Image Analysis For Deformation Behavior Of Optical

Based Silicone Tactile Sensor

Abdul Halim Esa, Muhammad Azmi Ayub

Faculty of Mechanical Engineering

Universiti Teknologi MARA (UiTM)

40450 Shah Alam, West Malaysia

abdhalim85@gmail.com

muhammadayub@salam.uitm.edu.my

Bakri Ali

Faculty of Mechanical Engineering

Universiti Teknologi MARA (UiTM),

13500 Permatang Pauh, West Malaysia

bakali65@yahoo.co.uk

Abstract – This paper presents a tactile sensor which is made

of a silicone based material. The tactile sensor is designed

similarly like a human finger. The hollow space inside the tactile

sensor is marked at the ‘finger tip’ inner side to sense any

deformation when force is apply outside the ‘finger tip’. The

force is apply by using micrometer tip . A CCD camera is

connected to a fiberscope and the fiberscope is connected to the

tactile sensor to ‘see’ the deformed image inside the silicone

dome. Several images is captured. The captured image is

analyzed by a WiT image processing algorithm. Based on the

processed images, the result is analyzed and the deformation

behavior is studied.

Keywords – Optical based sensor, tactile sensor, image

analysis, deformation behavior.

I. INTRODUCTION

Tactile sensor is a type of sensor that sense any physical properties and characteristics through contact with objects at

any parts or section. This sensory device is an essential device

to integrate with robot control system specifically in object

manipulation task. [1]

To date, common several basic tactile sensing principle are

using capacitive sensor, piezoelectric sensor, inductive sensor,

opto-mechatronic and piezoelectric sensor as their basic

sensing principle. Massachusetts Institute of Technology

(MIT) research team has developed sensor with a protruding

shape that allows them to easily make contact with the world in a similar way to ridges of human fingerprint. The sensor can

estimate the magnitude and direction of applied forces with

great sensitivity by measuring the deformation of compliant

dome.

To perform the object manipulation tasks effectively for

robot system, at least two types of tactile information is

required which is contact sense and slippage. To define

contact sense, normal force by means of static tactile sensing

is measured. To define slippage, shear force by dynamic

tactile sensing is measured. Therefore the tactile sensor system

is able to measure force at three axes direction [2]. Nagoya University research team has developed a novel optical three

axes tactile sensor system based on an optical waveguide

transduction method capable of acquiring normal and shear

force [3]. In order to help surgeon to determine the health of the tissue, Fath El Bab et al (2009) uses information from a

miro-machined piezoresistive type tactile sensor to detect

reciprocal of stiffness of a soft tissue [4]. A capacitive type

tactile sensor using copper clad laminated with flexible

polyimide substrates is fabricated by Anastasios Petropoulus

et al (2009) [5]. A tactile sensor based on tridimensional

piezoelectric aluminium nitride (AIN) membranes is proposed

by Tobias Polster et al (2009) [6]

Most of the sensors using piezoelectric, piezoresistive and

capacitive sensing technique only describe the magnitude of the force and hardness of the object and cannot react to force

changes and also can’t determine the direction of the forces.

Waveguide transduction method technique can react to the

forces and direction changes. That is why this method is more

convinced than other method. However, its individual

protruding column feeler is very small about 6 mm and will be

easily damage when handled roughly and harshly. All the

mostly using piezoelectric, piezoresistive and capacitve based

principle.

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II. EXPERIMENTAL TEST RIG

The tactile sensor as in Figure 1 is designed and tested with

Cosmoexpress simulation software [7]. The test rig as in

Figure 2 is designed, fabricated, and tested by first author. To

verify the theory [8], preliminary experiment is already carried

out to verify the theory [9].

Figure 1 Silicone tactile sensor

As shown in Figure 2. The test is consists of a rectangular

block, U clamper, micrometer clamper, micrometer rod and

tactile sensor. The material used for the rectangular block and

U clamper are mild steel. Mild steel is selected because to

ensure the test rig is stable and not easily move in either X and

Z axes direction as mild steel is heavy enough to sustain any

little movement.

