Capsule endoscopy is a procedure that uses a tiny wireless camera inside a capsule endoscope to take pictures of patient&#x2019;s gastrointestinal tract for diagnosis. Gastrointestinal examination has been revolutionized by capsule endoscope for its simplicity and non-invasiveness. However, at this stage, the capsule endoscope has weak controllable locomotion capability, and does not have extended functions such as biopsy, localization, and therapeutics, which has become the main obstacle to expanding its application. Using an external magnetic field to actuate the capsule endoscope has the advantages of simple response structure inside the capsule and remote energy supply, which can expand the above-mentioned functions of the capsule endoscope and develop into a multifunctional capsule robot. This paper analyzes two types of magnetic actuation systems for magnetically actuated capsule robots, discusses the research on the functions of magnetically actuated capsule robots in active locomotion, anchoring, biopsy, localization, therapeutics, wireless power supply, and multi-capsule robot collaboration, and points out the existing problems and future development directions of magnetically actuated capsule robots. 

Magnetically Actuated Capsule Robots: A Review

Calibrating the magnetic sensor array is an inevitable but troublesome process before using it for tracking intra-body objects such as wireless capsule endoscope (WCE). Existing calibration methods generally require many samples with prior known pose information of the magnetic target, and then the unknown parameters can be estimated by minimizing the pose error. Aiming to simplify the calibration process, we propose a calibration-by-pivoting (CbP) method which does not require any predefined poses of the magnetic target. After mounting a magnet on the top of a pointed tool, the CbP method only requires the tool pivot at an arbitrary position within the measurable range of the array. Using the measured magnetic field data from the pivoting process, the proposed algorithm iteratively updates the unknown parameters by utilizing the constraint of the sphere determined by the calibration tool. Experimental results have shown that the magnetic sensor array can achieve good positioning and orientation accuracy after applied the proposed calibration method.

Calibration-by-Pivoting: A Simple and Accurate Calibration Method for Magnetic Tracking System

The magnetoresistive sensor strapped to the projectile is easily disturbed in highly dynamic environments, which has the problem of low accuracy for sensitive geomagnetic signals. In this article, a magnetoresistive sensor error compensation method using geometry-constraint contour scaling is proposed. A benchmark ellipsoid is obtained based on a two-step method. The shortest distance between any measured single point and the benchmark ellipsoid is calculated, and its position distribution relative to the benchmark ellipsoid is determined. The general form of the benchmark ellipsoid is converted into the standard form. The contour is scaled according to the shortest distance, and the single-point ellipsoid is obtained. The calibration parameters are extracted so that the single-point error compensation can compete. Simulation and experiment results show that the compensation accuracy of the proposed method is improved by two orders of magnitude compared with the traditional method.

Magnetoresistive Sensor Error Compensation Method Using Geometry-Constraint Contour Scaling

This article proposed a new compensation method for an underwater magnetic vector measurement system that innovatively uses the geomagnetic total field as a benchmark. Moreover, this method does not require the use of heading angle data in the calculation of the compensation parameters, which avoids errors caused by insufficient accuracy of underwater heading angle. The implementation of these features relies on the new objective function constructed according to the characteristics of the spatial projection of the magnetic vector field on the horizontal plane of the geographical coordinate. The core matrix of the geomagnetic vector ellipsoid model is used as a constraint to determine the range of the functional solutions. The Levenberg–Marquardt algorithm is used to find the optimal solution to the new objective function. Three experiments were carried out to verify the proposed method. In the simulation experiment, the deviation between the calculated value and the preset value is less than 0.01%. In a field experiment, the standard deviation (SD) value of <inline-formula> <tex-math notation="LaTeX">${x}$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">${y}$ </tex-math></inline-formula>, and <inline-formula> <tex-math notation="LaTeX">${z}$ </tex-math></inline-formula> magnetic components and the root-mean-square error (RMSE) of the magnetic total field after compensation are reduced from 1527.38, 1397.35, 1529.16, and 574.94 nT to 9.86 nT (0.65%), 9.99 nT (0.72%), 5.63 nT (0.38%), and 2.14 nT (0.37%). The proposed method is finally verified by the marine experiment. The SD values of <inline-formula> <tex-math notation="LaTeX">${x}$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">${y}$ </tex-math></inline-formula>, and <inline-formula> <tex-math notation="LaTeX">${z}$ </tex-math></inline-formula> magnetic components and the RMSE of the magnetic total field after compensation are reduced from 575.02, 830.60, 620.95, and 1702.35 nT to 17.43 nT (1.11%), 14.14 nT (1.70%), 25.17 nT (4.10%), and 7.18 nT (0.42%), respectively.

Compensation Method for the Carrier Magnetic Interference of Underwater Magnetic Vector Measurement System

The performance of magnetic anomaly detection (MAD) with magnetic gradient tensor (MGT) measurement system is severely limited by both the measurement errors and accuracy of localization algorithm. However, the robust calibration and localization method against various interferences and noises has not received the deserved attention. This study proposes a joint calibration and localization method with MGT to improve the accuracy of non-cooperative target (NCT) detection with environmental magnetic interferences and noise. First, compared to the previous calibration method requiring a uniform magnetic field environment and precise triaxial nonmagnetic turntable, a new calibration method based on multi-invariant constraints is studied, which is insensitive to the magnetic interferences and movement of array center during the calibration. Then, an adaptive multi-pair of MGTs localization (AMML) method is proposed for the MAD of NCT. On one hand, the corresponding multi-pair of MGTs are chosen adaptively depending on the condition number of MGT, which is far more robust against varying movement directions of NCT compared to previous methods. On the other hand, the AMML method is optimized with the Levenberg–Marquardt (LM) algorithm guided by the prior information of analytical scalar triangulation and ranging (STAR) method, which enhances the efficiency and accuracy of localization method significantly. The experimental results demonstrate that the AMML method reduces the localization error by 39%, 54.3%, and 55.4% compared to the new STAR method (NSM), Lv-STAR method (LSM) and conventional STAR method, respectively. 

A Robust Calibration and Adaptive Multi-pair of Magnetic Gradient Tensors Localization Method for Magnetic Anomaly Detection

Magnetic sensor array is usually designed for object detection and localization, where sensor coordinate is required to be consistent. Misalignment angles between coordinates should be calculated and calibrated. A new calibration method is proposed in order to calibrate the misalignment error between host frame and sensors. Host platform frame and perpendicular platform are used to obtain misalignment angles of sensor array. Experiment results show that it can estimate all angles of magnetic sensors and suppress misalignment error. Misalignment rms error is a reduction from 1109.7 to 27.6 nT, which means 2.48% indeed, thus improving the remote sensing accuracy of array which is unified to host frame coordinate.

Misalignment Error Suppression Between Host Frame and Magnetic Sensor Array

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Misalignment Error Suppression Between Host Frame and Magnetic Sensor Array