Sensors, Focus on Tactile,
Force and Stress Sensors

Sensors, Focus on Tactile,
Force and Stress Sensors

Edited byJose Gerardo Rocha
and
Senentxu Lanceros-Mendez

I-TechIV

Published by In-Teh

In-Teh is Croatian branch of I-Tech Education and Publishing KG, Vienna, Austria.
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First published December 2008
Printed in Croatia

p. cm.
ISBN 978-953-7619-31-2
1. Sensors, Focus on Tactile, Force and Stress Sensors, Jose Gerardo Rocha and Senentxu
Lanceros-Mendez

Preface
This decade has been called by many people as the decade of the sensors. With anenormous increase in the research and application of sensors in the last fifteen years, it canbe considered that a revolution similar to the one of microcomputers in the decade of 1980 isin course. In the last times, we have witnessed enormous advances in sensor´s technology
and more innovations are in the way. The sensitivity of the sensors is becoming higher, theirdimensions lower, their selectivity better and their price lower. Some issues remain
nevertheless constant: the basic principles used in the project of sensors and applications,once these principles are governed by the laws of the nature. However, through the times
our appreciation, knowledge and mastering of these same laws has changed.
Among the existing sensors to measure the most diverse quantities, the tactile and force
sensors are becoming more popular mainly, but not only, in the field of the robotic
applications, where the machines are instructed to execute tasks more and more similar tothe ones executed by human operators.
Tactile sensors are devices that measure the parameters related to the contact between
the sensor itself and a certain object. This interaction is restricted to a well defined andusually small region. In contrast, the force and torque sensors normally measure the total
forces and torques applied to an object.
Tactile sensors can be used to detect a wide range of stimulus: from the simple
identification of a contact with a given object to a complete tactile image giving information
on forces and shapes, for example. Usually, the active component of a tactile sensor iscapable to feel and measure several properties, like contact forces, texture, impact, sliding
and other contact conditions that can generate specific patterns of force and position. This
information can be used to identify the state of the object handled by a manipulator, that is,
its size, shape or if it is in the correct position, for example.
Once it does not exist a complete theory that describes the requirements of a robotic
system in terms of tactile information, most of the knowledge in this area is produced fromthe study of the human tactile sensors and the way humans grasp and handle. From thesestudies, the investigators concluded that the function of grasping within the incorporation oftactile feelings requires several sensors, namely force sliding and even temperatureknowledge. Moreover, the manipulator must have in its memory the right way to handle theobject, that is, it must know a priori which are the sensations produced by the object, inorder to handle it correctly.
This book describes some devices that are commonly identified as tactile or force
sensors. It is achieved with different degrees of detail, in a unique and actual resource, theVIdescription of different approaches to this type of sensors. Understanding the design andthe working principles of the sensors described here, requires a multidisciplinary
background of electrical engineering, mechanical engineering, physics, biology, etc. It has
been made an attempt to place side by side the most pertinent information in order to reacha more productive reading not only to professionals dedicated to the design of tactile
sensors, but also all other sensor users, as for example, in the field of robotics. The latest
technologies presented in this book, are more focused on information readout andprocessing: as new materials, micro and sub-micro sensors are available, wirelesstransmission and processing of the sensorial information, as well as some innovative
methodologies for obtaining and interpreting tactile information are also strongly evolving.
This book is organized in twenty four chapters. In the first chapters, someconsiderations concerning tactile sensors and the way they must operate, as well as someexamples of silicon sensors are presented. Then, tactile sensors of three and six axes aredescribed. Some of them can measure, beyond the force, the slip. After that, several flexible
sensors with anthropomorphous characteristics and with particularities resembling thehuman skin are reported. Finally, some methods of transmission and information
processing, namely wireless and with more or less elaborated algorithms are described.

December, 2008

Editors

Jose Gerardo Rocha
and
Senentxu Lanceros-Mendez

University of Minho,
PortugalContents
Preface
1. How tactile sensors should be?

