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SHARIF UNIVERSITY OF TECHNOLOGY, INTERNATIONAL CAMPUS
RESEARCH BULLETIN
A Quarterly Publication of School of Science and Engineering
EDITOR IN CHIEF
Alireza Ghorshi
EDITORIAL BOARD
Masoud Askari, Sharif University of Technology,
International Campus
Habib Bagheri, Sharif University of Technology
Morteza Eskandari, Sharif University of
Technology, International Campus
Kambiz Ghaemi Osgouie, Sharif University of
Alireza Ghorshi, Sharif University of Technology,
Saeed Hashemi, Sharif University of Technology,
Mohsen Jahanshahi, Sharif University of
Mehran Jahed, Sharif University of Technology
Siamak Kazemzadeh Hannani, Sharif University of
Technology
Mohammad Khansari, Sharif University of
Amir Ali Khayyat, Sharif University of
Mohammad Taghi Manzuri, Sharif University of
Technology
Seyed Abolghasem Miremadi, Sharif University of
Technology
Seyed Mohammad Mortazavi, Sharif University of
Seyed Reza Mousavi, Sharif University of
Abolghasem Najafi, Sharif University of
Alireza Nemaney Pour, Sharif University of
Saeed Orangi, Sharif University of Technology,
Mohsen Sadighi, Sharif University of Technology,
Mahdi Sani, Sharif University of Technology,
Ali Selk Ghaffari, Sharif University of Technology,
Mohammad Reza Shams, Sharif University of
Hossein Shodja, Sharif University of Technology
Mohammad Ali Vesaghi, Sharif University of
Technology
Abolghasem Zabihollah, Sharif University of
Hossein Zaman, Sharif University of Technology,
Aims and Scope
The major objective of the bulletin of research is to archive the current and most recent research
activities of faculty members and post-graduate students of SUT-International Campus and to
distribute them in order to facilitate the communication of research outcomes between scholar public.
Basically, the papers that have already been published or accepted for publication in journals and
conferences are reviewed by editorial board and presented in the bulletin; however research high
quality original/unpublished papers are also welcomed.
The scope of the bulletin congruent with the graduate programs of the school is multi-disciplinary. It
covers analytical, numerical and experimental papers in the fields of Engineering and Science from
both industrial oriented aspects and leading edge research endeavours.
Disclaimer
Publication of papers in this particular research bulletin is for internal use only. It does not imply that
the editorial board and reviewers endorse the data and conclusions of authors.
CONTENTS
Civil Engineering
M.R. Nemati
M.H. Sadighiani
Interaction between Tunnel and Adjacent Structures Using a
Two-Dimensional Finite Element Analysis
1-5
The Design of a Low-Power High-Speed Current Comparator
in 0.35-μm CMOS Technology
6-11
Electrical Engineering
S. Ziabakhsh
H. Alavi-Rad
M. Alavi-Rad
M. Mortazavi
Information Technology
M. Khansari
H. R. Rabiee
M. H. Rohban
M. Ghanbari
On the Search Window Updating for Occlusion Handling in 12-16
Object Tracking Application
Materials Engineering
M. R. Shams
H. Pezeshki Modarres
Composite Particleboard Panels Made from Stone powderRice straw Properties are Experimented as a New
Construction Materials
17-20
R. Hortamani
A. Zabihollah
Modeling and Simulation of Graspers Force in Minimally
Invasive Surgery
21-25
F. Mohammadi
I. Hemmatian
K. Ghaemi Osgouie
Manipulability Analysis for Gimbal Driven Robotic Arms
26-31
Mechatronics Engineering
Research Bulletin
Vol. 1, No. 1, December 2009
Research Bulletin, Sharif University of Technology, International Campus, Kish Island, Vol. 1, No. 1, December 2009
Interaction between Tunnel and Adjacent Structures Using a Two-Dimensional
Finite Element Analysis
Mohammad R. Nemati, Mohammad H. Sadighiani
Abstract: This paper concerns a study of the interaction between tunneling and adjacent structures.
Analysis is performed using a full two-dimensional finite element model, which takes into consideration the presence of adjacent structure with regard to distance to tunnel and diameter of tunnel during
construction of the tunnel. The soil behavior is assumed to be governed by an elastic perfectly-plastic
constitutive relation based on Mohr-Coulomb criterion with a non-associated flow rule. The paper is
composed of two parts. However, compatibility of each method with beam and solid continuum element models in two dimensional finite element (FE) analyses was investigated. The first part describes
the numerical model used in this study. The two-dimensional analysis of the construction of a shallow
tunnel close to a multi-level building was conducted using the finite element program, ABAQUS. The
analyses include influence of effective parameters such as tunnel diameter, width of soil between tunnel crown and building foundation. The effect of construction stages of structures on the tunnel stability was also studied. Next, the results of analyses were compared quantitatively.
Keywords: Interaction; Plasticity; Structure; Two-dimensional; Tunnelling.
and investigated influences of building weight and
stiffness over tunnel deformation and the stress regime. It
would be more satisfactory to predict the measure which
minimizes the impact of the tunnelling works, before
planning a structure. However, this optimal situation is
hardly feasible both technically and economically due to
the uncertainties that remain at the design stage on the
ground response to tunnelling and the actual condition of
the buildings [6].
Current study is performed using a 2D finite element
analysis, which takes into consideration the elastoplastic
behaviour of the soil, the tunnelling procedure and the
presence of the structure. After a brief review of
numerical method, the first part addresses the 2D
analysis employed in the construction of a shallow tunnel
in the proximity of a 4-story building and compares the
influences of tunnel effective parameters. The last part
includes the investigation of the structure stages over
impressible parameter of tunnel. According to the results
of FE analyses, the best pattern among all patterns was
achieved with convergence-confinement method using
beam elements as shotcrete. Besides, its model predicted
the max settlement larger than the other methods [5].
1. INTRODUCTION
This paper presents a thorough 2D analysis related to
the interaction between tunnelling and adjacent structure.
This problem was previously analyzed using a
combination of in situ observations and numerical
modelling. Analysis of previous case histories paved the
way for the establishment of various empirical
relationships between tunnelling induced ground
movement and associated structure damage [1–3]. In this
paper, a study of the interaction between the construction
of a lined tunnel and adjacent structures is described.
This study is divided in to two parts: Structure
construction before tunnelling and Tunnelling before
structure construction. The first part addresses the
determination of tunnelling-induced ground movement
using empirical, numerical methods such as those
proposed by Peck [9], O’Reilly and New [8], Mroueh
and Shahrour [7]. The building response to tunnelling is
then determined in the second step by performing a
complete structural analysis of the building. It should be
mentioned Potts and Addenbrooke [10] used a coupled
2D finite element model to study the influence of a
surface structure on the ground movement caused by
tunnelling. Moreover, Franzius [4] verified their study
2. NUMERICAL MODELLING
__________
Figure 1 indicates the problem under consideration
which is used to quantify the interaction between tunnelling
proximity structure. The tunnel is characterized by its depth
Hb, diameter D, lining thickness t, while the building is
modelled by a spatial reinforced concrete framed structure
characterized by the level height H and column’s spacing as
S. The behaviour of the structure is assumed to be linearelastic. The soil behaviour is assumed to be governed by an
elastic perfectly-plastic constitutive relation based on the
Mohr–Coulomb criterion with a non-associative flow rule.
Manuscript has been presented at 2nd International Conference
on Computational Methods in Tunneling in 2009.
Mohammad Reza Nemati, M.Sc student, School of Science
and Engineering, Sharif university of Technology, International
Campus, Kish Island.
Mohammad H. Sadaghiani, Ph.D, Department of Civil
Engineering, Sharif University of Technology, Iran.
(Corresponding author to provide phone: +98-21- 66022727 Ext:
4228; fax: +98 -21- 66014828; e-mail: mhsadagh@sharif.edu).
1
Research Bulletin, Vol. 1, No. 1, December 2009
Figure 1 Tunneling–structure interaction: problem under consideration
ground surface (tunnel depth) grows from 9m to 24m, but
tunnel diameter is 9m for all of them. Of course, the
specifications and dimensions of the whole models are
changeless. Meantime, the structure construction is prior to
tunnel construction. Whereas, variation of mentioned
parameters effects over impressible parameters like as
surface settlements, tunnel deformations, plastic zones, axial
force of structure’s columns, structure’s beams
deformations and columns’ bending moments; therefore,
each impressible parameters are investigated separately in
the following section.
It is worth noting that such analysis can be improved by
employing a more realistic soil material constitutive relation,
which takes into account soil hardening and stressdependant elastic properties. Analysis of the tunnelling–
structure interaction problem is performed in two parts. The
first part is concerned with the determination of initial
stresses in the soil mass prior to the tunnel construction. The
second part deals with the numerical analysis for the
construction of the tunnel prior to the structure construction.
In this paper, numerical simulations were performed by
means of the finite element program ABAQUS which
provides flexible features for the analysis of 2D/3D and
non-linear soil–structure interaction problems.
3.2. Presentation of the example-second part
Here the stages of structure construction (the numbers of
building’s floor vary from 1 to 5) are developed during of
this study. On the other hand, the tunnelling is prior to
structure construction. However, the rest specification of
soil, structure and tunnel are remained constant for all cases.
As a matter of fact, the growth of floors influences
differently over the impressible parameters as surface
settlements, tunnel principal stresses, tunnel deformations
and plastic zones which are concerned in the following
sections. In addition, the entire analysis is performed in
drained condition. Computation is carried out in ten
successive steps for the structure construction and
excavation modelling.
3. 2D FINITE ELEMENT ANALYSIS
3.1. Presentation of the example-first part
Table 1 depicts all of specification of soil, structure
and tunnel especially the variable effective parameters
(diameter and depth) are wholly defined. Besides, the
thickness, elasticity modulus and Poisson’s ratio of
concrete lining are 50cm, 35000MPa and 0.2
respectively and also constant for both parts of this study.
Finite element analysis is carried out using the mesh
approximately between 16000 to 25000 elements, for
different cases. In order to simulate such a relative
movement interface elements are introduced in this study.
