Underwater Robot Detection System Based on Fish’s Lateral Line

Abstract

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.

Fish Lateral Line Inspired Flow Sensors and Flow-aided Control: A Review

“…The pressure field generated by vibrating sphere which was simulated as an underwater pressure source was derived by means of linearizing the kinematic and dynamic conditions of the free surface wave equation. The pressure field detected by the ALL was consistent with simulation results [62] .…”

“…(a) The fish-shaped prototype inspired by the trout lateral line in Ref. [62]. (b) Photo of an AHC sensor array used in Ref.…”

“…Table 3 as follows can be a summary of this section. Flow induced by oscillating sources Tang et al 2019 [62] 8 pressure sensors Linearizing the kinematic and dynamic conditions of the free surface wave equation Yang et al 2007 [30] An array of AHC sensors Extracting velocity amplitudes at the sphere vibration frequency Yang et al 2010 [32] 15 biomimetic neuromasts Beamforming algorithm Pandya et al 2006 [44] An array of 16 hot-wire anemometers Template training approach and the modeling approach Asadnia et al 2013 [33] An array of 2 by 5 pressure sensors Measuring the maximum peak-to-peak out put of the sensors Abdulsadda et al 2011 [35] 5 IPMC sensors Neural network Abdulsadda et al 2013 [65] , Chen et al 2012 [69,70] 6 IPMC sensors Gauss Newton and Newton Raphson algorithms Ahrari et al 2016 [66] Multiple flow velocity sensors Bi-level optimization methodology Zheng et al 2018 [63] 9 underwater pressure sensors forming a cross Generalized regression neural network Lin et al 2018 [64] 9 pressure sensors in a straight line Least square method Ji et al 2018 [76] 9 pressure sensors in a straight line MUSIC, MVDR Ji et al 2019 [77] 9 pressure sensors in a straight line CRLB model…”

An Artificial Lateral Line Sensor Using Polyvinylidene Fluoride (PVDF) Membrane for Oscillatory Flow Sensing

“…At present, there are two types of artificial lateral line systems, one uses the pressure sensor array to mimic canal neuromasts and the other uses a hair-like artificial lateral line system to mimic superficial neuromasts. For some artificial lateral line systems using pressure sensors, Tang et al [57] introduced a near field detection system for an underwater robot based on a fish lateral line, and an array of pressure sensors was developed and installed on the surface of an underwater vehicle. Eight pressure sensors were used to build the array, and the resolution was approximately 0.0036 Mbar.…”

An Environmental Perception Framework for Robotic Fish Formation Based on Machine Learning Methods

“…Yanagitsuru et al [22] used pressure sensors to detect flow parameters (flow speed, vortex shedding frequency, and cylinder diameter), and the results provide insight into the sensory ecology of schools of fish and give implications for the design of autonomous underwater vehicles. Inspired by the lateral line of fish, Tang et al [23] proposed a new kind of near-field detection system to be applied to detect impending walls, approaching obstacles and other target objects. Nawi et al [24] could detect the moving objects located in front of the sensor by an artificial lateral line flow sensor.…”