V
001

Satoshi Saga

2. Torque Sensors for Robot Joint Control

015

Dzmitry Tsetserukou and Susumu Tachi

3. CMOS Force Sensor with Scanning Signal Process Circuit
for Vertical Probe Card

037

Jung-Tang Huang, Kuo-Yu Lee and Ming-Chieh Chiu

4. Three-Dimensional Silicon Smart Tactile Imager Using
Large Deformation of Swollen Diaphragmwith Integrated Piezoresistor Pixel Circuits

053

Hidekuni Takao and Makoto Ishida

5. High-Sensitivity and High-Stiffness Force Sensor Using
Strain-Deformation Expansion Mechanism

073

Yong Yu Takashi Chaen and Showzow Tsujio

6. High-Precision Three-Axis Force Sensor for Five-Fingered
Haptic Interface

087

Takahiro Endo, Haruhisa Kawasaki, Kazumi Kouketsu and Tetsuya Mouri

7. Optical Three-axis Tactile Sensor for Robotic Fingers

103

Masahiro Ohka, Jumpei Takata, Hiroaki Kobayashi, Hirofumi Suzuki,
Nobuyuki Morisawa and Hanafiah Bin Yussof

8. Measurement Principles of Optical Three-Axis Tactile Sensor
and its Application to Robotic Fingers System
Hanafiah Yussof, Jumpei Takata and Masahiro Ohka

123

VIII

9. Three Dimensional Capacitive Force Sensor for Tactile Applications

143

Jose Gerardo Rocha and Senentxu Lanceros-Mendez

10. Study on Dynamic Characteristics of Six-axis Wrist Force/torque Sensor

163

Ke-Jun Xu

11. Performance Analysis and Optimization of Sizable 6-axis Force Sensor
Based on Stewart Platform

205

Y. Z. Zhao, T. S. Zhao, L. H. Liu, H. Bian and N. Li

12. Grip Force and Slip Analysis in Robotic Grasp:
New Stochastic Paradigm Through Sensor Data Fusion

217

Debanik Roy

13. Development of Anthropomorphic Robot Hand with Tactile Sensor:
SKKU Hand II

253

Byung June Choi, Jooyoung Chun and Hyouk Ryeol Choi

14. Design of a Tactile Sensor for Robot Hands

271

Giorgio Cannata and Marco Maggiali

15. Tactile Sensing for Robotic Applications

289

Ravinder S. Dahiya and Maurizio Valle

16. Fast and Accurate Tactile Sensor System
for a Human-Interactive Robot305

Toshiharu Mukai, Shinya Hirano and Yo Kato

17. Development of a Humanoid with Distributed Multi-axis Deformation
Sense with Full-Body Soft Plastic Foam Cover as Flesh of a Robot

319

Marika Hayashi, Tomoaki Yoshikai and Masayuki Inaba

18. Research and Preparation Method of Flexible Tactile Sensor Material

325

Ying Huang, Min Wang, Huaili Qiu, Bei Xiang and Yugang Zhang

19. A Principle and Characteristics of a Flexible
and Stretchable Tactile Sensor Based on Static Electricity

341

Yasunori Tada, Masahiro Inoue, Toshimi Kawasaki, Yasushi Kawahito, Hiroshi
Ishiguro and Katsuaki Suganuma

20. Design Considerations for Multimodal “Sensitive Skins”
for Robotic Companions
Walter Dan Stiehl

353

IX

21. Compliant Tactile Sensors for High-Aspect-Ratio Form Metrology

377

Erwin Peiner

22. Tactile Sensor Without Wire and Sensing Element in the Tactile Region
using New Rubber Material

399

Yo Kato and Toshiharu Mukai

23. Recognition of Contact State of Four Layers Arrayed Type Tactile
Sensor by Using Neural Networks

409

Seiji Aoyagi

24. Tactile Information Processing for the Orientation Behaviourof Sand Scorpions
DaeEun Kim

431

16
Fast and Accurate Tactile Sensor System for a
Human-Interactive Robot
Toshiharu Mukai, Shinya Hirano and Yo Kato
Bio-Mimetic Control Research Center, RIKEN
Japan