The concrete lining of tunnel is modelled as Timoshenko
beams with zero thickness.
For the first part of this paper the structure is a 4-story
building and the profiles of HE300 B and IPE240 are
selected for the columns and beams sections successively.
Tunnel excavation steps are modelled in two steps for
whole cases. Primary, the first effective parameters (tunnel
diameter) increases from 6m to 9m with constant tunnel
depth.
Lastly, the width of soil between tunnel crown and
4. TUNNELLING-STRUCTURE INTERACTIONPART ONE
4.1. Surface settlement, tunnel deformation and plastic
zones
Figure 2 presents surface settlements of tunnel for
both effective parameters. It should be noted when tunnel
depth of Hb=12m is constant and tunnel diameter increases from 6m to 9m, tunnel diameter of D=9m has
maximum settlement and is about 19mm. On the other
2
5. TUNNELING-STRUCTURE INTERACTION
PART-TWO
0
‐40
‐20
‐5 0
20
40
Settlement (mm)
‐10
‐15
The purpose of this section is to investigate about
impressible tunnel parameters, while tunnelling is prior
to the structure construction. Whereas, tunnel construction influence ground surface, therefore it is subsided
according Smax (Peck, 1969) [9], but it continues until
stages of structure are completed. However, tunnel diameter of D=9m and tunnel depth of Hb=9m are constant in the
whole steps. It should be noted that the growth of numbers
of building’s floors from 1-story to 5-story and subsequence
loading increases settlement from 3.5mm t0 17.4mm in
Figure 3. Furthermore, the principal tunnel stresses increases especially in the tunnels crown. On the other hand,
the growth of numbers of building’s floors from 1-story to
5-story increase tunnel deformation from 4.9mm to 16.3mm
in the tunnel crown and decrease from 5.3mm to 4.6mm in
the bottom of tunnel.
Lastly, the growth of numbers of building’s floors from
1-story to 5-story increase plastic zones in the tunnel circumference in Figure 4 (a) to 4 (e).
D=6m, Hb=12m
D7.5m, Hb=12m
D=9m, Hb=9m
D=9m, Hb=12m
D=9m, Hb=24m
‐20
‐25
‐30
‐35
Displacement of Centerline of Tunnel (m)
Figure 2 Comparison between settlements of different
tunnel diameter and depth
hand, while tunnel diameter of D=9m is constant and
tunnel depth increases from 9m to 24m, surface settlement decreases from 32mm to 12mm.
Table 2 shows the growth of tunnel diameter increases tunnel’s crown deformation from 6mm to 23mm,
vice versa the growth of tunnel depth reduces it from
35mm to 20mm. However, the growth of tunnel diameter
and depth cause an increase on the plastic zones circumference of tunnel and even beneath structure foundation.
4.2. Structure elements
Table 3 indicates the increment percentages of axial
force and bending moments for external and internal
column, separately. Whereas, these models have symmetric geometry, therefore centreline column changes
indiscernible. However, the growth of tunnel diameter
and the diminution of tunnel depth increase axial force
and bending moment in the external columns (C1/C5).
Meantime, increment magnitudes in the lower floors are
greater than the upper floors in these columns. In contrast, the growth of tunnel diameter and the diminution of
tunnel depth decrease noticeably axial force, but increase
bending moment in the internal columns (C2/C4) which
have upwards trend toward the upper floors unlike the
external columns. In addition, the growth of tunnel diameter and the diminution of tunnel depth increase beam
deformation especially in the beams which are located
between middle columns.
a) 1-story
b) 2-story
c) 3-story
d) 4-story
e) 5-story
Figure 4 Plastic zones of tunnel circumference for 1- to
5-storey building
2.0
0.0
ground Settlement (mm)
-40
-30
-20
-10
-2.0 0
10
20
30
40
-4.0
First step of excavation
Second step of excavation
-8.0
Excution of Final support
-10.0
Cutting underground
After construction of first floor
-12.0
After construction of second floor
-14.0
After construction of third floor
-16.0
After construction of fourth floor
After construction of fifth floor
-18.0
Displacement of Centerline of Tunnel (m)
-6.0
Figure 3 Comparison of surface settlement between 1- to 5-storey buildings and the
whole tunnelling steps.
3
6. CONCLUSION
A numerical study of the interaction between
tunnelling and adjacent structure is introduced in this
paper. Numerical simulations were conducted using 2D
calculation which takes into account the presence of the
structure in two different conditions. In the first case, the
structure is prior to tunnelling and in the next case,
tunnelling is prior to the structure. Present analysis indicates
that tunnelling-induced forces drastically depend on the
presence of adjacent structures. However, the presence of
structure prior to tunnelling influence on the settlement and
plastic zone beneath structure. Furthermore, present
analysis show that it is far too interesting to consider
substantially the growth tunnel diameter and depth in the
trend determination of surface settlement, deformation
and principal stresses of tunnel and also in the structure
elements. Finally, neglect of the structure may generally
lead to notable underestimation of the tunneling-induced
forces and incorrect computation of settlement and
subsequent unreal internal forces in the structure.
[5]
[6]
[7]
[8]
[9]
[10]
REFERENCES
[1] Boscardin MD, Cording EG. Building response to
excavation induced settlement. ASCE Journal of
Geotechnical Engineering 1989; 115(1):1–21.
[2] Burland JB. Assessment of risk damage to buildings
due to tunnelling and excavation. In: Proceedings
of 1st International Conference on Earthquake and
Geotechnical Engineering, IS-Tokyo; 1995.
[3] Burland JB, Wroth CP. Settlements on buildings
and associated damage. In: Proceedings of Conference on Settlement of structures. Cambridge: BTS;
1974. p. 611–54.
[4] Franzius J.N., Behaviour of buildings due to tunnel
induced subsidence, Department of Civil and Envi-
[11]
[12]
ronmental Engineering, Imperial College of Science, Technology and Medicine, London, 2003.
Karakus M, Appraising the methods accounting for
3D tunnelling effects in 2D plane strain FE analysis,
Tunnelling and Underground Space Technology, 22,
[2007], 47–56.
Leca E, New B, ITA WG Research, Settlements
induced by tunnelling in Soft Ground, Tunnelling
and Underground Space Technology, 22, [2007],
119–149.
Mroueh H., Shahrour I., A full 3D finite element
analysis of tunnelling–adjacent structures interaction, Journal of Computers and Geotechnics, 30,
[2003], 245-253.
O’Reilly MP, New BM. Settlements above tunnels
in United Kingdom—their magnitude and prediction. In: Proceedings of Tunnelling’82, London;
IMM; 1982. p. 173–81.
Peck RB. Deep excavation and tunnelling in soft
ground. In: 7th International Conference on Soil
Mechanics and Foundations Engineering, Mexico
City, State-of-Art, 1969. p. 225–290.
Potts DM, Addenbrooke TI. A structure’s influence
on tunnelling-induced ground movements. ICE
Journal of Geotechnical Engineering 1997;
125(Issue 02):109–25.
Sagaseta C. Evaluation of surface movements
above tunnels: a new approach. Colloque International ENPC Interactions Soil-Structures, Paris
1987; 1987:445–52.
Zienkiewicz OC, Chan AHC, Pastor M, Schrefler
BA, Shiomi T, Computational geomechanics with
special reference to earthquake engineering, John
Wiley & Sons Ltd, 1999; England.
Table 1 Specification and values of parameters of tunnel, soil and structure for the first part
Parts of
Model
Soil
Mechanic
Structure
Parameters and Values
Parameter
γ(N⁄m3)
E(MPa)
c(kPa)
ν
φ(deg)
ψ(deg)
Value
20000
500
50
0.35
30
5
Position
Value of
loading
Constructed
700 kg/m2
Variable
Parameters
Tunnel
(circular)
Constant
Parameters
1
First
effective
Parameter
D(m)
Second
effective
Parameter
Hb(m)
Parameter
Value
Total
numbers of
stories
Number of
underground storey
Distance of
columns(m)
4
5
4
First Case
Second Case
Third Case
6
7.5
9
First Case
Second Case
Third Case
9
12
24
Horizontal distance between
centreline of tunnel and structure/e(m)
0
Number of
columns
Distance of centre of tunnel and
boundary condition of soil (m)
3.5D
4
height of
stories (m)
3
Number of
Excavation's step
2
Table 2 Deformation magnitude of tunnel’s different specification
Different tunnel
D=6m,
Hb=12m
Tunnel’s crown
deformation(mm)
6
D=7.5m,
Hb=12m
D=9m,
Hb=9m
11
35
D=9m,
Hb=12m
D=9m,
Hb=24m
23
20
Table 3 Increment and reduction percentages of columns axial force and bending moments
Different tunnel
Axial force of (C1/C5) for
underground
Axial force of (C1/C5) for the
last floor
Axial force of (C2/C4) for
underground
Axial force of (C2/C4) for the
last floor
Bending Moment of (C1/C5)
for underground
for the last floor
for underground
for the last floor
D=6m
Hb=12m
D=7.5m
Hb=12m
D=9m
Hb=9m
D=9m
Hb=12m
D=9m
Hb=24m
3
9
46
28
4
2
7
40
25
3
-1
-4
-20
-14
-1
-1
-3
-17
-13
-1
32
61
176
130
70
8
24
126
80
10
140
280
1100
570
270
110
286
1600
840
130
5
The Design of a Low-Power High-Speed Current Comparator in 0.35-μm
CMOS Technology
Soheil Ziabakhsh, Hosein Alavi-Rad, Mohammad Alavi-Rad, Mohammad Mortazavi
Abstract: A novel low power with high performance low current comparator is proposed in this paper
which comprises of low input impedance using a simple biasing method. It aimed for low power
consumption and high speed designs compared with other high speed designs. The simulation results
from HSPICE demonstrate the propagation delay is about 0.7 ns and the average power consumption is
130 μW for 100 nA input current at supply voltage of 1.8 V using 0.35 micron CMOS technology.
Keywords: Current Comparator, Propagation Delay, Instantaneous Power, Positive Feedback, Signal
Processing .
by current mode circuits, should be considered first.
