A magnetic type tactile sensor by GMR elements and inductors

Goka, Masanori; Nakamoto, Hiroyuki; Takenawa, Satoru

doi:10.1109/iros.2010.5650283

Cited by 30 publications

(25 citation statements)

References 8 publications

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“…A number of different technologies have been used in endeavours to create better tactile sensors and sensitive skins. A wide variety of sensing techniques has stemmed from exploration of different transduction effects and materials, ranging from the use of large-scale arrays of discrete sensors based on organic FETs [12] or piezoresistive semiconductors [13]- [15] to sensors that use capacitive [16], [17], magnetic [18], 0000-0000/00$00.00 c 2012 IEEE [19], piezoelectric [20]- [25], optical [26]- [29] and other principles [30]- [32]. Often, multiple layers of different sensor types [9] are used in an attempt to imitate the sensing capabilities of human skin [33].…”

Section: Artificial Sensitive Skin For Roboticsmentioning

confidence: 99%

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Electrical Impedance Tomography for Artificial Sensitive Robotic Skin: A Review

et al. 2015

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Electrical impedance tomography (EIT) is a nondestructive imaging technique used to estimate the internal conductivity distribution of a conductive domain by taking potential measurements only at the domain boundaries. If a thin electrically conductive material-that responds to pressure with local changes in conductivity-is used as a conductive domain, then EIT can be used to create a large-scale pressure-sensitive artificial skin for robotics applications. This paper presents a review of EIT and its application as a robotics sensitive skin, including EIT excitation and image reconstruction techniques, materials and skin fabrication techniques. Touch interpretation via EIT-based artificial skins is also reviewed.

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Section: Artificial Sensitive Skin For Roboticsmentioning

confidence: 99%

“…Inductive/Magnetic [18], [19], [61]- [63] Change in magnetic coupling Linear output; high dynamic range. Moving parts; low spatial resolution; bulky; highly susceptible to noise.…”

Section: Typementioning

confidence: 99%

Electrical Impedance Tomography for Artificial Sensitive Robotic Skin: A Review

et al. 2015

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“…In this study, we have proposed a tactile sensor using a permanent magnet and giant magnetoresistive (GMR) elements [11,12]. The GMR elements convert change in magnetic flux density to output voltage.…”

Section: Journal Of Sensorsmentioning

confidence: 99%

Estimation of Displacement and Rotation by Magnetic Tactile Sensor Using Stepwise Regression Analysis

Nakamoto¹,

Wakabayashi²,

Kobayashi³

et al. 2014

Journal of Sensors

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The human is covered with soft skin and has tactile receptors inside. The skin deforms along a contact surface. The tactile receptors detect the mechanical deformation. The detection of the mechanical deformation is essential for the tactile sensation. We propose a magnetic type tactile sensor which has a soft surface and eight magnetoresistive elements. The soft surface has a permanent magnet inside and the magnetoresistive elements under the soft surface measure the magnetic flux density of the magnet. The tactile sensor estimates the displacement and the rotation on the surface based on the change of the magnetic flux density. Determination of an estimate equation is difficult because the displacement and the rotation are not geometrically decided based on the magnetic flux density. In this paper, a stepwise regression analysis determines the estimate equation. The outputs of the magnetoresistive elements are used as explanatory variables, and the three-axis displacement and the two-axis rotation are response variables in the regression analysis. We confirm the regression analysis is effective for determining the estimate equations through simulation and experiment. The results show the tactile sensor measures both the displacement and the rotation generated on the surface by using the determined equation.

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“…In order to cope with this increasingly pressing demand, over the past thirty years many tactile sensors have been proposed (see [7] for an extensive review, up to the year 2010). Even just during the last five years, a considerable number of solutions have been proposed, employing many different technologies: capacitive [8]- [11], optical [12], [13], piezoresistive [14]- [16] (see [17] for a recent review), piezoelectric [18]- [20], ultrasonic [21], magnetic [22]- [24], nanoparticles [25], carbon nanotubes [26], [27], conductive liquids [28]- [30], conductive polymers [31] and tunnel effect [32]. Unfortunately, only a few of these technologies have been tested in actual robots, and therefore it is not easy to evaluate to what extent the data extracted from these sensors is useful for robotic applications.…”

Section: Introductionmentioning

confidence: 99%

Highly Sensitive Soft Tactile Sensors for an Anthropomorphic Robotic Hand

et al. 2015

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The paper describes the design and realization of novel tactile sensors based on soft materials and magnetic sensing. In particular, the goal was to realize i) soft, ii) robust, iii) small and iv) low-cost sensors that can be easily fabricated and integrated on robotic devices that interact with the environment; we targeted a number of desired features, the most important being v) high sensitivity, vi) low hysteresis and vii) repeatability. The sensor consists of a silicone body in which a small magnet is immersed; an Hall-effect sensor placed below the silicone body measures the magnetic field generated by the magnet, which changes when the magnet is displaced due to an applied external pressure. Two different versions of the sensor have been manufactured, characterized and mounted on an anthropomorphic robotic hand; experiments in which the hand interacts with real world objects are reported.

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A magnetic type tactile sensor by GMR elements and inductors

Cited by 30 publications

References 8 publications

Electrical Impedance Tomography for Artificial Sensitive Robotic Skin: A Review

Electrical Impedance Tomography for Artificial Sensitive Robotic Skin: A Review

Estimation of Displacement and Rotation by Magnetic Tactile Sensor Using Stepwise Regression Analysis

Highly Sensitive Soft Tactile Sensors for an Anthropomorphic Robotic Hand

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