1. Introduction
With the advent of the aging society, the demand for nursing care for the elderly is
becoming much larger. The application of robotics to helping on-site caregivers isconsequently one of the most important new areas of robotics research. Such humaninteractive robots, which share humans’ environments and interact with them, should becovered with soft areal tactile sensors for safety, communication, and dextrous
manipulation.
Tactile sensors have interested many researchers and various types of tactile sensors havebeen proposed so far. Many tactile sensors have been developed on the basis of microelectro-mechanical system (MEMS) technology (for example, (Suzuki, 1993; Souza & Wise,
1997)). They have a high-density and narrow covering area realized by applying MEMS
technology, and as a result, are not suitable for covering a large area of a robot’s surface.
Some tactile sensors suitable for use on robot fingers or grippers have also been developed(Nakamura & Shinoda, 2001; Yamada et al., 2002; Shimojo et al., 2004). Many of them havethe ability to detect tangential stress and can be used in grasping force control. Their main
target is robot fingers, and consequently they were not designed to cover a large area. There
are also commercially available tactile sensors such as those offered by Tekscan (Tekscan,
2008) based on pressure-sensitive ink or rubber, and KINOTEXTM tactile sensors (Reimer &Danisch, 1999) utilizing the change in the intensity of light scattered by the covering
urethane foam when deformed. However, they are not sufficiently accurate because ofstrong hysteresis and creep characteristics.
The idea of covering a large area of a robot’s surface with soft tactile skinlike sensors is
attracting researchers (Lumelsky et al., 2001). Some human-interactive robots for which alarge area of their surface is covered with soft tactile sensors have actually been developed(Inaba et al. 1996; Tajima et al. 2002; Kanda et al. 2002; Mitsunaga et al. 2006; Ohmura et al.,2006; Ohmura & Kuniyoshi, 2007). However, the tactile sensors are not suitable for humaninteractive robots, particularly when physical labor using tactile sensation is required. For
example, one tactile sensor in (Tajima et al. 2002) has only 3 values as its output, and anothertactile sensor in (Tajima et al. 2002) is gel-type and cannot be used over a long period
because of the evaporation of the contained water. The tactile sensor in (Mitsunaga et al.
2006) has only 56 elements in total. Flexible fabric-based tactile sensors using an electricallyconductive fabric have also been proposed for covering a robot (Inaba et al. 1996), but the306

Sensors, Focus on Tactile, Force and Stress Sensors

sensors are binary switches, and are difficult to fabricate. To our knowledge, the tactile
sensor used by (Ohmura et al., 2006) has been the most successful for covering a large areaof a robot’s surface. This tactile sensor is based on similar technology to KINOTEXTM, butuses tiny photoreflectors under urethane foam instead of the combination of light-emitting
diodes, photodetectors, and fiber-optic cables. The tactile sensor is fabricated on a flexible
substrate using photoreflectors and circuitry for driving and communication. Their sensor issuitable for detecting tactile contact, but the principle of their sensor depends on the
deformation of urethane foam, which inevitably causes strong hysteresis and creep
characteristics. Hence, when accuracy is needed, for example, when tactile feedback control
is required, we need more accurate tactile sensors.
For the realization of a robot with tactile sensation, a real-time acquisition and integration
system for gathering tactile sensor data distributed all over the robot’s body is also needed.
When a robot is covered with tactile sensors, the problems of huge computational load and alarge number of cables arise. Localized processing is an effective solution, and tactile sensors
with distributed processors have been developed. For example, the robot in (Tajima et al.
2002) had multiple MPUs connected by a serial bus, and that in (Ohmura et al., 2006) used a
network composed of local serial buses and a custom-designed ring-type network.
We are developing a robot named RI-MAN (Odashima et al., 2006; Odashima et al., 2007;
Mukai et al., 2008), shown in Fig. 1, with soft areal tactile sensors, as a platform for physicalhuman-robot interaction research. Our ultimate goal for RI-MAN is to help nurse elderly
people in their daily lives, and this inevitably involves performing hard physical tasks incomplex environments such as hospitals and homes. RI-MAN can physically interact withhumans via soft and whole-body interaction. Having a similar size to a human (158 cm inheight and 100 kg in weight) and a smooth surface without bumps, RI-MAN can performthe task of lifting up a dummy human in its arms. To skillfully perform such tasks thatinvolve physical contact with humans, RI-MAN is equipped with soft areal tactile sensors infive places, the chest and the right and left of the upper arms and forearms.