Secondly, a quick time response is demanded by the
current comparator. The main limitation to the time
response usually comes from the initial balance of the
output branches that often leads to the triode region some
output transistors. Finally, the precision of comparator
designs are playing an important role in the design
requirements, and it depends on the offset caused by the
mismatch of transistors. In the recent years, there have
been many good implementations reported [5, 6].
However, many of the proposed implementations had
only emphasized on one or several aspects at the cost of
deterioration in other characteristics. Obviously there is a
requirement to transform the input current to a large
voltage signal. Thus to design a high speed current
comparator, one has to consider the voltage swing
carefully since it directly determines the propagation
delay.
Conventionally, most reported current comparators
[7, 8] are based on the concept shown as a block diagram
in Figure 1, where the input current signal is converted to
the voltage Vin and V1 by the transimpedance stage
comprising inverter amplifier A1 and voltage buffer A2.
The resulting voltage V1 is then amplified by the latter
high gain inverter amplifier A3 to produce output logic
voltage. There exist parasitic capacitors at all nodes.
Ideally for high speed comparators, the signal swing
at V1 should be maintained as small as possible and
situated exactly around the inverter threshold voltage of
the inverter A3. However, the reported works were
relating to improve the lowest input current acquiring
ability by arranging a proper biasing to turn on the
MOSFETs of the buffer A2 all the time.
Most of them utilized diode connected MOSFETs as
a level shifter to create VGS of the buffer MOSFETs. It
is seen that although the transimpedance stage is formed
in a negative feedback loop, a much larger loop gain has
not been exploited to keep the signal Vin and V1 as low
as possible. Moreover with a larger loop gain, the input
impedance at node Vin could be much lower and receive
a much smaller input current in the range of Pico-Amps.
1. INTRODUCTION
Current comparators are important building blocks
within many analogue circuit designs. In particular, they
are used for front-end signal processing applications and
increasingly within neuromorphic electronic systems
[1,2]. Low voltage and low power application demands
confront voltage mode IC designs, for there is less
dynamic available under low power supply condition.
While the circuit implemented in current mode technique
occupies small area, consumes less power dissipation
and achieves more dynamic range and high operation
speed. Thus the current mode circuit design methodology
receives increasing wide attention in the recent years [3,
4].
Moreover, many sensors in SoC such as temperature
sensors, photo sensors provide current signal. In these
applications and high speed data converters, where the
function of comparison is a limiting component for
accuracy, noise and power consumption reasons, the
introduction of current mode solutions is highly
desirable. The current comparison process is injecting
one or two current flowing into the comparator and
distinguishing the current (or the difference of two
currents) is positive or negative. The output voltage
generated by the output current is used conveniently to
indicate the result of the comparison.
The comparison process is relatively simple, but the
implementation of the current comparator is becoming
more complex. Low input impedance, which is required
__________
Manuscript has been presented at IEEE 10th Int’l Symposium
on Quality Electronic Design.
Soheil Ziabakhsh and Hosein Alavi-Rad, M.Sc students,
Faculty of Engineering, University of Guilan, Rasht, Iran.
Mohammad Alavi-Rad, M.Sc student, Electrical Engineering
Department, Sharif University of Technology, Tehran, Iran.
Mohammad Mortazavi, Ph.D, Department of Electrical,
Sharif University of Technology, International Campus Kish
Island, Iran. (Corresponding author to provide phone: +98-7644422299
Ext:
347;
fax:
+98-764-4422828;
e-mail:
mortazavi@sharif.edu).
6
nonlinear positive feedback to enhance the response
time, and it can be said that improvement is achieved at
the expense of sensitivity and power consumption. The
feedback operation of these circuits does not allow the
input node to slew from rail to rail. Instead it maintains
the operating voltage of the comparator node midway
between the threshold voltages of the PMOS and NMOS
transistors M1 and M2. This allows high speed operation
but consumes high current through transistors M1-M4 as
quiescent non-zero DC power consumption.
The dead zone term which is the smallest input current
range to which comparators are insensitive is then
minimized. However, a drawback of having the small
voltage swing at V1 is that the gain of the latter inverter
amplifier must be necessarily high. Hence it yields to
higher power consumption. Obviously, there is a conflict
that if the speed as a result of a small voltage swing of
the tranresistance stage is desired, a very high gain of the
latter inverter amplifier will be necessary to provide the
rail to rail output swing.
Figure 1 Current Comparator Concept.
Figure 2 The Original Current Comparator [9].
One of most significant challenges is to minimize the
dead zone. Figure 3 shows the new circuit which
employs one diode-connected NMOS transistor instead
of two to provide the voltage drop between the gates of
M1 and M2 [11]. The advantages are not only saving one
transistor but also reducing the channel width. Here, the
(VGS - VTH) value of M4 is proportional to the square
root of current through M3, M4 and M5.
Since the input current (Iin) is very small, the
variations of current and (VGS - VTH) of M4 are also
very small. The input impedance is about 1/ (gm1 +
gm2), which is much smaller than that of Figure 1 due to
higher VGS . The drain and source of M4 are connected
to the gates of M6 and M7, respectively. The purpose is
to provide higher current for charging and discharging
the gates of M8 and M9, and thus enhance the speed. In
order to reduce the current through M6 and M7, the
channel lengths were increased to save the power
consumption. M8-M11 are a pair of inverters to amplify
the output signal.
2. PREVIEW LOW-POWER HIGH-SPEED
CURRENT COMPARATORS
Recently, a number of current comparator circuits
have been reported [9, 10]. The current comparator
reported in [9] is perhaps the first current comparator
which possesses lower input impedance than previous
circuits. In the circuit shown in Figure 2, M1 and M2
form a class B voltage buffer; and M3- M6 form two
inverting amplifiers. Iin is the input current, which is the
difference between the signal and the reference currents.
The circuit has three modes of operation. When Iin is
positive, V1 is pulled high.
This is amplified by M3 and M4, causing V2 to go
low. VGS1 and VGS2 are negative, turning M1 off and
M2 on. In this state, V1 is a low impedance node,
because Iin is supplied by M2. When Iin changes its
sign, there is insufficient gate drive for the buffer to
supply Iin, thus V1 is temporarily a high impedance
node. When Iin is negative, V1 is pulled low and V2 is
pulled high, turning M1 off and M2 on; again V1 is a low
impedance node. The width of this dead band region in
the transfer characteristic of the buffer is determined by
the threshold voltage of M1 and M2, and the response
time of the comparator significantly increases as the
input current decreases. The current comparator reported
in [10] reduced this dead band by changing the biasing
scheme of M1 and M2 from class B to class AB
operation. This results in smaller voltage swings at V1
and V2 and hence faster response. However, this
comparator requires a complex biasing circuit in order to
reduce the dead band, and increase the power
consumption.
Therefore, the comparators proposed in [9,10] use
Figure 3 The Current Comparator Proposed in [11].
7
degrading response of the current comparator for small
input currents. It consists of two current mirrors. To
minimize power consumption, the widths of M1-M4
were kept to a minimum while the lengths were adjusted
to achieve a desired current gain.
After matching the currents through M1 and M2, the
currents were matched as well through M3 and M4. An
additional Rp was added to minimize the DC current
offset.
Dimensions of M1-M4 were chosen while taking into
consideration the inverse relationship between the gain
and the 3-dB frequency of the current amplifier. M5 and
M6 are in the positive feedback loop and serve to invert
the incoming signal. In order to reduce parasitic
capacitances while allowing the inverter to draw more
current for a faster charge, the lengths of M5 and M6
were minimized and their widths were adjusted. The
dead-band region created by M7 and M8 is minimized by
setting the lengths and widths of both transistors to a
minimum. M9-M12 are a pair of CMOS inverters to
output a rail-to-rail resulting signal with a negligible
delay time.
The problem of using inverters as amplifiers is
sensitivity of processes. Since the process may go to the
SS, FS, SF and FF comers, the output of M6 and M7
may not be at the right threshold voltage of the inverter
M8/M9. Here, S and F stand for slow and fast,
respectively. The first character is for NMOS transistors,
while the second one is for PMOS. The two transistors
Mn and Mp are used to adjust the inverter threshold
voltage using different voltage values of Vn and Vp. For
the typical case (TT), Vn is equal to VDD and Vp is
grounded. A schematic of the positive feedback system
proposed in [12] is shown in Figure 4.
Positive feedback operates at the output nodes of the
inverters M5/M6 and M7/M8, respectively. In the predecision state transistors M2 and M3 are closed and
transistors M1 and M4 are open. As the voltage on the
comparator node is affected by input current, so the
inverter M5/M6 begins to switch. As this slews to either
rail the transistors M2 or M3 are switched open, and then
with a delay of about 10 ns the transistors M1 or M4,
respectively, are switched closed. This latched feedback
dumps enough charge on the comparator node to
significantly speed the decision process, particularly at
low current inputs.
Figure 5 New Current Comparator.
4. EXPERIMENTAL RESULTS
With HSPICE, the new current comparator was
simulated using TSMC 0.35 μm CMOS technology
parameters and with 1.8 V power supply. Figure 6 shows
the input square-wave current which changes between 100 nA and 100 nA, as well as the transient waveform of
output voltage of the proposed comparator and other
three comparators discussed in the previous section.
Incidentally, the rise and fall time delays of the new
comparator are both 0.7 ns and the average power
consumption is 130 μW.
Obviously, the solid line from the new circuit
switches faster than the other cases. To our knowledge,
the simulation results of the proposed current comparator
are better than existing comparators to date. When the
circuit in [9] was simulated, the delay was 1.7 ns for a 5
μA wave and 2.5 ns for a 1 μA wave. A major problem
of this comparator is its response to low inputs. A large
delay for small signals can jeopardize the performance of
the current comparator. Instantaneous power of the
proposed comparator is shown in Figure 7.
Figure 8 and Figure 9 compare the propagation delay
Figure 4 Current Comparator Proposed in [12].
One disadvantage of this system is that the input node
slews from rail to rail and this can slow the operation of the
comparator. However, this is still a significant speed
improvement over a simple inverter comparator.
