Tracking system with five degrees of freedom using a 2D-array of Hall sensors and a permanent magnet

Schlageter, Vincent; Besse, P.‐A.; Popović, R.S.; Kučera, Pavel

doi:10.1016/s0924-4247(01)00537-4

Cited by 159 publications

(91 citation statements)

References 3 publications

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“…This idea was investigated in many papers, e.g. [19], [21]. The technique requires finding a method for determining theoretical value of magnetic vector field.…”

Section: Modelling Vector Field Of a Permanent Magnetmentioning

confidence: 99%

“…Some authors tried using these distortions for detection and low accuracy tracking of metallic objects [16], [17]. Magnetic field produced by permanent magnets locally overshadow earth's, thus extensive research have been done on reverse problem of tracking permanently magnetised markers with relation to magnetometer and (most often) arrays of magnetometers [18], [19], [20], [21].…”

Section: Introductionmentioning

confidence: 99%

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Position tracking using inertial and magnetic sensing aided by permanent magnet

Meina

Rykaczewski

Rutkowski

2016

Annals of Computer Science and Information Systems

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Abstract-This paper describes a method for spatial tracking of a strapdown device that can be used for design of humancomputer interfaces. Inertial Measurement Unit (IMU) is used to obtain 6-dof position exploiting the so-called ZUPT technique by the means of the Kalman Filter. Additional corrections of position are done using magnetometer readings in the presence of static magnetic field induced by permanent magnet that overshadow geomagnetic field. This correction allows us to overcome drifting errors of integration of IMU readings. We have also presented comparisons of different models for magnetic field reconstruction that is crucial for this system.

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“…This idea was investigated in many papers, e.g. [19], [21]. The technique requires finding a method for determining theoretical value of magnetic vector field.…”

Section: Modelling Vector Field Of a Permanent Magnetmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Position tracking using inertial and magnetic sensing aided by permanent magnet

Meina

Rykaczewski

Rutkowski

2016

Annals of Computer Science and Information Systems

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“…Within the magnetic tracking community, the impact of the number of measurements has been studied by Schlageter et al (2001) and Plotkin and Paperno (2003). Schlageter et al (2001) found that the accuracy of their magnetic tracking system was improved when the number of transmitters, and thus the number of measurements, was doubled.…”

Section: Introductionmentioning

confidence: 99%

“…Schlageter et al (2001) found that the accuracy of their magnetic tracking system was improved when the number of transmitters, and thus the number of measurements, was doubled. Plotkin and Paperno (2003) found that using more transmitters reduces the number of local minima present in the inverse problem.…”

Section: Introductionmentioning

confidence: 99%

Convex optimization of measurement allocation for magnetic tracking systems

2016

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Magnetic tracking is a popular technique that exploits static and lowfrequency magnetic fields for positioning of quasi-stationary objects. One important system design aspect, which substantially influences the performance of the tracking system, is how to collect as much information as possible with a given number of measurements. In this work, we optimize the allocation of measurements given a large number of possible measurements of a generic magnetic tracking system that exploits time-division multiplexing. We exploit performance metrics based on the Fisher information matrix. In particular, the performance metrics measure worstcase or average performance in a measurement domain, i.e. the domain where the tracking is to be performed. An optimization problem with integer variables is formulated. By relaxing the constraint that the variables should be integer, a convex optimization problem is obtained. The two performance metrics are compared for several realistic measurement scenarios with planar transmitter constellations. The results show that the worst performance is obtained in the most distant parts of the measurement domain. Furthermore, measurement allocations optimized for worstcase performance require measurements in a larger area than measurement allocations optimized for average performance.

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“…The use of stationary magnetometers to determine position and orientation is proposed in several publications (Haynor et al, 2001;Beck, 2001;Yabukami et al, 2000;Schlageter et al, 2001). They model the object as a magnetic dipole moment inducing a magnetic dipole field that can be computed analytically.…”

Section: Introductionmentioning

confidence: 99%

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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Tracking system with five degrees of freedom using a 2D-array of Hall sensors and a permanent magnet

Cited by 159 publications

References 3 publications

Position tracking using inertial and magnetic sensing aided by permanent magnet

Position tracking using inertial and magnetic sensing aided by permanent magnet

Convex optimization of measurement allocation for magnetic tracking systems

Modeling of Magnetic Fields and Extended Objects for Localization Applications

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