Fig. 1. RI-MAN with tactile sensors for physical human-robot interaction research
We have developed soft areal tactile sensors for RI-MAN by embedding semiconductor
pressure sensors as pressure-sensing elements in an elastic body (Mukai, 2004; Mukai, 2005),

Fast and Accurate Tactile Sensor System for a Human-Interactive Robot307

as well as their controllers that can realize localized processing and integration through the
network in a robot. Our primary target is the achievement of physical tasks using tactile
sensation, such as lifting up a human. Because semiconductor pressure sensors have little
hysteresis or creep, our sensors also have an accurate response, although the elastic bodycovering causes a little hysteresis and creep. The sensor should be able to detect wide rangeof pressure from light finger touch to the load of a human held by the robot arms. The
sampling speed and accuracy should be enough for usage in sensor feedback control. Ourtactile sensors satisfy the requirements for human-interactive robots.
In this paper, we report our tactile sensor, as well as its implementation in a robot. After thisintroduction, we first describe specifications necessary for tactile sensors in humaninteractive robots. Next we describe the structure and fabrication method of our tactile
sensor. Next we describe the implementation of the tactile sensor system in our robot RIMAN. Then we report experimental results of the sensor itself and sensor usage in the robot.
Finally we conclude our paper.

2. Specifications
In this research, we are aiming to develop soft areal tactile sensors that cover the surface of ahuman-interactive robot, and provide a pressure strength and distribution that can be used
to control the manipulation of objects. To make this possible, we need sensors that are soft
like human skin and can cover a large area of a robot’s curved surfaces, for safety andaffinity. We are developing such sensors by embedding small semiconductor pressure
sensors as pressure-sensing elements in an elastic body. The elastic body also contributes tothe removal of undesirable insensitive regions by giving interpolation ability to the sensor.
The preciseness of semiconductor pressure sensors can yield high-accuracy tactile sensors.
Considering the application of tactile sensors to human-interactive robots, we determined
the necessary specifications of our tactile sensor system as follows. First, we require a spatial
resolution of about 10 to 20 mm, referring to the approximately 10 mm resolution of thehuman palm and 40 mm of the human forearm. Except for the fingertips, this resolution is
sufficient to realize a resolution similar to that of a human. Next, we consider themeasurable pressure range. When a robot holds a person of 60 kg in its arms with a contact
area of 20×20 cm2, the average pressure is 14.7 kPa. Using a safety factor of 6, we require apressure range of 0 to 88 kPa. Next, we discuss the measurement resolution. Considering
feedback control using tactile sensation, we require a measurement resolution in which thecontact force caused by typical human-robot interaction is expressed by more than 5 bits.
We believe that feedback control is smooth if the value is expressed with this resolution.
Tactile sensors for robots require tactile sensor controllers suitable to be used in robots. It is
desirable that each controller be in the vicinity of the tactile sensor, with short connections
between sensors and controllers, because the connection requires a large number of cables.
This also reduces electric noise because tactile sensor output is analog, while we can use
digital signals for connections among controllers. This requires the following. Controllers
must be able to form a network for sensor data integration in the robot. Controllers must be
sufficiently small to fit in a robot. Controllers must calculate abstract compressed featuresfrom sensor data. Such compressed features are carried through a narrower bandwidth, tosimplify connection in robot and reduce the possibility of cable breakdown. We also requirethat the sampling speed be sufficiently fast for our robotic purposes. The sampling speed
depends on the performance of both the sensor and its controller, so that the total system308

Sensors, Focus on Tactile, Force and Stress Sensors

should be designed to satisfy this requirement. The sampling speed of sensor data and thecommunication speed among controllers should agree with the robot control period. It isempirically known that, for stable and smooth feedback control, the sampling frequency
should be more than 10 times the resonance frequency of the controlled object (Paul, 1981).
In general, robots have a resonance frequency of 1 to 50 Hz, so that the required sampling
frequency is 10 to 500 Hz, which corresponds to a sampling period of 2 to 100 ms (RSJ,2005).