3. PROPOSED LOW-POWER HIGH SPEED
CURRENT COMPARATOR ARCHITECTURE
The proposed high speed, low DC offset, and lowpower consumption CMOS current comparator is shown
in Figure 5. The current comparator consists of a current
amplifier (M1-M4 and Rp), a Class B output stage
(M7/M8), and three CMOS inverters (M5/M6, M9M12). The proposed design is a modified version of the
simple current comparator in [9], with an added current
amplifier and an extra pair of inverters compared to the
original design. The current amplifier enhances the
8
Research Bullletin, Vol. 1, No.
N 1, December 2009
and the averaage power of different com
mparators. In these
t
figures, the labels
l
“1”, “22”, “3” and “44” represent three
t
different com
mparators shoown in figurees 2, 3, 4 andd the
new compaarator in Figure
F
5, reespectively. The
propagation delay is deefined as thee time difference
between the output and thee input signals when they reach
r
the 50% of thheir total variaations.
As it can be seen from
m Figure 8, thee delay time of the
new comparrator is lowerr than compaarators in [9] and
[12] for all ranges
r
of inpput current annd is only sligghtly
higher than comparator inn [11] for inpput current loower
than 10 nA
A. But, the power
p
dissipaation of the new
comparator is
i very low in comparison with
w others. Soo for
the power deelay product, the
t new compparator is supeerior
to the other circuits,
c
especcially at low input
i
current. The
component values
v
of the new compparator and other
o
comparators discussed in
i the previious section are
presented in Table 1.
Performaance comparisons among reported circcuits
are listed in Table
T
2.
mparison with other reportedd comparatorss.
com
Figu
ure 7 Instantaneeous Power of th
the Proposed Co
omparator.
Since for maany applicatioons, the response time off
com
mparator at low
w current levvel limits the overall speedd
of the
t system, thhis circuit will allow a sign
nificant speedd
imp
provement in system levell designing. Also
A
the low
w
pow
wer dissipationn characteristiic of it is quitte suitable forr
porttable and batteery supplied eelectronics dev
vices.
Figure 8 Delayy Time Compariison Due to Inp
put Current.
ure 9 Power Consumption Com
mparison Due to
o Input
Figu
Currrent.
Figure 6 Compparison of Wavveform Responsses of the Input
Current and Output
O
Voltage.
CON
NCLUSION
We havee proposed ann improved cuurrent comparrator
for high speeed and low-ppower applicaations. Simulaation
results done by HSPICE and by usingg TSMC 0.355 μm
CMOS technnology with 1.8
1 V supply voltage
v
show that
in the propossed comparatoor, the power--delay productt has
been significcantly reducedd at low inpuut current leveel in
9
Table 1 The Channel Length And Width Of Transistors Parameters Used For Current Comparators.
Na
me
Träf [9]
W(μ
m)
L(μ
m)
Na
me
Lin [11]
W(μ
m)
M1
9
2
M1
0.5
M2
3
2
M2
1.2
M3
M4
M5
M6
9
3
9
3
2
2
2
2
M3
M4
M5
M6
M7
0.5
0.5
2.5
0.6
1.8
M8
0.8
M9
3.7
M1
0
M1
1
0.9
3.5
Mn
1.9
Mp
5
L(μ
m)
0.3
5
0.3
5
0.6
0.7
1
1
1
0.3
5
0.3
5
0.3
5
0.3
5
0.3
5
0.3
5
Na
me
Banks [12]
W(μ
L(μ
m)
m)
Na
me
Our Approach
W(μ
L (μm)
m)
M1
2
2
M1
0.36
0.48
M2
2
2
M2
0.36
2.04
M3
M4
M5
M6
M7
2
2
2
2
2
2
2
2
2
2
M3
M4
M5
M6
M7
0.36
0.36
1.08
0.36
0.36
0.24
0.6
0.24
0.24
0.24
M8
2
2
M8
0.36
0.24
M9
1.08
0.24
0.36
0.24
1.08
0.24
0.38
0.48
M1
0
M1
1
M1
2
Table 2 Table Performance Comparisons Used for Current Comparators.
Träf [9]
Lin [11]
Banks [12]
Our Approach
1992
2000
2008
2008
Year
3
3
3
1.8
Power supply (V)
2
0.35
0.35
0.35
Technology (μm)
Minimum Input Current
500
50
10
10
Amplitude (nA)
10
2.8
14
0.7
Propagation delay (nsec)
580
Power dissipation (μW)
390
300
130
(at 100
(at 10 nA)
(at 10 nA)
(at 10 nA)
nA)
Low Charge-Injection Errors,” IEEE Journal of
Solid-State Circuits, vol. 37, no. 10, pp. 1271-1281,
Oct. 2002.
REFERENCES
[1] D. J. Banks, P. Degenaar, and C. Toumazou, “A
Colour and Intensity Contrast Segmentation
Algorithm for Current Mode Pixel Distributed Edge
Detection,” Eurosensors XIX, Barcelona, 2005.
[5] V. Boonsobhak, A. Worapishet, and J. B. Hughes,
“Reduced
Kickback
Regenerative
Current
Comparator for High-Speed Switched-Current
Pipeline
Analogue-To-Digital
Converters”,
Electronics Letters, vol. 39, no. 1, pp. 4-5, Jan. 2003.
[2] D. J. Banks, P. Degenaar, and C. Toumazou,
“Distributed Current-Mode Image Processing
Filters,” Electronics Letters, 41, pp. 1201–1202,
2005.
[6] G. Palmisano and G. Palumbo, “OffsetCompensated Low Power Current Comparator,”
Electronics Letters, vol. 30, no. 20, pp. 1637-1639,
Sept. 1994.
[3] H. Hassan, M. Anis, and M. Elmasry, “MOS Current
Mode Circuits: Analysis, Design, and Variability,”
IEEE Transactions on VLSI, vol. 13, no. 8, pp. 885898, Aug. 2005.
[7] H. Lin, J. H. Huang, and S. C. Wong, “A simple
high-speed low current comparator,” IEEE Trans.
Circuit Syst., pp. 713-716, 2000.
[4] G. K. Balachandran and P. E. Allen, “SwitchedCurrent Circuits in Digital CMOS Technology with
10
[8]
L. Ravezzi, D. Stoppaa, and G. F. Dalta Betta,
“Simple High Speed CMOS Current Comparator,”
Electronics Letters, vol. 33, no. 22, pp. 1829-1830,
1997.
[9] H. Träff, “Novel Approach to High Speed CMOS
Current Comparators,” Electronics Letters, vol. 28,
no. 3, pp. 310-312, 1992.
[10] A. T. K. TANG and C. TOUMAZOU, “High
Performance
CMOS
Current
Comparator,”
Electronics Letters, 30, (l), pp. 5-6, 1994.
[11] H. Lin, J. H. Huang, and S. C. Wong, “A Simple
High-Speed Low Current Comparator,” IEEE
International Symposium on Circuits and Systems
(ISCAS), Geneva, Switzerland, May 2000.
[12] D. Banks and C. Toumazou, “Low-Power HighSpeed Current Comparator Design,” 31st Electronics
Letters, vol. 44, no. 3, January 2008.
11
On the Search Window Updating for Occlusion Handling in Object Tracking
Application
Mohammad Khansari, Hamid R. Rabiee, Mohammad H. Rohban, Mohammad Ghanbari
Abstract: Efficient search window updating mechanism has a great impact on the performance of object tracking
applications. In this paper, adaptation and analysis of an inter-frame texture analysis for efficient occlusion handling is presented. The algorithm uses the temporal difference histogram of two successive frames to estimate the
direction and speed of the object motion. This temporal texture analysis assists in tracking of the object under partial or short-term full occlusion. Experimental results show good performance in occlusion handling for object
tracking compared to search window updating using the well known particle filters.
Keywords: Interframe texture analysis, object tracking, occlusion handling, particle filters.
propagation of any mismatch into the following frames
to lose track, in particular for occluded objects [2].
Particle filtering techniques have recently proven to be
powerful and reliable tools for tracking nonlinear/nonGaussian systems [4, 5]. They allow fusion of different
data to incorporate constrains and to account for different
uncertainties. Furthermore, they are able to cope with
missing data, e.g. lost pixels in a SW of an object
tracking system.
Our approach to attain an efficient SW updating
mechanism is to estimate the direction and the speed of
motion of the moving object using inter-frame texture
analysis technique to update the location of the SW [1, 2,
3, 6].
The main contribution of this paper is the adaptation
of inter-frame texture analysis technique to cope with
partial or long-term full occlusion of the object in
tracking applications without assuming a model for the
target of interest and providing the required analysis
along with comparison against the well known particle
filters.
We present the inter-frame texture analysis algorithm
in section 2. Section 3 illustrates the experimental results
and section 4 concludes the paper.
1. INTRODUCTION
One of the challenging problems in the applied image
and 1 video processing is the tracking of objects. A
typical object tracking application associates a model to
the object of interest at a reference frame and then
temporally tracks and updates this model in the
successive frames of the video sequence.
Temporal object tracking applications aim at locating
the target object in the successive frames based on the
information about the object in the reference and the
current frames. More specifically, it can be defined as the
process of generating the trajectory of the object over
time by locating it in successive frames of image
sequence. One of the main difficulties in temporal
tracking is finding the direction and displacement of the
search window (SW). The SW defines the search area
within the algorithm to look for the object at the current
frame. The change of object location requires an
efficient, smart and adaptive SW updating mechanism
for at least three reasons:
• A proper SW location ensures that the object always
lies within the search area and thus prevents losing the
object.
• A location-adaptive fixed size SW reduces
computational complexity by searching only the
required area [1].
2. INTERFRAME TEXTURE ANALYSIS
Interframe texture analysis tries to estimate the SW
displacement by finding the direction and speed of the
moving object inside the SW. To find the direction and
the speed of the moving object, we define the temporal
difference histogram of two successive frames. Coarseness and directionality of the frame difference of the two
successive frames can be derived from the temporal difference histogram. Finally, the direction and speed of the
motion is estimated through the use of temporal difference histogram, coarseness and directionality [1, 3].