Figure 2 Experimental test rig

III. EXPERIMENTAL SET-UP AND PROCEDURE

Figure 3 shows a complete experimental system setup while

Figure 4 shows a schematic diagram of complete system setup

with each device is labeled respectively.

Figure 3 Experimental system set-up

.

Figure 4 Schematic diagram of experimental system set-up

Rectangular block

Image processing

software

Micrometer rod

Micrometer clamper

U clamper

Y

X

Tactile sensor

CCD Camera

Fiberscope

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The tip of silicone tactile sensor is adjusted to the tip of

micrometer rod until it both of it slightly touched each other.

The image is captured. The image is shown in Figure 5.

Then, the micrometer rod is adjusted to advance 0.5mm

toward the tip of silicone tactile sensor as normal force is

applied until it is deflected. The image is captured.

Figure 5 Image at 0.0mm micrometer rod advancement.

The step is repeated for 1.0mm, 1.5mm and so on until the

micrometer rod advancement reach 6.0 mm. The final image

captured is shown in Figure 6.

Figure 6 Image at 6.0 mm rod advancement.

IV. IMAGE PROCESSING

Images taken at inner side of silicone tactile sensor are

processed using image processing algorithm which is

developed in this research project. The algorithm is developed

to enchance the image until the centroids of each marking is plotted precisely. In this study, WiT software from Dalsa

Technologies has been used to develop the computer

algorithm of image processing.

Figure 5 shows that the image inside the silicone tactile

sensor. This image showed inside marking of silicone tactile

sensor which is there are no force applied from the micrometer

rod. This image is made as reference image. The algorithm

developed as in Figure 7 is applied to this reference image,

resulting the image is enhance as in Figure 8. Figure 8 showed

centroids each of the markings is plotted marked as number 1

to number 8. The numbering is automatically marked by the algorithm. Then the data is appear as shown in Figure 9.

Figure 7

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Figure 8

This image processing is repeated for each picture with

micrometer advancement increase at 0.5mm at each step until

the total advancement reach 6.0mm. Then all the data is as in

Figure 9 is collected and analyzed.

Figure 9

Please note that the data in Figure 9 is numbered from number

0 to number 7 and the plot in Figure 8 is numbered from

number 1 to number 8. In the result section later, the

numbering that will be use is number 1 to number 8, not from

number 0 to number 7. The table will be label as P1 (Point 1)

to P8 (Point 8).

Point 0 is the centre of the images or label as P0 as showed in

Figure 10.

Figure 10

V. EXPERIMENTAL RESULTS AND DISCUSSION

The result is tabulated in Table 1 to show the displacement for

each deflection. From table, the displacement is calculated by

using the formula below:

∆X0i = X0i – X00 and

∆Y0i = Y0i – Y00, where

∆X0i = ith X coordinate displacement

X0i = X coordinate for ith deflection

X00 = X coordinate without any deflection

∆Y0i = ith Y coordinate displacement

Y0i = Y coordinate for ith deflection

Y00 = Y coordinate without any deflection

Where 1 ≤ i ≤ 12

Table 1 Deflection values for every X and Y coordinate for

centre point or Point 0, P0

No

(i) δ P0

mm X0 Y0 ∆X0 ∆Y0

0 0.0 366 298 0 0

1 0.5 376 309 10 11

2 1.0 372 314 6 16

3 1.5 366 324 0 26

4 2.0 351 333 -15 35

5 2.5 349 357 -17 59

6 3.0 347 368 -19 70

7 3.5 350 386 -16 88

8 4.0 306 384 -60 86

9 4.5 312 400 -54 102

10 5.0 295 413 -71 115

11 5.5 302 391 -64 93

12 6.0 292 415 -74 117

The movement of coordinates is plotted in Figure 11

Centroid Marking

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Figure 11 Displacement of centre P0 VS Deflection graph

It can be seen that the X coordinates is displace to the positive

X direction (right) for the 1st deflection. Then it deflect to the

negative X direction (left) until 8th deflection. At last the X

coordinate is displace sinusoidal to the right and to the left.

