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Sensors and Actuators A 295 (2019) 541–550

Contents lists available at ScienceDirect

Sensors and Actuators A: Physical

journa l homepage: www.e lsev ier .com/ locate /sna

ow-hysteresis and low-interference soft tactile sensor using aonductive coated porous elastomer and a structure fornterference reduction

yungseo Park a, Seunghwan Kim a, Hyosang Lee b, Inkyu Park a, Jung Kim a,∗

Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon, 34141, Republic of KoreaMax Planck Institute for Intelligence Systems, Germany

r t i c l e i n f o

rticle history:eceived 24 August 2018eceived in revised form 13 May 2019ccepted 13 June 2019vailable online 15 June 2019

eywords:oft tactile sensorysteresis

nterference reduction structureonductive coated porous elastomer

a b s t r a c t

The need for soft whole-body tactile sensors is emerging. Piezoresistive materials are advantageous interms of making large tactile sensors, but the hysteresis of piezoresistive materials is a major drawback.The hysteresis of a piezoresistive material should be attenuated to make a practical piezoresistive softtactile sensor. In this paper, we introduce a low-hysteresis and low-interference soft tactile sensor usinga conductive coated porous elastomer and a structure to reduce interference (grooves). The developedsensor exhibits low hysteresis because the transduction mechanism of the sensor is dominated by thecontact between the conductive coated surface. In a cyclic loading experiment with different loadingfrequencies, the mechanical and piezoresistive hysteresis values of the sensor are less than 21.7% and6.8%, respectively. The initial resistance change is found to be within 4% after the first loading cycle. Toreduce the interference among the sensing points, we also propose a structure where the grooves areinserted between the adjacent electrodes. This structure is implemented during the molding process,which is adopted to extend the porous tactile sensor to large-scale and facile fabrication. The effectsof the structure are investigated with respect to the normalized design parameters �D, �W , and �T in a

simulation, and the result is validated for samples with the same design parameters. An indentationexperiment also shows that the structure designed for interference reduction effectively attenuates theinterference of the sensor array, indicating that the spatial resolution of the sensor array is improved. Asa result, the sensor can exhibit low hysteresis and low interference simultaneously. This research can beused for many applications, such as robotic skin, grippers, and wearable devices.

© 2019 Elsevier B.V. All rights reserved.

. Introduction

The importance of tactile information in the physical human-obot interaction (pHRI) has been constantly raised due to itsontribution in reducing uncertainty the environment around theobot. The information about the environments around a robot cane exploited for motion planning, decision making, interactions,nd safety. Some works utilize visual information due to its advan-age in recognizing objects, but it is difficult to obtain information

bout physical contact. Furthermore, contact can occur at multipleocations and out of the sight; hence, using only visual informations insufficient to enable the robot to work in the pHRI environ-

∗ Corresponding author.E-mail addresses: kyungseo.park@kaist.ac.kr (K. Park),

unghwan1106@kaist.ac.kr (S. Kim), hslee@is.mpg.de (H. Lee), inkyu@kaist.ac.krI. Park), jungkim@kaist.ac.kr (J. Kim).

ttps://doi.org/10.1016/j.sna.2019.06.026924-4247/© 2019 Elsevier B.V. All rights reserved.

ment. In contrast, tactile information is more reliable during contactbecause physical quantities such as a reaction force and vibrationare directly obtained from the physical interaction. These data canhelp robots deal with dangerous situations, such as clamping andcollision, and reduce the severity of the accident [1]. On the otherhand, a soft material can absorb energy and attenuate the impactforce due to its compliance. A tactile sensor that is made using a softmaterial will also show conformity on curved surfaces and human-skin-like mechanical properties [2–5]. Therefore, it is necessary todevelop a whole-body soft tactile sensor.

With the goal of developing a whole-body soft tactile sensor,we had to optimize the sensor requirements for the purpose of thesensor. For example, a soft tactile sensor for a robotic hand shouldhave a high spatial resolution and accuracy [6,7] because it is used

for object recognition, manipulation, and force feedback [8–10].In addition, it should be possible to measure the temperature ortexture because multimodal information can be useful for object

5 Actuat

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42 K. Park et al. / Sensors and

ecognition. In contrast, whole-body soft tactile sensors cover theody of the robot, which is not used for delicate tasks. Instead,hole-body soft tactile sensors must achieve other requirements,

uch as low cost, accessibility, scalability, and durability. If the sen-or is expensive, it will be too costly to install the sensor over allarts of the body, making it difficult to study or use the sensor in aeal environment. Thus, we must ensure that the production pro-ess is as inexpensive and easy as possible. In the pHRI, the sensoray be exposed to a strong impact, so the sensor should be suffi-

iently durable against an external force. In addition, the reliabilityf the system becomes poor if the configuration and wiring of theystem are too complicated. Therefore, the size of the sensor itselfeeds to be increased to simplify the system.

