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Article
Publication date: 31 January 2025

Minglu Chi, Shuaibing Chang, Zuhua Guo, Qiang Zhao, Guomiao Zhang and Fei Meng

To improve the localization accuracy of the magnetically controlled capsule endoscope (MCCE), a new localization method, based on the magnetic dipole model, is proposed, where the…

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Abstract

Purpose

To improve the localization accuracy of the magnetically controlled capsule endoscope (MCCE), a new localization method, based on the magnetic dipole model, is proposed, where the anti-disturbance permanent magnet (APM) is used as the source of stable magnetic field, thus reducing the interference of the geomagnetic field or the electric conductor magnetic field in the system.

Design/methodology/approach

The coupling magnetic force model between the APM and the capsule endoscope is established to obtain the magnetic force relationship and magnetic induction intensity. Along the three axes, magnetic induction intensity data are collected by a 3 × 3 sensor array composed of nine magnetic field intensity sensors, while the data are uploaded to the main computer by the STM32F103C8T6 control board over a ESP8266 WIFI module connection. Next, the axial magnetic induction intensity data are decoupled to obtain the measurement trajectory, whereas the error function is established based on the calculated trajectory parameters. Finally, the Levenberg–Marquardt (L-M) algorithm is used to solve the position information of the MCCE.

Findings

Experiments show that the average localization error of an MCCE in a straight and circular bend tube is 4.76 mm, whereas in a U-bend tube, it is 6.82 mm.

Originality/value

The optimized simulation value in the linear and bending environment is in good agreement with the experimental value, which verifies the accuracy of the MCCE localization system based on magnetic field sensor array, exhibiting good performance in localization and position tracking while providing a theoretical basis for the subsequent research.

Details

Robotic Intelligence and Automation, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2754-6969

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