3. Structure and fabrication method of the tactile sensor
3.1 Basic structure and components
As pressure-sensing elements, we adopted FUJIKURA FPBS-04A pressure sensors (Fig. 2).
These are very small (φ5.8 mm) piezoresistive semiconductor pressure sensors that can
detect absolute pressure between 42.6 and 434.7 kPa. Each sensor has a resistive bridge on
its diaphragm and the output changes almost linearly with the applied pressure.

Fig. 2. Small FUJIKURA semiconductor pressure sensors
To reduce the number of cables leading out from the tactile sensors, we designed a scanningcircuit, an example of which including 4x4 elements is shown in Fig. 3. By changing
switches, we can select a row and a column to obtain the output from the selected element.
In this example, the top-left element is selected by switching. All outputs of the pressuresensing elements are obtained by scanning this array. The actual circuit we made has anarray of 8x8 pressure-sensing elements with an 18 mm pitch. This pitch was determined tosatisfy the above requirement to realize a spatial resolution similar to a human. We
fabricated the circuit as a flexible printed circuit (FPC), so that it can be fit onto a 2D-curved
surface (which can be expanded into a 2D plane) because of its flexibility. We call the FPC
sheet with the pressure-sensing elements and other electronic parts as ‘sensor sheet’. To
mount it onto a free-curved surface (which cannot be expanded into a 2D plane), we
designed the circuit so that all the wiring is concentrated into a comb-shaped region. Thus,
the sensor sheet can be cut into a shape consisting of thin regions. After cutting, the sheet
can be wound onto a free-curved surface, as shown in Fig. 4, if the curvature is not too
sharp. In addition, we designed the circuit all of which wiring concentrates into a combshaped region, so that it works if the central part remains even when the marginal parts are
cut off. Therefore it can be applied to a smaller surface than the original sensor sheet. To
reduce cables, we also put analog switches and an instrumentation amplifier on the FPC. As
a result, the number of cables has become 10. As the instrumentation amplifier, we adopted
a digital amplifier that can select its gain from 1, 2, 4, and 8. If this amplifier gain needs to becontrolled, additional two cables are needed.

Fast and Accurate Tactile Sensor System for a Human-Interactive Robot

309

Fig. 3. Circuit of our tactile sensor

Fig. 4. Sensor sheet that can be cut into a comblike shape and wound on a curved surface
3.2 Method of fabricating a curved tactile sensor
To make the tactile sensors soft, we embedded the sensor sheet in an elastic body.
First, the sensor sheet is fixed after it is wound around the curved surface. Next, to remove
gaps between the shells of pressure-sensing elements, the gaps are filled with a plastic
material that hardens after the desired form is reached. Then, a small projection-shaped
piece of elastic material is placed on the diaphragm of each pressure-sensing element. After
that, an elastic sheet covers the above assembly. Fig. 5 shows a schematic of the structure of
our curved tactile sensor. We used paper clay to fill the gaps, liquid rubber to fabricate theprojection-shaped pieces, and a 5-mm-thick sponge sheet as the elastic sheet.

310

Sensors, Focus on Tactile, Force and Stress Sensors

Fig. 5. Schematic structure and a photo of our curved tactile sensor
We selected the material of the elastic projection-shaped pieces to be harder than the elastic
sheet. As a result, the small pieces push up against the elastic sheet, and the regions aroundthe pieces in the sheet are compressed and become denser than the other regions. Thus, hardand soft areas appear in the elastic sheet (Fig. 5), and this structure has an amplifying effect(Mukai, 2005). A photograph of our curved tactile sensor is also shown in Fig. 5.

4. Implementation of a tactile sensor system
We installed the tactile sensors in our robot RI-MAN in five places, the chest and the rightand left of the upper arms and forearms. Each sensor sheet has 8x8 elements, so that RIMAN has 320 pressure-sensing elements in total. To process enormous sensor data inrealtime in the vicinity of sensor, we developed a tactile sensor controller based on a dsPIC
board (Landmark LM517), a picture of which is shown in Fig. 6.

