Machined Flow Sensors Mimicking Lateral Line Canal Neuromasts

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