Ahmad T. Abdulsadda

An Artificial Lateral Line System Using IPMC Sensor Arrays

Most fish and aquatic amphibians use the lateral line system, consisting of arrays of hair-like neuromasts, as an important sensory organ for prey/predator detection, communication, and navigation. In this paper a novel bio-inspired artificial lateral line system is proposed for underwater robots and vehicles by exploiting the inherent sensing capability of ionic polymer–metal composites (IPMCs). Analogous to its biological counterpart, the IPMC-based lateral line processes the sensor signals through a neural network. The effectiveness of the proposed lateral line is validated experimentally in the localization of a dipole source (vibrating sphere) underwater. In particular, as a proof of concept, a prototype with body length (BL) of 10 cm, comprising six millimeter-scale IPMC sensors, is constructed and tested. Experimental results have shown that the IPMC-based lateral line can localize the source from 1–2 BLs away, with a maximum localization error of 0.3 cm, when the data for training the neural network are collected from a grid of 2 cm by 2 cm lattices. The effect of the number of sensors on the localization accuracy has also been examined.

Nonlinear estimation-based dipole source localization for artificial lateral line systems

As a flow-sensing organ, the lateral line system plays an important role in various behaviors of fish. An engineering equivalent of a biological lateral line is of great interest to the navigation and control of underwater robots and vehicles. A vibrating sphere, also known as a dipole source, can emulate the rhythmic movement of fins and body appendages, and has been widely used as a stimulus in the study of biological lateral lines. Dipole source localization has also become a benchmark problem in the development of artificial lateral lines. In this paper we present two novel iterative schemes, referred to as Gauss-Newton (GN) and Newton-Raphson (NR) algorithms, for simultaneously localizing a dipole source and estimating its vibration amplitude and orientation, based on the analytical model for a dipole-generated flow field. The performance of the GN and NR methods is first confirmed with simulation results and the Cramer-Rao bound (CRB) analysis. Experiments are further conducted on an artificial lateral line prototype, consisting of six millimeter-scale ionic polymer-metal composite sensors with intra-sensor spacing optimized with CRB analysis. Consistent with simulation results, the experimental results show that both GN and NR schemes are able to simultaneously estimate the source location, vibration amplitude and orientation with comparable precision. Specifically, the maximum localization error is less than 5% of the body length (BL) when the source is within the distance of one BL. Experimental results have also shown that the proposed schemes are superior to the beamforming method, one of the most competitive approaches reported in literature, in terms of accuracy and computational efficiency.

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

Motivated by the lateral line system of fish, arrays of flow sensors have been proposed as a new sensing modality for underwater robots. Existing studies on such artificial lateral lines (ALLs) have been mostly focused on the localization of a fixed underwater vibrating sphere (dipole source). In this paper we examine the problem of tracking a moving dipole source using an ALL system. Based on an analytical model for the moving dipole-generated flow field, we formulate a nonlinear estimation problem that aims to minimize the error between the measured and model-predicted magnitudes of flow velocities at the sensor sites, which is subsequently solved with the Gauss‐Newton scheme. A sliding discrete Fourier transform (SDFT) algorithm is proposed to efficiently compute the evolving signal magnitudes based on the flow velocity measurements. Simulation indicates that it is adequate and more computationally efficient to use only the signal magnitudes corresponding to the dipole vibration frequency. Finally, experiments conducted with an artificial lateral line consisting of six ionic polymer‐metal composite (IPMC) flow sensors demonstrate that the proposed scheme is able to simultaneously locate the moving dipole and estimate its vibration amplitude and traveling speed with small errors. (Some figures may appear in colour only in the online journal)

Underwater source localization using an IPMC-based artificial lateral line

Fish and aquatic amphibians use the lateral line system, consisting of arrays of hair-like neuromasts, as an important sensory organ for prey/predator detection, communication, and navigation. In this paper a novel bio-inspired artificial lateral line system is proposed for underwater robots and vehicles by exploiting the inherent sensing capability of ionic polymer-metal composites (IPMCs). Analogous to its biological counterpart, the IPMC-based lateral line processes the sensor signals through a neural network. The effectiveness of the proposed lateral line was validated in localization of underwater motion sources, including both a vibrating sphere (a dipole source) and a flapping foil. In particular, as a proof of concept, a prototype with Body Length (BL) of 8 cm, comprising five millimeter-scale IPMC sensors, was constructed and tested. Experimental results showed that the IPMC-based lateral line could localize the sources from 4–5 BLs away, with a localization error comparable to source placement resolution at the source-sensor separation of 1 BL. In addition to the ease of fabrication, these results established the competitiveness of the proposed approach, in terms of both localization range and accuracy, against the state of the art in artificial lateral lines.