For the Y coordinates, it displace to the positive Y direction

(bottom) until 8th deflection and then not consistently displace

to the bottom and to the top (negative Y direction).

No (i)

δ P1 P2 P3 P4

mm X1 Y1 ∆X1 ∆Y1 ∆R1 X2 Y2 ∆X2 ∆Y2 ∆R2 X3 Y3 ∆X3 ∆Y3 ∆R3 X4 Y4 ∆X4 ∆Y4 ∆R4

0 0.0 374 129 8 -169 169 286 162 -80 -136 158 461 193 95 -105 142 235 267 -131 -31 135

1 0.5 383 133 7 -176 176 292 168 -84 -141 164 473 199 97 -110 147 239 276 -137 -33 141

2 1.0 379 131 7 -183 183 285 167 -87 -147 171 472 198 100 -116 153 229 279 -143 -35 147

3 1.5 374 132 8 -192 192 275 170 -91 -154 179 470 201 104 -123 161 217 286 -149 -38 154

4 2.0 358 131 7 -202 202 255 172 -96 -161 187 459 201 108 -132 171 198 294 -153 -39 158

5 2.5 351 142 2 -215 215 245 187 -104 -170 199 461 213 112 -144 182 189 316 -160 -41 165

6 3.0 338 139 -9 -229 229 229 193 -118 -175 211 458 209 111 -159 194 178 331 -169 -37 173

7 3.5 328 146 -22 -240 241 217 208 -133 -178 222 458 211 108 -175 206 172 355 -178 -31 181

8 4.0 296 170 -10 -214 214 196 222 -110 -162 196 407 236 101 -148 179 152 351 -154 -33 157

9 4.5 301 182 -11 -218 218 200 235 -112 -165 199 415 249 103 -151 183 155 364 -157 -36 161

10 5.0 283 186 -12 -227 227 179 241 -116 -172 207 401 256 106 -157 189 136 374 -159 -39 164

11 5.5 293 177 -9 -214 214 193 228 -109 -163 196 405 244 103 -147 179 149 356 -153 -35 157

12 6.0 279 189 -13 -226 226 176 244 -116 -171 207 397 257 105 -158 190 134 377 -158 -38 163

No (i)

δ P5 P6 P7 P8

mm X5 Y5 ∆X5 ∆Y5 ∆R5 X6 Y6 ∆X6 ∆Y6 ∆R6 X7 Y7 ∆X7 ∆Y7 ∆R7 X8 Y8 ∆X8 ∆Y8 ∆R8

0 0.0 507 285 141 -13 142 264 373 -102 75 127 447 393 81 95 125 358 439 -8 141 141

1 0.5 520 293 144 -16 145 270 385 -106 76 130 459 407 83 98 128 367 453 -9 144 144

2 1.0 521 296 149 -18 150 262 391 -110 77 134 456 413 84 99 130 362 457 -10 143 143

3 1.5 521 302 155 -22 157 253 402 -113 78 137 456 425 90 101 135 357 473 -9 149 149

4 2.0 515 307 164 -26 166 238 413 -113 80 138 449 437 98 104 143 346 485 -5 152 152

5 2.5 520 323 171 -34 174 234 437 -115 80 140 454 460 105 103 147 348 508 -1 151 151

6 3.0 525 322 178 -46 184 232 453 -115 85 143 462 470 115 102 154 354 522 7 154 154

7 3.5 534 327 184 -59 193 235 478 -115 92 147 476 483 126 97 159 366 540 16 154 155

8 4.0 476 339 170 -45 176 203 467 -103 83 132 424 478 118 94 151 322 531 16 147 148

9 4.5 483 354 171 -46 177 207 481 -105 81 133 430 493 118 93 150 326 544 14 144 145

10 5.0 474 364 179 -49 186 192 492 -103 79 130 420 506 125 93 156 314 555 19 142 143