Soft sensors transduce a force and deformation to other physicaluantities, such as capacitance [11–13], resistance [14–16], optical

ntensity [17–19]. Capacitive and piezoresistive methods are com-on transduction methods for soft tactile sensors. Capacitive-type

ensors estimate the deformation of the sensor based on a changen capacitance by utilizing a soft material or air as a dielectric. Thehange in capacitance is only related to geometrical changes, sohe sensor exhibits low hysteresis and high repeatability. How-ver, it is difficult to realize a large soft tactile sensor using theapacitive method due to the limitation of the design parame-ers. Instead of making a single large array, the capacitive tactileensor can be modularized using rigid electronics to cover a largeurved surface [20]. On the other hand, the piezoresistive methods advantageous for making a sensor with a large curved shapeue to the ease of the fabrication process. A piezoresistive mate-ial experiences a change in resistance due to a deformation, whichan be measured by using array indexing [21–24] or tomographicmaging [25–27]. Clearly, piezoresistive soft sensors have uniquedvantages for whole-body soft tactile sensors. However, mostiezoresistive soft tactile sensors exhibit high hysteresis, whichakes the signal unreliable [28]. Generally, most piezoresistiveaterials exhibit conductivity by the formation of a network of con-

uctive fillers such as silver nanowires [29,30], carbon nanotubesCNTs) [25,31,32], and metal particles [24]. The problem is that theesistance is affected by not only the mechanical deformation ofhe sensor at the macroscale but also changes in the internal con-uctive network. In most cases, conductive networks are not fullyecovered after a deformation due to the realignment of the poly-

er chain and the conductive filler [33]. For example, CNT bundlesan slide and buckle during repeated deformations, causing unpre-ictable and irreversible changes in the initial resistance [34]. Someesearchers report contact-type piezoresistive materials with a dif-erent transduction mechanism. Han et al. developed a conductiveNT-polymer sponge [35]. The resistance of this material decreasesuring compression, because a short conductive pathway is gen-rated when the coated surfaces are attached. This study reportshat the resistance changes nonlinearly and monotonically. Yaot al. also developed a pressure-sensitive graphene-polyurethaneponge based on a fractured microstructure design [36]. The resis-ance varied due to the contact of graphene on the fracture of theorous structure, so that the resistance changes were dominated byhe deformation only. In summary, these conductive coated porouslastomers exhibit less hysteresis than a mixture-type piezoresis-ive material, because these materials are less affected by changesn the conductive network.

Another issue associated with a piezoresistive soft tactile sen-or is the interference on the sensor array. Array indexing is widelysed for the operation of a large sensor; two electrodes are selectedn each side, and physical quantities, such as resistance and capac-

tance, are measured at the intersection of the electrodes. Thisethod makes it possible to cover a large area with a small number

f electrodes, but interference may occur among the sensing points.ince we fabricate a single large piezoresistive rather than attaching

ors A 295 (2019) 541–550

small sensors, each sensing point is electrically connected becausethey are not insulated from each other. This means that there is anunintended conductive pathway among the sensing points, whichleads to interference. Some studies have made the sensor as thinas possible to reduce interference [37]. However, this method canonly be applied for thin materials, such as a force-sensitive resistor(FSR) or a pressure-sensitive film. Thus, this method is not suitablein our case, because the conductive coated porous elastomer mustbe thick compared to the pore size. In addition, a whole-body tactilesensor needs to be thick and soft for shock absorption.