(a) Front and back view(b) Stacking with extension board

Fig. 6. dsPIC board for general sensing/controlling purposes
The dsPIC board is a general purpose sensing/controlling board developed by us, with a sizeof 35x50 mm2. It is equipped with a dsPIC (Microchip technology 30F6012A) as the CPU and a
USB interface IC (FTDI FT232RL) that realizes 1 Mbps communication. It also has many
connectors through which many pins can be accessed. It also has a stacking connector for an
extension board. The tactile sensor controller we developed uses a 12 bit A/D converter anddigital I/Os in the 30F6012A. Its program is written in the C language and downloaded in the
flash memory of the 30F6012A, as the firmware. The C program determines how to compress
data from a tactile sensor sheet into abstract features suitable for network communication.

Fast and Accurate Tactile Sensor System for a Human-Interactive Robot

311

Using this board, up to 1 ms sampling of 1 tactile sensor sheet can be realized. We also
developed an extension board for network communication, to connect the tactile sensors to
the network in our robot RI-MAN. It has a network IC (Step Technica MKY40) that realizes avirtual shared memory, the maximum size of which is 512 byte. The guaranteedsynchronization time of the virtual shared memory depends on the memory size, and is 1
ms for 256 byte and 2.4 ms for 512 byte. The extension board can be stacked with the dsPIC
board as shown in Fig. 6(b). The small size and the network communication ability of ourtactile sensor controller enable us to install them distributedly in the robot body. The
communication can be realized using only 2 cables, which largely simplifies wiring andreduces maintenance cost in the robot.
In the virtual shared memory space, each node occupies an area consisting of stations one ofwhich corresponds to 8 byte. In RI-MAN, various sensor controllers and motor controllers
are connected to the network and, as a result, the area that tactile sensors can use is limited.
In the current implementation, the host PC (with RT-Linux) occupies 1 station to sendcommands (for setting modes and parameters) through network to tactile sensors, and eachof 5 tactile sensor controllers occupies 3 stations.
Each tactile sensor has only 3 stations, corresponding to 24 byte, for communication, thus allof 8x8 sensor element values (which is expressed by 12 bit) cannot be transmitted
simultaneously. It is possible to send data line by line and combine them in the host PC toobtain whole output of one sensor sheet, but this takes unacceptable time (about 90ms) for
feedback control. So we determined to calculate geometric moments in local controllers andtransmit only the moments through network. The geometric moments are expressed, using
element value I xy at ( x, y ) , as follows.
Zeroth: M =
0

∑I

xy

x, y

First: M =x∑ xI , M = ∑ yI
yxy

Second: M

xy

xy

x, y

x, y

= ∑ xyI xy , M x2 − y 2 = ∑ ( x 2 − y 2 ) I xy
x, y

x, y

The zeroth moment is the total sum itself, and the centroids (center of pressure) can beobtained by dividing the first by the zeroth. Using up to the second moments, we can obtain
the axis of least inertia (Horn, 1986), which is the orientation of the object, as shown in Fig. 7.
In the controller using dsPIC, all of data acquisition and calculation finishes in 2 ms.

θ=(x, y)

1arctan( 2( M xy − M 0 x y ), ( M x 2 − y 2 − M 0 ( x 2 − y 2 ))2θAxis of least inertia

Fig. 7. The axis of least inertia

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Sensors, Focus on Tactile, Force and Stress Sensors

5 Experimental results
5.1 Basic performance of the sensor
We conducted experiments to investigate the basic performance of our tactile sensor system.
Flat tactile sensors with the 5-mm-thick elastic sheet were used to investigate the basic
performance. In experiments where a dynamic force was needed, the experimental setup
shown in Fig. 8 was used. The setup consisted of a digital force gauge, a load cell (Minebea
LSM-1K-B), a vibrator (Asahi SeisakusyoWaveMaker01), and an XY stage. The force gauge
was used to approximately measure the applied force to ensure that an excessive force was
not exerted. Actual measurement of the applied force was carried out using the load cell,which has higher accuracy. The vibrator was used to generate controlled dynamic motion,and the force was exerted using a rod with a circular tip with a diameter of 8 mm. In
experiments where a force over a wider area was needed, weights were used. However, in
this case, the force was limited to a static force. Outputs from pressure-sensing elements
were digitized by an A/D converter in the tactile sensor controller and sent to a PC throughUSB connection. These values are referred to as ‘sensor output’. The unit of sensor output
corresponds to 0.00122 V, and the sampling period of the measurement was 1 ms. The
amplifier gain of sensor sheets were fixed to 8 in all experiments.