11 5.5 472 348 170 -43 175 199 473 -103 82 132 419 486 117 95 151 317 537 15 146 147

12 6.0 471 366 179 -49 186 189 495 -103 80 130 417 508 125 93 156 312 557 20 142 143

Table 2 Change of radius values for X and Y coordinate for Point 1 (P1) until Point 8 (P8) at difference deflection

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As shown in table 2, the change of radius of each point at

each deflection also calculated based trigonometry formula;

∆XPi = XPi – X0i,

∆YPi = Ypi – X0i,

∆RPi = Change of radius of ith deflection,

∆XPi = Change of X coordinate at point P of ith deflection,

∆YPi = Change of Y coordinate at point P of ith deflection, XPi = Coordinate of point P at ith deflection,

YPi = Coordinate of point P at ith deflection,

X0i = X coordinate of P0 at ith deflection,

Y0i = Y coordinate of P0 at ith deflection,

Where 1 ≤ p ≤ 8 and 1 ≤ i ≤ 12

Figure 12 P1 to P8 change of radius VS Deflection Graph

All eight points is change almost in same pattern where the

change of radius in increase from 1st until 7th deflection. Then,

8th deflection onwards, the pattern show that the change of

radius is not consistently increase and decrease.

VI. CONCLUSION AND FUTURE WORK

This research presents the deflection behavior by using silicone tactile sensor. The deflection pattern is not consistent

since in the theory the deflection should linear to the force

applied. In this research, the deflection is consistent almost

third quarter along the micrometer advancement. For future

research, new test rigs will be develop to ensure absolutely no

movement in X and Z axes direction. In order to analyze a lot

of data, a lot of silicone tactile sensor composition samples

will be develop to collect more data. This is essential to make

sure the result can be compare to this paper result.

REFERENCES

[1] Bakri Ali, M. Azmi Ayub, H. Yussof. “Characteristics of a New

Optical Tactile Sensor for Interactive Robot Fingers”, International

Journal of Social Robotics, DOI: 10.1007/s12369-011-0129-4,

December 2011.

[2] H.Yussof, M. Ohka, H. Suzuki, N. Morisawa, J. Takata, “Tactile

sensing-based control architecture in multi-fingered arm for object

manipulation”, Engineering Letters, 16:2, EL_16_2_09, 2008.

[3] H. Yussof, M. Ohka, Y. Nasu, M. Yamano, J. Takata,”Low force

control scheme for object hardness distinction in robot

manipulation based on tactile sensing”, Proceedings of IEEE

International conference on robotics and automation, 2008,

Pasadena, USA.

[4] A.M.R Fath El Bab, K. Sugano, T.Tsuchiya, O. Tabata, M.E.H.

Eltaib, M.M Sallam, “ Micro machined tactile sensor for soft tissue

compliance detection,” Procedia Chemistry 1, 2009, pp. 84-87.

[5] Anastasios Petropoulos, Grigoris Kaltsas, Dimitrios Goustouridis,

Evangelos Gogolides, “A flexible capacitive device for pressure

and tactile sensing,” Procedia Chemistry 1, 2009, pp 867-870.

[6] Tobias Polster, Martin Hoffmann,” Aluminium nitride based 3D,

piezoelectric, tactile sensor,” Procedia Chemistry 1, 2009, pp. 144-

147.

[7] Bakri Ali, Rozaini Othman, Rasdi Deraman, Muhammad Azmi

Ayub, “ Deformation analysis of a silicone tactile

sensor,”International Conference on Robotics and Intelligents

Sensors, March 2010, Japan.

[8] Bakri Ali, Sukarnur, M. Azmi Ayub, “Development of

experimental test-rig for vision based tactile sensor”, International

Conference on Advances in Mechanical Engineering, June 2009,

Malaysia, pp.70.

[9] Bakri Ali, Rozaini Othman, Rasdi Deraman, M. Azmi Ayub,”A

new approach in design and operating principle of silicone tactile

sensor, “Journal of Computer Science, Volume 6, August 2010, pp/

940-945.

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