A Cubic 3-Axis Magnetic Sensor Array for Wirelessly Tracking Magnet Position and Orientation

Hu, Chao; Li, Mao; Song, Shuang; Yang, Wei; Zhang, Rui; Meng, Max Q.-H.

doi:10.1109/jsen.2009.2035711

Cited by 191 publications

(67 citation statements)

References 28 publications

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“…The position and attitude (x p , y p , z p , α p , β p , γ p ) of each exploring coil can be solved precisely. In this paper the Gauss-Newton method is employed in the fast algorithm and it converges faster [16][17][18][19]. It is not only conducive to the reduction of iteration delay and data processing time, but also improves the precision of the electromagnetic positioning navigation and realizes the miniaturization of the probe.…”

Section: Electromagnetic Navigation Modelmentioning

confidence: 99%

Fast numerical algorithm for a high-precision 6D electromagnetic positioning navigation system

Xiang¹,

Wang²,

Liu³

2014

Turk J Phys

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Abstract:A fast numerical algorithm is proposed for the 6 degrees of freedom electromagnetic navigation system, which can be used to improve surgical operations guided by medical images. Both the rotation transformation technique and optimization technique are adopted in the algorithm. The results from simulations show that the calculating time is improved greatly under the required precision in the surgery. A navigation system based on the algorithm can make the medical device's dimensions miniaturized and the structure simplified and portable. The performance and application scope of the electromagnetic positioning navigation system can be improved.

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Section: Electromagnetic Navigation Modelmentioning

confidence: 99%

Fast numerical algorithm for a high-precision 6D electromagnetic positioning navigation system

Xiang¹,

Wang²,

Liu³

2014

Turk J Phys

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“…This magnetic dipole moment includes both position and orientation of that object as well as its magnetic strength. This initial work has been further elaborated by Yabukami et al (2002Yabukami et al ( , 2003, Hu et al (2005Hu et al ( , 2006Hu et al ( , 2008Hu et al ( , 2010) and researchers at Institute of Physiology, University of Lausanne (Stathopoulos et al, 2005;Guignet et al, 2006). Their primary application has been to record images of the digestive track, so-called capsule endoscopy, where a capsule equipped with a small magnet can be localized during its path through the tract.…”

Section: Introductionmentioning

confidence: 98%

Modeling of Magnetic Fields and Extended Objects for Localization Applications

Wahlström¹

2015

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Cover illustration: The cover shows a magnetic dipole field (3.6), which is used as the sensor model in Paper A. The dipole is placed at the height of the front cover with position r 0 = [104 mm, 90 mm, 0 mm] relative to the bottom left corner of the front cover, with the magnetic dipole moment m = [0. 85, 0.53, 0] being orthogonal to its surface. A 3D cutout of the scalar potential for the magnetic dipole ϕ(r) = (r·m) r 3 is displayed on front, back and side cover, where r is the displacement relative to the position of the magnetic dipole. On the front cover, the field lines of the magnetic dipole field are overlaid.Linköping studies in science and technology. Dissertations.No. 1723 Modeling of Magnetic Fields and Extended Objects for Localization Applications AbstractThe level of automation in our society is ever increasing. Technologies like selfdriving cars, virtual reality, and fully autonomous robots, which all were unimaginable a few decades ago, are realizable today, and will become standard consumer products in the future. These technologies depend upon autonomous localization and situation awareness where careful processing of sensory data is required. To increase efficiency, robustness and reliability, appropriate models for these data are needed. In this thesis, such models are analyzed within three different application areas, namely (1) magnetic localization, (2) extended target tracking, and (3) autonomous learning from raw pixel information. Magnetic localization is based on one or more magnetometers measuring the induced magnetic field from magnetic objects. In this thesis we present a model for determining the position and the orientation of small magnets with an accuracy of a few millimeters. This enables three-dimensional interaction with computer programs that cannot be handled with other localization techniques.Further, an additional model is proposed for detecting wrong-way drivers on highways based on sensor data from magnetometers deployed in the vicinity of traffic lanes. Models for mapping complex magnetic environments are also analyzed. Such magnetic maps can be used for indoor localization where other systems, such as gps, do not work.In the second application area, models for tracking objects from laser range sensor data are analyzed. The target shape is modeled with a Gaussian process and is estimated jointly with target position and orientation. The resulting algorithm is capable of tracking various objects with different shapes within the same surveillance region.In the third application area, autonomous learning based on high-dimensional sensor data is considered. In this thesis, we consider one instance of this challenge, the so-called pixels to torques problem, where an agent must learn a closedloop control policy from pixel information only. To solve this problem, highdimensional time series are described using a low-dimensional dynamical model. Techniques from machine learning together with standard tools from control theory are used to autonomously design a controller f...

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“…The method in [8] is based on magnetic field strength which reported 1.8 mm average localization error. Though the accuracy of [8] is high, the method requires more space in the capsule. Since VCE is equipped with a radio communication system, developing localization system using RF techniques got attention.…”

Section: Introductionmentioning

confidence: 99%

Local Parametric Approach of Wireless Capsule Endoscope Localization Using Randomly Scattered Path Loss Based WCL

Hany

Akter

2017

Wireless Communications and Mobile Computing

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We propose scattered path loss based weighted centroid localization (WCL) algorithm for wireless video capsule endoscope (VCE). The main challenge in this approach is the random deviation in the measured received signal strength indicator (RSSI) caused by multipath propagation and shadowing effects of human body channel which in turn increases the localization error. To address this issue, we propose local parameter dependent path loss representation in the training phase and apply adaptive least square error (LSE) method to extract the parameters. Then, in the test phase, we estimate distance using the extracted parameters and the randomly scattered path loss. The position of capsule is estimated using non-degree based WCL followed by a calibration process. We propose suboptimal method of estimating the calibration coefficient and also compute the optimal value of coefficient analytically to set the benchmark. We develop a simulation platform using MATLAB to present the results and to verify the performance. We gradually increase the number of sensors and place them in different topologies using different dimensions. The obtained accuracy by our proposed suboptimal method of WCL is very close to the optimal benchmark for all cases. Our proposed approach also outperforms existing works in terms of localization accuracy.

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A Cubic 3-Axis Magnetic Sensor Array for Wirelessly Tracking Magnet Position and Orientation

Cited by 191 publications

References 28 publications

Fast numerical algorithm for a high-precision 6D electromagnetic positioning navigation system

Fast numerical algorithm for a high-precision 6D electromagnetic positioning navigation system

Modeling of Magnetic Fields and Extended Objects for Localization Applications

Local Parametric Approach of Wireless Capsule Endoscope Localization Using Randomly Scattered Path Loss Based WCL

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