• If an object of interest is occluded by another object,
intelligent positioning of the SW through the finding of
the direction and the speed of the moving object may
alleviate the occlusion [2, 3].
SW Updating based on the center of the bounding box
around the object at the current frame, will lead to
Mohammad Khansari, Ph.D, Department of Information
Technology, Sharif University of Technology, International Campus Kish Island, Iran. (e-mail: khansari@sharif.edu).
H. R. Rabiee and M. Rohban are with the Digital Media Research Lab, Computer Eng. Department, Sharif University of
Technology, Tehran, Iran.
M. Ghanbari is with the School of Computer Science and Electronic Engineering, University of Essex, England.
2.1. Temporal difference histogram
The temporal difference histogram of two successive
frames is derived from the absolute difference of gray
level values of the corresponding pixels at the two
frames.
12
used to identify the principle texture direction. If a
texture is directional, that is coarser in one direction than
the others, then the degree of the spread of the values in
pδ i should vary with the direction of δ , assuming that
Consider the current search window ( SAt ( x, y ) ) at
t
and a new search window ( SAt +1 ( x, y ) )
frame
determined by a displacement value of δ = (Δx, Δy ) to
the current search window center in the next frame. It
should be noted that the two search windows have the
same size. We define absolute temporal difference
( ATDδ ) of the two windows as follows:
i
its magnitude is in the proper range. Thus, texture
directionality can be analyzed by comparing spread
measures of pδ i for various directions of δ .
To derive the motion direction from texture
direction, the direction that maximizes the IDM should
be found.
ATDδ ( x, y ) =| SAt ( x, y ) − SAt +1 ( x + Δx, y + Δy ) |
(1)
Then, we calculate the histogram of the values of
ATDδ . Note that the histogram has M bins, where
IDM max = max {IDM i } , i = 1, 2,..,8
M is the number of gray level values in each frame (256
The maximum value of IDM , IDM max indicates
that the frame difference is more homogenous in that
direction than the others, implying that the corresponding
blocks in the successive frames are more correlated.
for an 8 bit image, or pixels may be quantized into M
levels).
Finally, the histogram values are normalized with
respect to the number of pixels in the search window
( N x × N y ) to obtain the probability density of each gray
2.3. Search window dispalcement
The quantitative measure for coarseness of texture is
the temporal contrast which is defined as the moment of
p
inertia of δ around the origin, and is given by:
level value, pδ (i ) i = 0,.., M − 1 .
2.2. Search window direction
Assume that the search window is a rectangular block.
Consider eight different blocks at various directions with
distance of δ i from the center of search window at the
current frame (Figure 1).
M −1
TCON =
calculate
the
temporal
difference
p
histogram, δ i , for each block with respect to the
original block (search window). Now, we can easily
LCON =
compute the inverse difference moment, IDM i ,
corresponding to each block using equation (2). The
inverse difference moment, IDM , is the measure of
homogeneity and is defined as:
i =0
2
1
SW
∑ ⎡⎣ g ( x , y ) − g ⎤⎦
2
(5)
SW
where g ( x, y ) is the gray level value of the pixel
located at position ( x, y ) and g is the average gray
value of the pixels in the search window. Based on the
temporal and local contrasts, a good estimation of the
average motion speed, S within a block can be defined
p (i )
∑ i δ +1
(4)
where M is the number of gray level values in each frame
as stated in section 2.1.
The parameter TCON , gives a quantitative measure
for the coarseness of the texture and its value depends on
the amount of local variations that are present in the
region of interest. The existence of high local variations
in a frame implies an object activity in the frame and this
frame is called active when compared to the frames with
small variations. Since active frames of an image
sequence exhibit a large amount of local variations, the
temporal contrast derived from the frame difference
signal is related to the picture activity. The parameter
TCON is normalized to Local Contrast ( LCON ) in order
to minimize the effect of size and texture of the search
window ( SW ). The parameter LCON which defines
the pixel variance within the search window is given by:
Then,
IDM =
∑ i 2 pδ (i )
i =0
Figure 1 Distance assignment in the different directions to find the maximum (Inverse
Difference Moment)
M −1
(3)
(2)
In a homogeneous image, there are very few dominant
gray level transitions, hence pδ i has a few entries of
as:
S =k
large magnitudes. Here IDM contains information on the
distribution of the non-zero values of pδ i and can be
13
TCON
LCON
(6)
where k is a constant with empirically selected values.
The average motion speed, S, in equation (4), is not only
independent of the size of the moving objects but also is
invariant to the orientation of their texture. The value of
S approaches to zero for stationary parts of the picture
such as background, independent of its texture contents
[1].
The displacement value of the search window for the
next frame is given by
R j −1 = S j −1 − Disp j −1
Disp j = ⎢⎣S j + R j −1 ⎥⎦
algorithm were set to
δ =4
and k=16. All figures
a) Frame #506
b) Frame #646
c) Frame #830
d) Frame #855
(7)
In some future frames the value of S might be less than
1, thus the displacement of the search window will be
equal to zero. Parameter R j −1 denotes the displacement
residue at the previous frame. Assuming low speed
object movements, the parameter R j −1 , helps to sum up
18
the values of displacements that are less than one pixel
away, until they reach to at least one pixel displacement.
16
14
12
D is t a n c e (p ix e l)
2.4. Occlusion handling analysis
Using Inter-frame texture analysis for search window
updating mechanism keeps the object in search area
during and after the occlusion. We analyze two different
full occlusion cases; short-term and long-term occlusion
scenarios.
10
8
6
4
2
• In case of short-term occlusion, motion directions of
the object and the occluding object are different.
Therefore, a suitable search window size is led to
handle the occlusion as soon as the object partially
re-appears.
0
500
550
600
650
700
Frame Number
750
800
850
f)
Figure 2 (a-d) Search Window Updating in order to
track a man with a long term occlusion (about 200
frames) using inter-frame texture analysis (f) Objective
evaluation: distance between the center of tracked
bounding box and the expected center for the interframe texture analysis algorithm.
• Long-term occlusion originates from the fact that the
object of interest and the occluding object both
moves at the same direction. Since the algorithm uses
activity analysis to find the motion and direction of
the search window and hence updates the search
window location, it can predict the location of the
object after occlusion. Therefore, our updating
mechanism ensures that the object lies within the
search window in case of occlusion and a robust
target representation model allows for successful
tracking, afterward.
(except for the reference frame) are zoomed in to show
the bounding box and search window status better.
In the video sequence a full-occlusion starts at frame
645 and lasts for 200 frames. During this period there is
no clear information available on the object location.
However, our SW updating mechanism acts very well in
this occlusion period and keeps the object within the
search area during and after the occlusion (Figure 2(a, b,
c, d)).
Long-duration occlusion normally occurs when the
object of interest and the occluding object both moves at
the same direction. Since the algorithm uses the activity
analysis to find the motion and direction of the SW and
updates the SW location, the SW follows the object even
in the case of occlusion. Moreover, it avoids error
propagation of false SW center prediction in the
following frames in the case of incorrect object tracking
of the current frame. Therefore, in contrast to the well-
3. Experimental results
The inter-frame texture analysis algorithm was applied
on a sequence with a long term occlusion (data set S7,
camera 1, from IEEE PETS2 2006 workshop). The SW
size was set large enough, 212x177 (±78 pixels), to show
how good the algorithm can locate the SW to handle the
occlusion and encompass the target object of 56x21
pixels after the occlusion. Empirical parameters for the
2
Ninth IEEE International Workshop on Performance Evaluation of Tracking and Surveillance
14
known methods miss-tracking of occluded object is
mostly prevented.
In short-duration occlusion, normally motion
directions of the object and the occluding object are
different. Despite the fact that SW moves in the opposite
direction to the object, for a suitable SW size, the
occlusion can be handled as soon as the object partially
reappears.
Figure 2(f) shows the difference between the centre of
gravity of the bounding box and the actual centre of the
object in successive frames, as a measure of tracking
fidelity (in pixels). There is an initial 18 pixel offset error
which is mainly due to the large size of the bounding
box. Note that, during the tracking the object has been
tracked within the distance of the range of the initial
offset. During the complete occlusion the distance
measure is meaningless (we have deliberately set the
distance to zero), but tracking is resumed with accuracy
as good as the pre-occlusion period. The corresponding
video clip of Figure 2 is available through the Internet3.
Particle filtering algorithm is also used to update SW,
with 20 and 50 particles. State vector is 2 dimensional
that is [Δx, Δy], where (Δx, Δy) is the change in upper left
coordinates of SW. Dynamic process which used to
update state vectors include adding a Gaussian noise
with variance 6.0 to (Δx, Δy) each time.
Feature that was used during measurement process is
a vector containing SW pixels grey values and SW edge
map values. Measurement process is performed using
weighted MSE of the previous and current window
features as follows.
appearance model formed by weighted averaging of
chosen SW feature at time t-1 and At-1 :
At = aFt-1(pt-1avg) + (1-a)At-1
Where pt-1avg is the mean of particles using the particle
weights as the estimated probability. We have chosen a
around 0.98 which means that appearance model changes
very slowly. In order to find the new place of the SW in
the current frame, average of {pt1, pt2, …} = ptavg is
Probability{pti|features of previous frames} = exp{|W×(Ft(pti)-At)|2/2σ2}
a) Frame #506
a) Frame #506
b) Frame #646
b) Frame #646
c) Frame #830
c) Frame #830
a) Frame #506
b) Frame #646
Figure 3 Search window updating using particle filters
without occlusion detection.
Where W is a weighting function which heavily
emphasizes on the center of the window. pti is the ith
particle at time t. pt-1avg is the average of particles in time
t-1 which were weighted according to their estimated
probability. Ft(pti) is the feature corresponded to the
window related to pti of the frame at time t.
σ is chosen to be about 100. Weighting function is of
Gaussian type with variance 20. At is a simple
d) Frame #855
d) Frame #855
Figure 4 Search window updating using particle filters
with occlusion detection (left: 20 particles, right: 50
particles).
calculated and used. However, particle filter completely
miss-tracks the object of interest from frame number
3
http://ce.sharif.edu/~khansari/JASP/S7-T6-B.-WBMAdep3sw78(212x177)-bs56x21-d4k16-00506-999.avi
15
646 and it will never place the SW in a position that
contains the target of interest. The result for frame #646
is shown in Figure 3.