In this study, we aim to improve the hysteresis and interfer-ence of a tactile sensor array. First, we use a conductive coatedporous elastomer to reduce the hysteresis of the sensor. The con-ductive coated porous elastomer is prepared by coating the innersurface of open-cell-type porous PDMS with a CNT-dispersed solu-tion [35]. When the sensor is compressed, the conductive surfacesof the sensor attach to each other and form new conductive path-ways. Currents flow through this new conductive pathway so thatthe resistance can be decreased. Second, we propose a structureto reduce the interference of the sensor array. Since the sensingpoints of the conductive coated porous elastomer are not insu-lated, there is interference among the sensing points of the sensor.To address this problem, we design the sensor to have groovesbetween the parallel electrodes on the same sides, which reducesthe unintended electrical connection between the electrodes. Wealso conduct a design parameter study of the grooves with a sim-ulation and validate the result by a comparison with the samples.An indentation experiment is also carried out to investigate theeffect of the grooves, and the results show that the structure caneffectively suppress the interference.

This paper is organized as follows: Section II briefly explains theconcept of the sensor, including the transduction mechanism andscanning method. The sensor structure is explained in Section IIIwith parameter studies and a validation. The fabrication processof the sensor is explained in Section IV. In Section V, the charac-teristics of the sensor are investigated through cyclic loading andan indentation experiment. Finally, the results of this research arediscussed in Section VI.

2. Concept of the sensor

2.1. Conductive coated porous elastomer (CNT-coated porousPDMS)

The proposed sensor uses the piezoresistive method, whichtransduces a deformation into a change in resistance. The con-ductive coated porous elastomer consists of a porous scaffold andconductive coating surface. The type of porous structure is an opencell, and the inner surface of the pores can be coated with conduc-tive particles such as CNTs, graphene, carbon black, metal particles,and conductive polymers. In this paper, we utilize multiwalledCNTs (MWCNTs) to form a conductive surface due to their excep-tional electrical properties. Scanning electron microscopy (SEM)images of the porous structure and CNT-coated surface are shownin Fig. 1. The conductive coated porous elastomer is made into alarge sponge sheet, and fabric electrodes are installed on both sidesof the sheet. When a normal directional force is applied to the sen-sor, the conductive surfaces on the pores attach as the pores close,so the resistance decreases. The transduction mechanism of theCNT-coated porous PDMS is shown in Fig. 1-(d). The change in thesurface condition can affect the resistance, but it can be neglected

because the resistance change is dominated by the contact betweenthe conductive surface. Therefore, the sensor exhibits low hystere-sis compared to the hysteresis of a mixture-type piezoresistivematerial.

K. Park et al. / Sensors and Actuators A 295 (2019) 541–550 543

Fig. 1. (a–c) SEM image of the CNT-coated porous PDMS, and each red circle indicates the pores, coated surface, and CNTs, respectively (scales: 500 �m, 100 �m, and 5 �m).( retativ

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d) Transduction mechanism of the conductive coated porous elastomer. (For interpersion of this article.)

.2. Scanning method

We implement an array indexing method to scan the resistivityistribution of the tactile sensor. Line electrodes are placed on eachide of the sensor for array indexing. The electrodes are selectedne by one on each side, and the normal directional resistances areeasured at the intersections of the selected electrodes. A constant

oltage is applied to the row electrode, and we measure the out-ut voltages from an inverting amplifier installed on the columnlectrode. The intersection between the selected electrodes corre-ponds to the sensing points. A schematic of the sensing systemnd sensor prototype is shown in Fig. 2.

The sensing system consists of the sensor, a multiplexing andmplifier circuit, and a data acquisition (DAQ) system. The rowlectrodes of the sensor are connected to 16 channel multiplexorsDG506, analog device, USA), and a constant voltage is applied to theow electrode through the multiplexer. Each column of electrodess connected to an inverse amplifier (AD704, analog device, USA),nd the output lines of the inverse amplifier are also connected tohe multiplexor. Multiplexing and the measurement are performedsing data acquisition board (cRIO-9036, National Instrument Inc.,SA), which allows a fast sampling frequency and multiplexing bytilizing a field-programmable gate array (FPGA) chip. The mea-ured data are transferred to a PC through TCP communication.

. Sensor structure

.1. Interference of the array

The ideal scenario in this scheme is that the output signal is notffected by unselected sensing points, but there are several factors

hat can produce interference in real situations. The first is the inter-erence caused by current flowing through an unintended path.

hen two orthogonal electrodes are selected, the current shouldnly flow through the intersection of the selected electrodes. If the

on of the references to colour in this figure legend, the reader is referred to the web

unselected electrode is floating, a crosstalk current flows, as shownin Fig. 3- (a). The red line indicates the crosstalk current, and blueand green glows indicate the resistance of the sensing points andthe leakage resistance, respectively. This interference can be elim-inated by fixing the potential of several unselected electrodes tothe ground [38]. Thus, we installed an inverting amplifier on thecolumn electrodes to fix the potential of the column electrodes tothe ground, as shown in Fig. 2-(a). Even if the circuit configurationis modified, the leakage resistance still produces interference, asshown in Fig. 3-(b).

