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Related Experiment Video

Updated: May 12, 2026

Electromagnetic Source Imaging in Presurgical Evaluation of Children with Drug-Resistant Epilepsy

Electromagnetic Source Imaging in Presurgical Evaluation of Children with Drug-Resistant Epilepsy

Published on: September 20, 2024

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

Ahmad T Abdulsadda¹, Xiaobo Tan

¹Smart Microsystems Laboratory, Department of Electrical and Computer Engineering, Michigan State University, East Lansing, MI 48824, USA. abdulsad@msu.edu

Bioinspiration & Biomimetics

|March 30, 2013

Summary

This summary is machine-generated.

This study introduces novel Gauss-Newton and Newton-Raphson algorithms for precisely locating dipole sources and estimating their vibration. These methods enhance artificial lateral line systems for underwater navigation.

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Development of New Methods for Quantifying Fish Density Using Underwater Stereo-video Tools

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Development of New Methods for Quantifying Fish Density Using Underwater Stereo-video Tools

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Published on: November 20, 2017

Area of Science:

Biomimetics
Robotics
Fluid Dynamics

Background:

The biological lateral line system in fish senses fluid flow, crucial for behaviors.
Artificial lateral lines are vital for underwater robot navigation and control.
Dipole sources, mimicking fin movements, are key stimuli for studying lateral lines.

Purpose of the Study:

To develop and validate novel iterative algorithms for dipole source localization and parameter estimation.
To enhance the functionality of artificial lateral line systems for underwater applications.
To compare the performance of new algorithms against existing methods like beamforming.

Main Methods:

Developed Gauss-Newton (GN) and Newton-Raphson (NR) iterative schemes based on an analytical dipole flow model.
Validated algorithms using simulations and Cramer-Rao bound (CRB) analysis.
Conducted experiments on an artificial lateral line prototype with optimized ionic polymer-metal composite sensors.

Main Results:

GN and NR algorithms accurately estimated dipole source location, vibration amplitude, and orientation.
Localization error was less than 5% of body length within one body length.
Proposed schemes outperformed the beamforming method in accuracy and computational efficiency.

Conclusions:

The GN and NR algorithms offer precise and efficient solutions for dipole source localization.
These algorithms significantly advance the development of artificial lateral line systems.
Optimized sensor arrays and advanced algorithms are key to robust underwater sensing.