One solution to improve particle filter based search
window displacement algorithm is to detect the occlusion
and not to update particles weights during the occlusion
period.
To detect occlusion we have adopted another
appearance model Bt with the same definition as At but
with another weight, say b. If MSE of features of SW
corresponding to pt-1avg and Bt is more than a threshold,
an occlusion is reported. In the case of occlusion,
particles weights will not be updated, until the end of
occlusion. If the MSE falls below another threshold, the
occlusion is considered to be ended. b is set around 0.94,
which causes Bt to change faster than At. This adoption
of b, makes the algorithm to detect the occlusion soon,
before it can affect the main appearance model At.
Results for 20 and 50 particles are shown in Figure 4.
The figures have been zoomed in and cropped to show
the search window better. As can be seen, occlusion
detection and increasing the number of particles (right
column) makes the results better; however it slows down
the tracking process tremendously. Tuning of a, b,
dynamic process variance, and σ is an important issue in
the particle filter algorithm. The only way to set these
parameters is by trial and error. They are highly
depending on the video sequence nature and can not be
set automatically. Incorrect choice of any parameter may
cause the algorithm to misguide the search window and
loss the object of interest. Therefore, regardless of
quality of results of particle filter which follow the
correct inter-frame texture analysis algorithm results in
some case, the particle filter based search window
updating algorithm is very sensitive to the parameters
initialization and entails computational complexity which
are far from practical applications requirements.
[2]
[3]
[4]
[5]
[6]
4. CONCLUSIONS
A search window algorithm using inter-frame texture
analysis for search window updating in object tracking
application has been presented. The algorithm finds the
object motion and direction to displace the search
window. The algorithm has been compared with the well
known particle filtering algorithm for search window
updating. The experimental results confirmed the
efficiency of inter-frame texture analysis for
displacement of search windows in tracking the object in
case of occlusion. The algorithm outperforms particle
filtering method for search window displacement and
does not have the parameter sensitivity problem as well
as the computational complexity of the particle filtering
method.
REFERENCES
[1] V. E. Seferidis and M. Ghanbari, “Adaptive Motion
Estimation Based on Texture Analysis”, IEEE
Transactions on Communications, Vol. 42, No. 2-4,
pp. 1277-1287, 1994.G.-D. Hong, “Linear controll16
able systems,” Nature, vol. 135, no. 5, pp. 18-27,
July 1990.
M. Khansari, H. R. Rabiee, M. Asadi, P. Khadem
Hamedani, M. Ghanbari, “Adaptive Search Window for Object Tracking in the Crowds using Undecimated Wavelet Packet Features”, WAC, World
Automation Congress, July 24-26, Budapest, Hungary, 2006.
M. Khansari, H. R. Rabiee, M. Asadi, M. Ghanbari,
“Occlusion handling for object tracking in crowded
video scenes based on the Undecimated Wavelet
features', ACS/IEEE International Conference on
Computer Systems and Applications, AICCSA,
May 13-16, Amman, Jordan, 2007.
M.S. Arulampalam,. S. Maskell, N. Gordon, T.
Clapp, “A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking,” Signal
Processing, IEEE Transactions on ,Volume 50, Issue 2, pp.174 - 188, Feb 2002.
M. Isard, A. Blake, “CONDENSATION - conditional density propagation for visual tracking,” Int.
J. Computer Vision, vol. 29, no. 1, pp. 5-28, 1998.
M. Khansari, H. R. Rabiee, M. Asadi, M. Ghanbari,
"Object Tracking in Crowded Video Scenes Based
on the Undecimated Wavelet Features and Texture
Analysis," EURASIP Journal on Advances in Signal Processing, vol. 2008, Article ID 243534, 18
pages, 2008. doi:10.1155/2008/243534.
Composite Particleboard Panels Made from Stone powder-Rice straw
Properties are Experimented as a New Construction Materials
Mohammad R. Shams , Hassan Pezeshki Modarres
Abstract: The objective of this research is to determine some of the properties of experimental multi layer
particleboard panels made from powder stone and natural rice fiber, which are considered as invasive
under-utilized species in Iran. Static bending, internal bond strength, the mixed concentration and
particle size are studied. The samples are tested for their mechanical strength and physical stability
properties according to the procedures defined by ASTM D-1037. The modulus of elasticity of the panels
made from this method is 18 to 24.5% higher than the ones made from wood mixed particles upon
particles size. Overall mechanical properties of the panels are not only more statistically advanced
compare to pressed particle wood, also has much better results for the water soaking tests. This is
demanding for environment of living on near water or environment of high humidity. This sandwich panel
formed by two composite skins, one on each side of a core of insulation material has high shear resistance
and light structures for the Earthquake zone, and is suitable for marine area with different climate and
temperatures.
Keywords: Particleboard, Stone Powder, Light Panels, Rice Straw, Fiber Surface Roughness, Shear
strength
Durability, desirable surface finishing and overlay is a
premium product in cabinet and furniture manufacture as
far as its quality is concerned. Usage of stone powder
and overlaying with thin laminates of substrate
composite panels such as rice fiber improve their
appearance and properties resulting in value-added
products.
Rice particleboard panels provide an
acceptable surface for the various applications, but well
developed adhesive strength between overlay and
substrate is required to have an ideal lamination process.
Using powder stone can improve the adhesive strength
and irregularities on the surface of substrate during the
service life [3, 4].
Some of the major factors which play significant role
for service life of the composite panels are particle size
and geometry that play significant role to maintain the
surface quality of overlaid products during its service life
[5,6].
Other objectives of this research are to study the
adhesive shear strength between stone powder and rice
fiber substrate. The evaluation of the surface roughness
of substrate panels and the strength of adhesive were
investigated to improve the quality of laminating process.
1. INTRODUCTION
Natural fiber composites are alternatives for
replacement of the glass-fiber composite in many
applications because of lower cost and lower density.
Life biodegradability of components, lower pollutant
emissions and enhanced energy recovery are some of the
environmental advantages of the natural fibers. Natural
fibers such as rice, cotton, bamboo, hay, jute and sisal are
attracted for application in consumer goods and civil
structures. These fibers have good thermal and acoustic
insulating properties and have higher corrosion
resistance to fracture [1, 2]. Relatively high strength
and stiffness of the rice fiber is acceptable. The level of
strength is not the same as glass fiber but most of the
natural fibers such as rice have good ductility. The
usage of rice fiber also has an economical advantage
compare with glass or carbon fiber.
The significant of this study is to explore the
potential of abundant resources from the waste to use for
fiber reinforced composite panels. Usage of the waste
stone powder enhanced the strength, durability,
workability and moisture uptake that can be suitable for
marine area with different climate and temperatures.
2. MATERIALS AND METHODS
__________
Manuscript has been presented at Fourth International
Conference on Advances and Trends in Enginering Materials and
their Applications (AES – ATEMA 2009 Hamburg).
Hassan Pezeshki Modarres, M.Sc student, Department of
Chemical Engineering, Sharif University of Technology.
Mohammad Reza Shams, Department of Material Science,
Ext:
334;
fax:
+98-764-4422828;
e-mail:
shams@sharif.edu).
The raw material of the rice fiber, stone powder and
silicon solution matrix was selected as epoxy resin for
the bonding. Rice straw and silicon resin was used to
make the base substrate sheet panels and stone powder
was applied as a single layer and double layers to study
the composite panels mechanical properties.
Preparation of rice fiber composite panels: The rice
fiber and stone powders was collected from local
resources (Isfahan, Iran).
17
Samples with a thickness of 10 mm were obtained from a
designed mould. The samples were formed into 220 (L)
x 110 (W) mm sheets for the experiments (Figure 1).
Long random and woven roving fiber
densities
1.5
2 Group Density
0.970.89
0.690.730.76
1
0.5
1 Group Density
0
0
Figure 2 Density (g/cm3) comparison of the Long
random and woven roving rice straw panels
mechanical test. The results for each group of 1 and 2
samples are listed in Tables 1 and 2.
Figure 1 Rice straw composite panels with and
without powder stone
Flexural test: Flexural test were performed on
Five samples of A1, B1, C1, D1 and E1 groups were
made in a long random fiber composite panel for the test.
Five more panels were obtained from the rice fiber and
silicon solution matrix in woven roving fiber reinforced
composite panels (A2, B2, C2, D2, and E2 groups).
The panels were applied with one side and two side stone
powders (D and E group).
The mould was made
double-sided in a form of square shape. The long random
fiber and woven roving fiber were obtained based on the
mould size. The matrix was poured over the fiber,
compressed and distribute evenly until it achieved the
final thickness of 10 mm panel. For the single layer
stone powder composite panels the same process is
applied but 2.0 mm stone powder is distributed with the
epoxy and is applied into the bottom of the mould first.
Double-sided stone powder covering the rice panel
substrate following the above process with additional 2.0
mm stone powder mixed with epoxy poured and
distributed over the top of the samples. Unfinished
composite plate then pressed and pushed down with the
finger to avoid and eliminate the bubbles. The samples
pressed with 0.5 Mpa pressure for 20 hours for the curing
time at the room temperature condition of 25°C. All
specimens of fiber composite panels are made this way
with10 mm thickness.
Test preparation: All specimens test were conditioned
based on the standard procedures of ASTM D618-99
before mechanical tests.
The test specimens were done in the room condition of
25oC in temperature and with relative humidity 40-45%
in the standard laboratory atmosphere.
A fine stylus profilometer, Bendix Model 400 was used
to determine surface characteristics of the substrate for
the adhesive shear strength of composite panels.