Fig. 8. Experimental setupa) Response to a sinusoidal wave
First, we show, in Fig. 9, the measured time response of a pressure-sensing element (withthe covering sheet) along with the applied force, when vibrated with a 1, 10, or 100 Hz
sinusoidal wave. The force was applied from immediately above the element using the rod
with the 8 mm circular tip. We can see that the time response has a smooth sinusoidal shapeat 1 and 10 Hz, though the shape is slightly deformed at 100 Hz. A typical relationshipbetween the applied force and the sensor output at 1 Hz is shown in Fig. 10. The sensor
output is almost linear with the applied force. The solid line in the graph is the linear
approximation y = ax based on the results (from 3000 samples), where a = 13.35 in thiscase. This slope is referred to as gain in this paper. From this experiment, we can also seethat our sensor has satisfactory measurable range and measurement resolution discussed in
Section 2. When a force of 8 N was applied using the rod with the 8 mm circular tip, thepressure was about 159 kPa and the sensor output was more than 90. These results satisfy
the required maximum range of 88 kPa and 5 bit resolution.

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Fast and Accurate Tactile Sensor System for a Human-Interactive Robot

5

60

4

50
40

3

30

Applied force [N]

6

2
20
1

10
0
0

500

1000

60

7

58

80
6
70
5

60

4

50
40

3

30
2
20
1

10

0
2000

1500

8

0
0

50

100

Time [ms]

0
200

150

5

Sensor output
Applied force

4.6
4.4
4.2

54

4
52

3.8
3.6

50

3.4
48

3.2

46

3
0

5

Time [ms](a) 1 Hz

4.8

56

Applied force [N]80
70

Sensor output
Applied force

90

Sensor output (one element)

Sensor output (one element)

100

7Applied force [N]Sensor output
Applied force

90

Sensor output (one element)

8

100

10

15

20

Time [ms](b) 10 Hz(c) 100 Hz

Fig. 9. Response of a pressure-sensing element to sinusoidal force

Sensor output (one element)

100

80

60

40

20

y = 13.35x
0
0

2

4

6

8

Applied force [N]Fig. 10. Force vs sensor outputb) Variations of pressure-sensing elements
Next, we checked the variations of pressure-sensing elements on a sensor sheet. A
sinusoidal force of 1 Hz was applied from immediately above the element using the rod
with the 8 mm circular tip. The results of 20 elements are shown in Fig. 11. The standard
deviation is about 6.5% of the averaged gain. The gains varied partly because we manuallyfabricated the projection-shaped elastic pieces on the diaphragms. We expect that if wemake them by a more controlled method, the variation will decrease.
16
14

Gain at 1 Hz

12
10
8

Average:
12.31
Standard deviation: 0.800(n=20)

6
4
2
0
0

5

10

Element number

15

20

Fig. 11. Variations of elements on a sensor sheetc) Frequency response
The results of experiments to investigate frequency response are shown in Fig. 12. The output
was measured from a certain pressure-sensing element in a tactile sensor, and gain was
normalized to 1 at 1 Hz. The decrease of gain at 100 Hz is 3 dB and the phase delay is 20
degree, approximately. These results show that our sensor can detect high-frequency signals.