The second reason for the interference is the drive voltage dropdue to the internal resistance of the multiplexer [21]. When a volt-age is applied to the row electrodes through the multiplexer, theactual circuit is configured like a voltage divider so that the volt-age applied to the row electrode is lower than the intended value.For the array indices (i, j) and the corresponding resistance valueRs(i, j), the output voltage Vout(i, j) is given by the equation

Vout(i, j) = Vd (i)

(− RfRs(i, j)

)

where Vd(i) is the applied voltage to the selected i-th row electrodeand Rf is the resistance value of the feedback resistor of the invert-ing amplifier. Then, the resistance value at (i, j) and its change dueto an indentation are

Rs(i, j) = −(Vd (i)Vout(i, j)

)Rf , �Rs (i, j) = Rs (i, j) − Rs,0 (i, j)

= −Rf Vd(i) ·(

1Vout (i, j)

− 1Vout,0 (i, j)

)

where Rs,0 (i, j) is the initial resistance of the sensing point and

Vout,0 (i, j) is the output voltage corresponding to the initial resis-tance. However, the above equation does not hold when the appliedvoltage Vd(i) is changed due to the indentation. If we assume thatall of the sensing points have a similar resistance Rs over the

544 K. Park et al. / Sensors and Actuators A 295 (2019) 541–550

Fig. 2. (a) Schematic diagram of the system including the sensor, multiplexer, amplifier, and DAQ system. (b) Sensor prototype (16 × 16 array, 160 mm × 160 mm × 8 mm).

Fig. 3. (a) Crosstalk current through the floated electrodes (red: the crosstalk current, blue: the resistances correspond to each sensing point, green: the leakage resistanceb (c) Schi to th

Ce

R

beFtv

V

etween adjacent electrodes). (b) Crosstalk current through the leakage resistance.

nterpretation of the references to colour in this figure legend, the reader is referred

NT-coated porous PDMS, the total resistance for the same rowlectrodes is

row (i) =

⎛⎝ N∑

j=1

(1

Rs (i, j)

)⎞⎠

−1

ecause these resistors are connected in parallel and the end of thelectrodes are connected to the inverting amplifier, as shown inig. 3-(c). Additionally, the resistances Rrow are connected throughhe leakage resistances Rleak, as shown in Fig. 3-(c). Therefore, the

oltage applied to the i-th row electrodes is

d(i) =(

Rtotal(i)Rmux + Rtotal(i)

)Vin

eme of the voltage circuit including the internal resistance of the multiplexer. (Fore web version of this article.)

where Rtotal(i) is the total resistance between the i-th row electrodeand the imaginary ground of the inverting amplifier. The aboveequations indicate that the applied voltage decreases and fluctu-ates as Rtotal(i) decreases. This problem becomes worse for a largearray, because the value of Rleak decreases as the size of the sensorincreases. Therefore, to fundamentally solve the interference prob-lem, the structure of the sensor should be optimized to reduce theleakage resistance of the sensor array.

3.2. Design parameter study

We propose a design to reduce the interference of the sensorarray, which has grooves among the adjacent electrodes of thesame surface. The shape of the proposed structure and an equiva-

K. Park et al. / Sensors and Actuators A 295 (2019) 541–550 545

Fig. 4. (a) Proposed structure for interference reduction (purple: the column directional electrodes, blue: the resistance of the sensing point, green: the leakage resistance,yellow: the row directional electrodes). (b) Cross-section of the structure and its normalized design parameters (�D , �W , and �T ). (c) Equivalent resistor network model(purple: the column directional electrodes, blue: the resistance of the sensing point, green: the leakage resistance, yellow: the row directional electrodes). (For interpretationof the references to colour in this figure legend, the reader is referred to the web version of this article.)

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ig. 5. The simulation results with different design parameters. (a) The relationshiphe normalized width of the groove and Rleak/Rs . (c) The relationship between the

ent simple resistor network model are shown in Fig. 4. The groovetructure reduces the unintended connection between the adjacentlectrodes so that the leakage resistance Rleak is increased and thenterference is attenuated. We can also simplify the circuit configu-ation with the proposed structure, because the crosstalk currentsre sufficiently excluded with this structure. The mechanical inter-erence is also partially decreased due to the structure.