Data Analysis: The densities of the specimens (Figure
2) were investigated. The types of mechanical test that
were measured in this research are flexural tests. Each
mechanical test was carried out based on natural fiber
composite. Ten specimens were prepared for the
Table 1 The results of the densities for the long
random (Group 1) and woven roving (Group 2)
rice fiber specimens
Group 2
Long random fiber(1)
Group 1
Density
& Woven roving fiber
Density
(g/cm3)
(2) panels
(g/cm3)
10 wt % fiber (A1) &
0.76
0.72
(A2)
15 wt % fiber (B1) &
0.73
0.69
(B2)
20 wt % fiber (C1) &
0.69
0.58
(C2)
Panel with one side
0.89
0.82
powder (D1) & (D2)
Panel with two side
Powder (E1) & (E2)
0.97
0.91
Table 2 The results of the Flexural strength of the
long random (Group 1) and woven roving rice fiber
specimens (Group 2)
12Long random fiber
Flexural
Flexural
(1) & Woven roving
strength
strength
fiber (2) panels
(MPa)
(MPa)
10 wt % fiber (A1)
79
105
& (A2)
15 wt % fiber (B1)
87
114
& (B2)
20 wt % fiber (C1)
82
107
& (C2)
Panel with one side
97
117
powder (D1) & (D2)
Panel with two
side Powder (E1) &
85
102
(E2)
18
Woven roving rice straw fiber composite: The flexural
properties of woven roving fiber reinforced composite
indicates that 15 wt.% woven roving fiber reinforced
epoxy composite has a maximum flexural strength of
105 MPa and Young’s modulus values of 4700 MPa.
While 20 wt.% woven roving fiber has the values
(Figures 3 and 4).
the same machine using the 3-point bending method
according to ASTM D790-99 [7]. The specimens were
tested at a crosshead speed of 1 mm/min.
3. RESULTS AND DISCUSSION
Density of the rice straw fiber composite: Density
results indicate that long random rice panels (group 1)
and woven roving panels (group 2) have close value
of the density of a typical Oak wood (0.68 g/cm3).
Adding powder stone to the substrate of rice straw
panels ( samples D and E) indicate acceptable values of
the densities of 0.82-0.91 g/cm3 which gives
comprehensive
information
about
overlaying
characteristics of these composite panels (Table 1 and
Figure 2)
Long random rice straw fiber composite: With the
increase of fiber loading percentages from 10% to 20wt.
% long random rice fiber, the flexural strength value
enhance regularly from 79 MPa and the density decrease
from 0.76 g/cm3 to 0.69 g/cm3 as the weight percent of
fiber increases (Figure 2 and Table 1). The condition
above indicates that 10% and 15 wt. % long random fiber
is stiff and strong, adding powder stone reveals that
overall mechanical properties are enhanced but it has a
limitation due to the size and thickness of rice straw
panels and powder stone (Figures 3 and 4).
Table 3 The results of the Young's modules of the long
random (Group 1) and woven roving rice fiber
specimens (Group 2)
12Long random fiber (1)
Young's
Young's
& Woven roving fiber (2)
modulus
modulus
panels
(MPa)
(MPa)
10 wt % fiber (A1) &
4300
4700
(A2)
15 wt % fiber (B1) &
3900
3850
(B2)
20 wt % fiber (C1) &
4200
4500
(C2)
Panel with one side
4550
4700
powder (D1) & (D2)
Panel with two side
4700
4600
Powder (E1) & (E2)
5. CONCLUSIONS
Flexural strength (MPa)
100
50
0
Long random and Woven …
Flexural strength (MPa)
117 114
105
102 107
97
87
85
79
82
Density, mechanical properties such as flexural
strength, young's modulus was studied for the rice fiber
reinforced composites panels.
Additional layers of powder stone was laminated on
the substrate of rice straw panels. The properties are
described on the basis of the experimental evidence, the
conclusions are as follows:
The results of flexural strength test of the rice straw
reinforced composites showed that 15 wt. % woven
roving fiber has the highest value compared to other fiber
content. Considering the density, the flexural strength
test of the rice composites panels with 15 wt. % woven
roving fiber and one side stone powder has the best
results. Moreover, the particle size of the rice fiber, shear
strength, adhesive bonding, water absorption and the
influence of the different pressure level during the
overlaying process are investigated and will be published
for the next proceeding paper to have more
comprehensive
information
about
overlaying
characteristics of these composite panels.
150
Figure 3 Flexural strength (MPa) comparison of the
Long random and woven roving rice straw panels
6000
4850
4700
5000
4500
4000
3000
2000
1000
0
Long random and Woven roving composite panels
4600
4700
Young's modulus (MPa)
Young's modulus (MPa)
REFERENCES
[1] Oksman. K., M. Skrivars and J.F. Selin, 2003. Natural fibers as reinforcement in polylactic acid
(PLA) composites. J. Comp. Sci. Technol.,
63:1317-1324.
[2] Joshi,S.V., L.T. Drzal and S.A. Mohanty, 2003. Are
Natural fiber composites environmentally superior
to glass fiber Reinforced composites: Applied
Science and Manufacturing , 35: 371-376.
[3] Kolmann, F.F.P., E.W. Kuenzi and A.J. Stamm,
Figure 4 Young's modulus (MPa) comparison of the
long random and woven roving rice straw panels
19
[4]
[5]
[6]
[7]
1975. Principle of Wood Science and Technology.
Wood Based Materials. Springer-Verlag, New York,
Heilderberg and Berlin, vol: 2.
Rabiej, R.J. and P.T. Brown, 1985. Factors affecting
setting rate of polyvinyl acetate adhesives in wood
joints. Proc. Conf.: Wood Adhesives in 1985: Status
and Needs, Madison, WI.M. Young, The Technical
Writer’s Handbook, Mill Valley, Seoul, 1989.
Faust, T.D and J.T. Rice, 1986. Characterizing the
Roughness of Southern Pine Veneer Surfaces. Forest Products J., 36: 45-48.
Heebink, B.G., 1967. A procedure for quickly evaluating dimensional stability of particleboard.
Forest Products J., 17: 77-80.
ASTM D790-99, 2000. Standard test method for
flexural properties of un-reinforced and reinforced
plastics
and
electrical
insulating
materials.American Society for Testing Materials.
20
Modeling and Simulation of Graspers Force in Minimally Invasive Surgery
Ramin Hortamani, Abolghassem Zabihollah
Abstract: In Minimally Invasive Surgery (MIS) the operation is performed through introducing
surgery instruments, graspers, and scissor into the body. In the present work, a novel smart grasper is
presented in which the surgeon can virtually acquire a feeling of force/momentum experienced by the
organ/tissue. The smart grasper uses piezoelectric sensors bonded at desired locations to detect the
applied force/momentum by surgeon and to measure the transmitted response to the tissue/organ.
Keywords: Minimally invasive surgery; grasper; force; piezoelectric;sensor.
scissor blades and the tissue. Tavakoli et al. [2] designed
a robotic master slave system for use in minimally
invasive surgery. The system was capable of providing
haptic feedback to the surgeon in all available degrees of
freedom, thus, providing a sense of touch to the user.
Sokhanvar et al. [3] proposed a sensor and modeled it for
both analytically and numerically considerations. They
examined a series of simulations performed in order to
estimate the characteristics of the sensor in measuring
the magnitude and position of a point load, distributed
load, and the softness of the contact object. Shikida et al.
[4] presented an active tactile sensor with ability to
detect both contact force and hardness of an object
simultaneously. Their system involved a diaphragm with
a mesa (a flat-topped projection) at the center, a
piezoelectric displacement sensor at the periphery, and a
chamber for pneumatic actuation. Dargahi [5] proposed a
prototype tactile sensing system with three sensing
elements. The magnitude and position of the applied
force were obtained by utilizing triangulation approach
combined with membrane stress. Narayanan et al. [6]
presented the design and fabrication of a micro machined
piezoelectric endoscopic tactile sensor to determine the
properties of tissues in minimally invasive surgery.
Rosen et al. [7] developed a computerized force
feedback endoscopic surgical grasper with computer
control and a haptic user interface in order to regain the
tactile and kinesthetic information that is lost. The
system used standard unmodified grasper shafts and tips.
The first steps in realizing soft tissue models through the
development of an automated laparoscopic grasper and
tissue cutting equipment to characterize grasping and
cutting tasks in minimally invasive surgery were
discussed by Tholey et al. [8]. Sjoerdsma et al. [9]
measured the force transmission of laparoscopic grasping
forces and bowel clamps and observed that the
mechanical efficiency of the system is lower than 50%.
Okamura et al. [10] developed an algorithm to
simultaneously display translational and cutting forces
for a realistic cutting simulation. They considered two
cutting models: real tissue data, and analytical model.
Although, in the past decade many distinguished
works have been presented in force/momentum sensing,
however, still many problems remain unexplored which
need to be thoroughly investigated before the idea of
1. INTRODUCTION
Minimally invasive surgery (MIS) is a very new
approach in medical operations. It involves inserting
special instruments into the body cavity through tiny
incisions in order to perform surgical procedures (see
Figure 1). Minimally invasive surgery (MIS) challenges
the surgeon’s skills due to his separation from the
operation area, which can only be reached with long
instruments. Therefore, surgeon has not a sense of touch
and sense of forces to recognize the material (tissue and
organs)
properties
and
thus
apply
proper
force/momentum to avoid damage to the tissue/organ. To
overcome these drawbacks, in the last few years many
research works have been presented to provide the sense
of touch in order to help the surgeon to recognize the
material softness/hardness of the tissues.
Figure 1 Procedure of minimally invasive surgery.
Callaghan et al. [1] used direct measurement of
contact forces between a surgical instrument tips for
__________
Manuscript has been presented at International Conference on
Bioinformatics and Biomedical Technology (ICBBT 2009) index
by IEEE Computer Society.
Ramin Hortamani, M.Sc student, School of Science and
Engineering, Sharif university of Technology, International
Campus, Kish Island.
Abolghasem Zabihollah, Ph.D, Department of Mechatronics,
Ext:
351;
fax:
+98-764-4422828;
e-mail:
zabihollah@sharif.edu).
21
smart grasper can find its place in minimally invasive
surgery. The works on giving sense of force to the
surgeon are very scars and mostly limited for remote
tele-operation and robotic surgery. According to the best
knowledge of the authors, sensing force for common
grasper has not been well studied. In the present work an
in-depth comprehensive study has been performed in
which surgeon can sense the amount of force applied to
the tissue and organ.