Localization of source with unknown amplitude using IPMC sensor arrays

The lateral line system, consisting of arrays of neuromasts functioning as flow sensors, is an important sensory organ for fish that enables them to detect predators, locate preys, perform rheotaxis, and coordinate schooling. Creating artificial lateral line systems is of significant interest since it will provide a new sensing mechanism for control and coordination of underwater robots and vehicles. In this paper we propose recursive algorithms for localizing a vibrating sphere, also known as a dipole source, based on measurements from an array of flow sensors. A dipole source is frequently used in the study of biological lateral lines, as a surrogate for underwater motion sources such as a flapping fish fin. We first formulate a nonlinear estimation problem based on an analytical model for the dipole-generated flow field. Two algorithms are presented to estimate both the source location and the vibration amplitude, one based on the least squares method and the other based on the Newton-Raphson method. Simulation results show that both methods deliver comparable performance in source localization. A prototype of artificial lateral line system comprising four ionic polymer-metal composite (IPMC) sensors is built, and experimental results are further presented to demonstrate the effectiveness of IPMC lateral line systems and the proposed estimation algorithms.

Artificial lateral line-based localization of a dipole source with unknown vibration amplitude and direction

The lateral line system is an important sensory organ for fish and many aquatic amphibians, allowing them to detect predators/prey, perform rheotaxis, and coordinate schooling. There is an increasing interest in developing artificial lateral line systems, consisting of arrays of flow sensors, for underwater vehicles and robots. In this paper we consider the problem of localizing a vibrating sphere, also known as a dipole source, using an artificial lateral line system. Dipole sources emulate the movement of fish fins and are often used in the study of biological lateral lines. We assume that the location, vibration amplitude, and vibration direction of the dipole sources are all unknown. A nonlinear estimation problem is formulated based on the analytical model for dipole-generated flow field. We present two recursive algorithms for source localization, the first obtained by linearizing the original nonlinear estimation problem, and the other by solving the equations corresponding to the first-order optimality condition. Simulation results are presented to illustrate the effectiveness of the proposed approaches.

Underwater Tracking and Size-Estimation of a Moving Object Using an IPMC Artificial Lateral Line

Motivated by the lateral line system of fish and amphibians, arrays of flow sensors have been proposed as a new sensing modality for underwater robots. Most existing studies on such artificial lateral lines have been focused on the localization of a vibrating sphere, also known as a dipole source. In this paper we investigate the problem of tracking a moving but non-vibrating cylindrical object and estimating its size and shape using an artificial lateral line system. Based on a nonlinear analytical model for the moving object-induced flow field, a two-stage extended Kalman filter is proposed to estimate the location, velocity, size, and shape of the object. Simulation results on tracking a cylinder with ellipsoidal cross-section are presented to illustrate the approach. On the experimental side, we demonstrate the use of an artificial lateral line prototype comprising six ionic polymer-metal composite (IPMC) flow sensors in the tracking and size estimation of a moving circular cylinder.Copyright

Localization of a moving dipole source underwater using an artificial lateral line

Motivated by the lateral line system of fish, arrays of flow sensors have been proposed as a new sensing modality for underwater robots. Existing studies on such artificial lateral lines (ALLs) have been mostly focused on the localization of a fixed underwater vibrating sphere (dipole source). In this paper we examine the problem of tracking a moving dipole source using an ALL system. A nonlinear estimation problem is formulated based on an analytical model for the moving dipole-generated flow field, which is subsequently solved with the Gauss-Newton method. The effectiveness of the proposed approach is illustrated with simulation results.