A finite element method (FEM) simulation was conducted tostimate the effect of the design parameters �D, �W , and �T as shownn Fig. 4-(b); these design parameters correspond to the normal-zed groove depth ( �D), the normalized groove width (�W ), andhe normalized thickness of the sensing point (�T ), respectively.he simulation was performed by varying one design parameterhile other parameters were fixed. The shape of the mesh and other

arameters, such as the base conductivity and contact resistance,ere selected based on the real sample (CNT-coated porous PDMS).

he mesh model was generated by Netgen, and the simulationas solved by EIDORS, a MATLAB library for electrical impedance

omography [39]. In this parameter study, a large deformation ofhe sensor was not considered. The simulation results are shownn Fig. 5, and Rleak/Rs is plotted on a log scale with respect to thehange in the design parameters.

The results show that Rleak/Rs increases along with �D and �W ,hich means that the interference can decrease as the groove

ecomes larger. In contrast, Rleak/Rs decreases along with �T , indi-ating that the interference can increase if we make a thick origh-spatial-resolution sensor array. In other words, the inter-

erence can be low when the �T is sufficiently small. Therefore,

nterference reduction is only needed for a thick sensor.

In this study, it was not easy to make the sensor thin enough dueo the transduction mechanism of the CNT-coated porous PDMS;

een the normalized depth of the groove and Rleak/Rs . (b) The relationship betweenlized thickness of the sensing point and Rleak/Rs .

the sensor should be thick compared to the size of the pores. Theresistance change becomes unpredictable if the sensor is too thin.The size of the pores could not be reduced below a certain level dueto a limitation of the fabrication process. As a result, we neededto apply the structure proposed for interference reduction to thesensor to utilize the CNT-coated porous PDMS, which allows thesensor to achieve low interference even though thick CNT-coatedporous PDMS is used as the pressure-sensitive material.

To validate the result of the parameter studies, we comparedthe simulation result with the samples that had three electrodesand the same design parameters as those shown in Fig. 6. The baseconductivity and contact resistance were selected to represent thesamples. The resistance of the sample was measured for all com-binations of the electrodes, and Rleak/Rs was calculated using astar-delta circuit equivalence. The results are also shown in Fig. 6,which reveal that the simulation result is similar to the actual dataobtained from the samples. As a result, the results of the parameterstudy can be used to design the array sensor.

4. Sensor fabrication

The fabrication process of the conductive coated porous elas-tomer is divided into four parts: molding a sugar template, makinga structured porous elastomer, coating the porous elastomer witha conductive coating solution, and installing the fabric electrodes.The overall fabrication process is shown in Fig. 7. First, we moldedthe sugar template to have grooves on the surface, and the sugar

template was used as a sacrificial layer. Sugar and water weremixed with a mass ratio of 15:1 using a spray, and the mixture waskneaded and molded. The space occupied by the slits of the moldbecomes the groove of the sensor. Then, the mixture was baked at

546 K. Park et al. / Sensors and Actuators A 295 (2019) 541–550

Fig. 6. Validation of the parameter study using samples with the same design parameters. (a) CNT-coated porous PDMS sample (�D = 0.5, �W = 0.066, and �T = 1.33). (b)Equivalent mesh model for the sample. (c) Equivalent resistor network model for the sample. (d) The relationship between �D (normalized depth of the groove) and Rleak/Rs .(e) The relationship between �W (normalized width of the groove) and Rleak/Rs . (f) The relationship between �T (normalized thickness of the sensing point) and Rleak/Rs .

Fig. 7. Fabrication procedure of the soft tactile sensor array. (a) Prepare the molds with grooves. (b) Fill the molds with kneaded sugars and bake the mold for 2 h at at ◦ ◦

40 mF Instal

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(

emperature of 70 . (c) Submerge the PDMS in sugar and cure the PDMS at 70 fororm a CNT-coated surface on the PDMS scaffold by using the CNT-IPA solution. (f)

temperature of 70 ◦ for 2 h and placed in a box with a desiccantor one day to remove the remaining moisture. The molds can berinted using a 3D printer (Dimension elite, Stratasys, USA) andllow the sensor to be customized for the curved surface of a robot.