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Sensors, Focus on Tactile, Force and Stress Sensors

Fig. 12. Frequency response of a sensing elementd) Interpolation ability
Interpolation ability is obtained because of the covering elastic sheet even though discretepressure-sensing elements are located separately. This removes undesirable insensitive
region on the tactile sensor. Experimental results for verifying this effect are shown in Fig.
13. By applying a force using the rod with a tip diameter of 8 mm at a certain distance awayfrom the element, gains in the graph were measured. The gain was normalized to 1 at the
distance 0. The response shape agrees with the theoretically calculated values in (Shimojo,1997).
1

Gain

0.8
0.6
0.4
0.2
0
0

0.2

0.4

0.6

Distance from the element [taxel]

Fig. 13. Results of interpolation teste) Hysteresis and drift
The results of experiments for investigating hysteresis are shown in Fig. 14. A load of 6.75 N
approximately was applied and removed in about 5 s. Hysteresis exists but it is small. Next,
to see longer-term effect (drift), a 668 g weight with an area of 52x44 mm2 was placed on thesensor for 10 minutes. The sum of outputs from all elements is shown in Fig. 15. The output
reduced slightly but it is about 4% of the initial output.

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Fast and Accurate Tactile Sensor System for a Human-Interactive Robot
100
90

7

80

Sensor output (one element)

6

Load [N]

5
4
3
2
1

70
60
50
40
30
20
10
0

0
0

2000

4000

6000

0

8000

1

2

3

Time [ms]

5

6

7

8

Force [N](a) Time profile of applied force
Fig. 14. Results of hysteresis test
Sensor output (sum of all elements)

4-10(b) Force vs sensor output

160
140
120
100
80
60
40
20
0
0

2

4

6

8

10

Time [min]Fig. 15. Drift over 10 minutes
5.2 Tactile sensors in a robot
The output of all tactile sensors when holding a dummy human weighing 18 kg in its arms
is shown in Fig. 16. The size of each square represents the amplitude of the corresponding
tactile sensor element in log scale. This data were obtained and recorded in the host PC by

Fig. 16. Tactile sensor output when holding a dummy human weighing 18 kg

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Sensors, Focus on Tactile, Force and Stress Sensors

line-by-line transmission. The transmission took about 90 ms, but data acquisition itself in
local tactile sensor controllers finished in 1 ms.
Next, we investigated the relationship between the roll angle and the sensor output when
RI-MAN rotated its waist joint right and left 15 degrees while holding the 18 kg dummy
human (Fig. 17). The results are in Fig. 18, where the realized roll angle and the pressure
centroid on the left forearm are shown in graph (a), and the loads (the sum of all element
outputs) detected by all tactile sensors in graph (b). In the sensor coordinates, the x-axis isalong the left forearm from the base to the end, and the y-axis is from outside to inside. We
can see that tactile sensors succeeded in detecting the changes of the object load and position
caused by the roll angle change. The data show that the position of the dummy humanshifted little by little during the cycles, even though the waist angle repeated the same
motion.

+15 degrees

0 degrees-15 degrees

Fig. 17. Experiment scenes to obtain sensor output from a dummy human10

Roll angle [deg]

5

1800

4.9
4.7
4.5
4.3

0
0

5000

10000

15000

20000

25000

30000

35000
4.1

-5
3.9
-10

3.7

-15

3.5
Time [ms](a) Roll angle and the centroids on the left
forearm

Sensor output (Sum of all elements)

Roll angle
Centroid x
Centroid y

Sensor coordinates [taxel]

15

Right upper arm
Left upper arm
Chest

1600

Right forearm
Left forearm

1400
1200
1000
800
600
400
200
0
0

5000

10000 15000

20000 25000

30000

35000

Time [ms](b) Load on each tactile sensor

Fig. 18. Sensor output caused by a dummy human when waist angle is changed

7. Conclusion
In this paper, we described the successful development of the tactile sensor system of ourhuman-interactive robot RI-MAN. The necessary specifications for RI-MAN tactile sensors
are satisfied by our tactile sensor system. RI-MAN, equipped with the tactile sensors,
succeeded in detecting the magnitude and position of the load when it was holding adummy human.

Fast and Accurate Tactile Sensor System for a Human-Interactive Robot

317

For future work, we will develop control methods for manipulating objects with arms usingtactile sensor feedback. We will also develop sensor signal processing methods for detecting
not only physical contact but also human tactile sensations such as hitting and stroking. This
enables the tactile sensor to be used in human-robot communication, as well as in physicallabors.

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