PDMS (Sylgard 184, Dowcorning, USA) was used for the porouslastomer due to its ease of use. The PDMS base was mixed withhe curing agent at a ratio of 10:1, and the PDMS prepolymer wasoured into a box with the sugar template. Then, the box was placed

n a vacuum chamber to allow the PDMS to permeate through theugar template. Next, the PDMS pre-polymer was cured at a tem-erature of 70 ◦ for 40 min. After the curing process, the PDMS layer

as detached from the outside of the molds to expose the sugar,

nd the sugar was dissolved in water.The coating solution was prepared by dispersing the MWCNTs

CM-280, Hanwha Inc., Korea) in isopropyl alcohol (IPA). The IPA

in. (d) Detach the PDMS layer from the molds and dissolve the sugar in water. (e)l the fabric electrodes on the CNT-coated porous PDMS.

and MWCNTs were mixed with a mass ratio of 0.025% and soni-cated for 1 h using a tip sonicator (VCX-505, Sonics and materialsInc. USA). Finally, the solution was mixed again using a vortexmixer (VM-10, Daihan scientific, Korea) for 5 min. To dip-coat theporous PDMS, the porous PDMS was placed in a basket, and theCNT-dispersed solution was poured onto it. Next, the porous PDMSwas pressed with a roller to allow the CNT-dispersed solution topermeate into the porous PDMS. Then, the soaked PDMS was driedin a fume hood to evaporate the IPA, and a conductive surface wasformed. This coating process was repeated several times until thedesired resistance was obtained. Finally, CNT-coated porous PDMS

was obtained with the structure proposed for interference reduc-tion.

The electrodes were made with mesh-type conductive fabric(2611, Statex, Germany). The conductive fabric was cut into strip

K. Park et al. / Sensors and Actuators A 295 (2019) 541–550 547

ship between compression and resistance. (c) The result of the repeatability test.

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Table 1Hysteresis of the conductive coated porous elastomer.

Frequency Hm (mechanical) Hp (piezoresistive)

0.01 Hz 13.4 % 3.6 %0.1 Hz 18.6 % 4.6 %

Fig. 8. (a) The relationship between compression and stress. (b) The relation

hapes and placed on the surface of the CNT-coated porous PDMS.ext, conductive ink (Electric paint, Bare conductive, UK) wasasted on the electrodes to connect the fabric electrode to the CNT-oated porous PDMS. Then, the connection was passivated withilicone rubber (Eco-flex 0030, smooth-on, USA). The resistancef the conductive fabric can be neglected because its conductiv-

ty (average = 1˝/sq) is much higher than that of the CNT-coatedorous PDMS. In addition, this fabric shows a very low Young’sodulus in a certain strain range due to its woven structure, so

he electrodes are not detached from the material even though thexternal force is applied to the electrodes directly.

. Sensor characteristics

.1. Material characteristics

A cyclic loading experiment was performed to investigate theharacteristics of the CNT-coated porous PDMS. The size of the sam-le (cube) was 15 mm × 15 mm × 8 mm, and the conductive fabriclectrodes were attached on both sides. The experimental setuponsists of an extensometer and a DAQ system. The resistance, com-ression, and force were recorded while the sample was pressederiodically. The compression frequency of each session was var-

ed from 0.01 Hz to 2 Hz. The relationship between compressionnd stress is shown in Fig. 8-(a). The result shows that the modulusf elasticity was small during the early stage of compression. This

s because the column of the porous structure was bent instead ofeformed with a barreling effect. The compression-resistance rela-ionship is also shown in Fig. 8-(b). The results show that the changen the resistance is linearly proportional to the compression whenhe compression is less than 50%. However, this relationship satu-ates as the material is compressed because the resistance cannote changed when all the pores are closed. The saturated curve ishown in the Supplementary material. The repeatability was alsonvestigated by pressing the sample at a rate of 0.01 Hz for approx-mately 7 h. Even after the first cycle, the initial resistance of theensor did not change much (approximately 4% of the initial resis-ance), and the relationship between compression and resistancelso did not change much. The initial resistance drift was recoveredithin a few minutes.

The mechanical hysteresis Hm is defined as the ratio betweenhe input work and the loss work during the loading cycle as shownelow.

m (%) = 100*Wload − Wunload

W, Wload

load

=∫ xmax

0

Fload dx, Wunload =∫ 0

xmax

−Funload dx

1 Hz 21.7 % 6.4 %2 Hz 20.4 % 6.8 %

The results reveal that the mechanical hysteresis Hm increasesup to 21.7% as the compression frequency increases. The overalllevel of the mechanical hysteresis is less than that of bulk PDMSdue to the porous structure.

The piezoresistive hysteresis Hp is also quantified by comparingthe areas under the loading curve and unloading curve as below.

Hp (%) = 100*∣∣∣Aload − Aunload

Aload

∣∣∣ , Aload

=∫ xmax

0

�Rload dx, Aunload =∫ 0

xmax

−�Runloaddx

As the loading frequency increases, the piezoresistive hysteresisincreases up to 6.8%. The hysteresis is also analyzed, and the resultsare summarized in Table 1.

5.2. Interference characteristic

A one-point indentation experiment was performed to inves-tigate the interference of the sensor array with the experimentalsetup shown in Fig. 9. The load cell (651AL, KTOYO, Korea) and the3D-printed indentation tip are installed on a 3D stage (EzROBO-5GX, Iwashita Engineering, Japan), and the sensor is placed on the3D stage. The sensor has a total of 256 sensing points, and thedimension of each sensing point is 10 mm x 10 mm x 8 mm. Theresistances of each sensing point were measured at a frequency of60 Hz, while the sensing point was indented at a speed of 0.1 mm/s.To investigate the effect of the structure proposed for interferencereduction, we conducted experiments for each sensor with andwithout the grooves; a comparison of the results is shown in Fig. 9.The result was cropped into a 7 × 7 image around the indentedsensing point (0,0). The interference at the point (i, j) resultingfrom the indented point (m, n) is defined as the ratio between thenormalized resistance change of the sensing point (m, n) and thenormalized resistance change of the sensing point (i, j).

I(i, j) = 100*

(�Rs(i, j)Rs,0(i, j)

)/

(�Rs(m, n)Rs,0 (m, n)

), when (i, j) /= (m, n)

548 K. Park et al. / Sensors and Actuators A 295 (2019) 541–550

Fig. 9. (a) Indentation experimental setup (sensor on the 3D stage). (b) Indentation tip and load cell of the 3D stage. (c) Interference result with grooves. (d) Interferenceresult without grooves. (e) Circular indentation (left: stamp, right: output image). (f) Cross-shaped indentation (left: stamp, right: output image).

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tCmhr

hen the sensor has no grooves, the interference level wasp to 92% for adjacent locations because the supplied voltagesecreased due to the leakage resistance. This interference con-inuously appeared along the column direction. In contrast, thenterference level was approximately 4% for adjacent sensing points

hen there were grooves on the sensor. The simulation estimatedhat the interference between adjacent sensing points was lesshan 5%, so the interference was effectively attenuated. However,he interference level increased from 4% to 25% as the sensoras strongly indented because the adjacent sensing points were

lso deformed due to the indentation. Since the sensor is madeith a soft material, these mechanical interferences were unavoid-

ble due to the compliance of the material itself. However, thisesult is still a considerable improvement for the sensor arrayecause the interference levels are less than 5% of those of theonadjacent sensing points even though the indented point is fullyompressed.

If the developed sensor is used in an actual environment, theensor will be pressed over a large area instead of being indented atne point; thus, we also conducted an experiment with a large-area

ndentation with stamps of specific shapes. The stamps used in thexperiments were circular and cross-shaped. The actual stamps,ressed location, and sensor output are also shown in Fig. 9. Theesults show that the shapes of the stamp were clearly recognizableven if the sensor was pressed over a large area. This means thathe interference of the sensor is considerably reduced by using theroposed structure, because if the interference is large, the output

mage (heatmap) will be distorted. Thus, the proposed sensor canuccessfully detect the forces applied over a large area.

. Conclusion

In this paper, we developed a tactile sensor array with low hys-eresis and low interference. To achieve low hysteresis, we utilized

NT-coated porous PDMS instead of a mixture-type piezoresistiveaterial. CNT-coated porous PDMS is known to exhibit a lower

ysteresis than a mixture-type piezoresistive material, because theesistance changes depending on the state of the contact between

the conductive surfaces inside the pores. Experimental results showthat the relationship between the force and resistance is linear atthe beginning of compression, but this relationship saturates whenthe sensor is fully compressed. The mechanical and piezoresistivehysteresis values were 21.7% and 6.8%, respectively. In addition, theinitial resistance of the sensor slightly increased when the sensorwas compressed, but it was observed that the initial resistance didnot change by more than 4% of its original value and recoveredto its original value within a few minutes. Since the nonlinear-ity and hysteretic behavior of the CNT-coated porous PDMS arepredictable and consistent, the behavior can be compensated by arecurrent neural network (RNN) or a hysteresis model such as thePrandtl-Ishlinskii model.

The interference of the sensor is caused by an unintended con-nection between adjacent electrodes and the internal resistanceof the multiplexing circuit. Some studies have tried to eliminatethe interference by changing the circuit configuration, but it wasnecessary to optimize the sensor structure for a more fundamen-tal solution. Therefore, we proposed a structure for interferencereduction that increases the leakage resistance by inserting groovesbetween adjacent electrodes. Before implementing the structure, itwas necessary to study how the leakage resistance would vary withthe design parameters, such as the depth and width of the grooves.Thus, a simulation was performed with respect to the normalizeddesign parameters �D, �W, and �T . The results revealed that theinterference decreases when the grooves are deep

(�D → 1

)and

wide(�W → 1

)and the sensor is thin

(�T → 0

). The grooved sensor

shows similar results to the simulation results, but the interferenceincreased as the sensor was compressed due to the large deforma-tion. Hence, the simulation can be improved by considering a largedeformation of the sensor.

In addition, the sensor can have an arbitrary 3D shape due tothe molding approach, so that the sensor does not need to be mod-ularized or stretched. The fabrication process is simple and easy

to follow, and the fabrication is also inexpensive. As a result, theproposed sensor exhibits low hysteresis and low interference andis expected to be easily applied for whole-body tactile sensing,wearable devices, and grippers.

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Technologies (KAIST), Daejeon, Republic of Korea, in 2012and 2017. He is currently a postdoctoral research fellow

K. Park et al. / Sensors and

cknowledgments

This research was supported by the Bio & Medical Technol-gy Development Program of the National Research FoundationNRF) funded by the Korean government (MSIT) (No. NRF-017M3A9E2063103)

ppendix A. Supplementary data

Supplementary material related to this article can be found,n the online version, at doi:https://doi.org/10.1016/j.sna.2019.06.26.

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Biographies

Kyungseo Park received his B.S. and M.S. degree in Dept.of Mechanical Engineering of Korea Advanced Institute ofScience and Technologies (KAIST), Daejeon, Republic ofKorea, in 2016 and 2018. He has been working towardshis Ph.D. degree at Korea Advanced Institute of Science andTechnology (KAIST). His research interests include wear-able robot, human-robot interaction, and soft robotics.

Seunghwan Kim received the B.S. in mechanical engi-neering from Sungkyunkwan University, Korea (2014),and M.S. in mechanical engineering from KAIST, Korea(2016). He is currently a doctoral student at KAIST. Hisresearch interests are flexible physical sensor, human-interface devices, electronic skin and wearable devices.

Hyosang Lee received his B.S. degree in Dept. of Mechan-ical Engineering of Korea University, in 2010. He receivedhis M.S. and Ph. D. degree in Dept. of Mechanical Engi-neering of Korea Advanced Institute of Science and

in Max Planck Institute for Intelligent Systems, Stuttgart,Germany. His research interests include soft tactile sen-sors, human-robot interactions.

5 Actuat

2003. He has joined the department of mechanical engi-neering in KAIST at 2004 and is currently a professor

50 K. Park et al. / Sensors and

Inkyu Park received his B.S., M.S., and Ph.D. from KAIST(1998), UIUC (2003) and UC Berkeley (2007), respec-tively, all in mechanical engineering. He has been withthe department of mechanical engineering at KAIST since2009 as a faculty and is currently an associate professor.His research interests are nanofabrication, smart sen-sors, nanomaterial-based sensors and flexible & wearableelectronics. He has published more than 60 international

journal articles (SCI indexed) and 100 international con-ference proceeding papers in the area of MEMS/NANOengineering. He is a recipient of IEEE NANO Best PaperAward (2010) and HP Open Innovation Research Award(2009–2012).

ors A 295 (2019) 541–550

Jung Kim received his B.S. and M.S. degree from theDept. of Mechanical Engineering of Korea Advanced Insti-tute of Science and Technologies (KAIST), Korea, in 1991and 1993, respectively. He also holds a Ph. D. degree inmechanical engineering from Massachusetts Institute ofTechnology (MIT), Cambridge, USA which he earned in

in the same department. His current research interestsinclude medical robotics, haptics, biomechanical signals,and assistive robotics.