Figure 2 Model of a real grasper which use in MIS.
⎡[ K dd ] [ K dssψ ]⎤ ⎧ {d } ⎫ ⎧⎪{Fd (t )} − [ K dsaψ ]{ψ a }⎫⎪
(3)
⎢ ss
s ⎬=⎨
ss ⎥ ⎨
s
sa
a ⎬
⎣⎢[ Kψd ] [ Kψψ ]⎦⎥ ⎩{ψ }⎭ ⎪⎩{Q (t )} − [ Kψψ ]{ψ }⎪⎭
2. GOVERNING EQUATION FOR A SMART
GRASPER
Piezoelectricity is a coupling between a material’s
mechanical and electrical behaviors. When a
piezoelectric material is squeezed, an electric charge
collects on its surface (direct effect). Conversely, when a
piezoelectric material is subjected to an electric field, it
exhibits a mechanical deformation (converse effect.
Applying an electric voltage to the electrodes of
piezoelectric material will induce a mechanical
deformation according to the magnitude and sign of
applied voltage. These characteristics can potentially be
utilized to develop and design smart graspers with
capability to sense the force applied by the surgeon.
where superscripts s and a stand for partitioned submatrices in accordance with the sensory and actuator
components, respectively. The left hand side includes the
s
unknown sensor voltage, {ψ } , and the nodal
displacements, {d } . The right hand side includes the
applied mechanical load, {Fd (t )} , applied voltage on the
a
s
actuator, {ψ } and the electric charge, {Q (t )} . The
present works deals with the sensing effect of
piezoelectric elements, so, the actuator’s terms are
removed from the above equation.
According to linear piezoelectric properties, the
governing equations are given by [11] as:
For direct coupling:
D = [e]{ε}-[p]{E}
In this work the theoretical behavior of the system
under different loading conditions has been thoroughly
examined. Modeling is performed based on a realistic
grasper used for MIS. In order to model the loading
effects, it is observed that when biological tissues are
positioned between endoscopic grasper jaws, distributed
loads sometimes mimic the actual grasping mechanism
more closely [12]. However, in the case of a small
contact area between the tissue and the surface of the
grasper, the assumption of point or concentrated loads
suffices in analyzing this phenomenon is adequate. In
fact, the smaller the contact surface, the more realistic a
concentrated load assumption is in the description of the
grasping process [13]. In the next section numerical
illustration are demostarted to show the concept of smart
garsper and present the fontionality and performance of
the system in sensing the applied force.
(1)
And for converse coupling,
σ = [C]{ε}-[e]{E}
(2)
where {σ},{ε},{D} and {E} are the stress, strain ,
electric displacement and electric field vectors, and [C],
[e]and [p] are the elasticity, piezoelectric and dielectric
constant matrices, respectively. According to Equation
(1), one can realize that mechanical strains produce
electrical field which later can be used to provide as an
indicator of sense of force.
3. FINITE ELEMENT ANALYSIS
4. NUMERICAL ILLUSTRATIONS
Real graspers integrated with sensors become very
complex instruments, thus, the electro-mechanical
analysis of this relatively complex mechanisms using
analytical approach is somehow infeasible. Here, a
numerical approach based on finite element method is
employed for this purpose.
The physical shape of a real grasper (Figure 2), can
be simplified and approximated with a cantilever beam
element.
According to the Kirchhoff’s hypothesis, the finite
element model of the smart beam element can be given
by [13]:
In this section, first the present finite element model
is validated using a simplified grasper modeled as a
cantilever beam available in litrature, then, a more
relastic grasper has been considered.
4.1Validating Example
For the validation purpose, the simplified grasper
modeled as a cantilever beam described in Reference
[13] is reexamined here. A cantilever beam integrated
with a layer of piezoelectric sensor at the fixed point as
22
N 1, December 2009
shown in Fiigure 3 is connsidered. Thee material forr the
grasper is brrass with a Yooung’s modullus of elasticitty of
100 GPa annd a Poissonn ratio of 0.34.
0
A layer of
piezoelectricc with dimenssions of 9 mm
m length andd 0.1
mm thick is positioned
p
froom the fixed-eend of the grassper.
This layer is divided to 5 electrodes loccated at 0~1 mm
m ,
2~3 mm,4~5 mm, 6~7 mm
m, 8~9 mm. Thhe beam is 222 mm
in length andd 3 mm in thiickness at fixed end and 2 mm
thickness at tip grasper and
a 4 mm deepth. The incllined
part located in the midddle of the graasper jaws haad a
length of 5 mm
m in the longgitudinal direcction of x.
wn in Figure 5 where one can easily observe that thee
show
high
her the strainn the higher voltage generated at thee
senssors. The maxximum voltagge occurred at the electrodee
locaated near thee fixed pointt where the strain is thee
high
hest.
4.2
4 A more Reealistic Grasp
per
The previous example ddescribed a very simplee
prottotype graspeer, however, a realistic graasper is moree
com
mplicated (seee Figure 2) and consequently thee
mod
deling is veryy important. P
Perhaps modelling the tip off
the grasper is of the highest coomplexity, theerefore, in thee
pressent work thee tip of the grrasper is conssidered for itss
resp
ponse when thhe object/organn is grasped.
With respect to strain in grasper jaw, electrode onn
piezzoelectric layyer generate tthe voltage, these
t
voltagee
hav
ve a relationship with strain..
Figure 3 Graspper tip with the position of appplied force and
defined electroode.
With appplying force on
o the jaw off the grasper,, the
grasper acteed like cantilever beam and as a reesult,
bending stresses grew onn the back facce of the jawss [1]
and as menntioned beforre bending stresses
s
causeed a
generation a voltage in piezoelecctric layer. The
magnitude of the resultingg output voltaage was relateed to
the magnitudde of the appplied forces. Moreover, iff the
distance betw
ween the definned electrodees on piezoeleectric
layer is know
wn, it can be shown that thhe location off the
force applicaation could be
b obtained by
b combiningg the
two output voltage from thhe piezoelectric.
To obtaiin generated voltage on piezoelectric, the
bottom of alll the electrodees are set zero voltage. Firstt, the
force apply at x = 18 mm and gennerated strainn on
piezoelectricc is explored and
a presented in Figure 4.
Figu
ure 5 generated voltage in the ddefined electrod
de respect to
electrode position for
f F =10 N, x =
=18 mm.
The
T grasper tipp is modeled aas Figure 6, th
he grasper jaw
w
has 22 mm in length,
l
3 mm
m in width and
a
4 mm inn
m
is veryy close to thee real grasperr
thicckness. This model
jaw
w commonly used in M
MIS. Here, an
a action iss
inveestigated wheen the graspper grips a subjects likee
rubb
ber, foam andd muscle witth its tooth, which
w
is veryy
sim
milar to the real action of tthe grasper in
n surgery. Inn
ordeer to investiggate the behaavior of geneerated voltagee
and
d strain, it waas decided too employ a tw
wo parameterr
Mooney–Rivlin for each maaterial [1]. The
T
Mooney––
Riv
vlin constants used
u
are show
wn in Table 1.
The grasped object assum
mes to be a hyperelasticc
matterial with 9.2 mm in diameeter.
Figure 7 shhows the squueeze of thee object andd
gen
nerated strain in
i the object aas a result of applied
a
force.
As discussed before, the sttrain and voltaage on PVDF
F
are proportional, so with this sstrain we havee a voltage onn
PVD
DF sensor whhich shown in Figure 8.
Figure 4 Strainn variations witth respect to thee longitudinal
distance on thee top surface off the grasper forr F =10 N and x =
18 mm.
Taable 1 Hyperelaastic constant
It is noteed that the errror between the
t present results
and the resuults publishedd in Referennce [12] is inn an
acceptable raange.
Further, the
t same probblem is investtigated for volltage
generated at the sensors. The
T corresponnding voltagess are
Subject
Rubber
Foam
Muscle
23
C10 (MP
Pa)
0.293
0.382
0.03
C01 (MPa)
0.177
0
0.096
0
0.01
0
N 1, December 2009
45
Muscle
Foam
Rubber
40
R eaction fo rce (N )
35
30
25
20
15
10
5
0
-5
0
Figure 6 Deetailed drawing of the jaw of thhe endoscope
grasper
2
2.5
3
3.5
4
-3
x 10
First,
F
a protootype grasperr simplified by a simplee
canttilever beam available
a
in liiterature is used to validatee
the present approoach. Then, a rrealistic grasp
per is modeledd
usin
ng the develloped finite element mod
del. Differentt
matterials in contaact with the ggrasper’s jaw are
a utilized too
observe the functionality of thhe system and
d to study thee
elecctro-mechaniccal response oof the smart sy
ystem. It wass
observed that thhe higher the strain the higher voltagee
gen
nerated at the sensors. Anoother feature of
o importancee
reallized was thatt the reaction forces generaated at the tipp
of the
t grasper’jaaw are correspponding to th
he softness off
the materials annd thus, propportional to the
t
generatedd
volttages at the seensors.
The
T results off the present work may potentially
p
bee
used
d to design annd fabricate a new generatio
on of grasperss
with
h capability to
t alert the ssurgeon for any
a excessivee
forcce and thus preventing from
m any possib
ble damage too
the tissue/organ. Using the nnew graspers, surgeons cann
opeerate with lessser fault. Thhe smart grassper help thee
stud
dents and innstructors byy maintaining
g a definedd
stan
ndard force foor grasping tisssue and woulld also ensuree
few
wer traumas too the patient by decreasin
ng the risk off
dam
maging levels of tissue com
mpression. Other applicationn
of the
t smart grassper is helping any surgeon
n and studentt
to learn minim
mally invassive surgery in virtuall
env
vironment.
It is realiized that musccle cause the lowest voltagge at
the sensors and
a subsequenntly, foam takees the second rank
and the highhest value is for the rubbber. It is exaactly
proportional to the stiffneess of each material.
m
Similarly,
f
generatted at the tip of
o the grasperr’jaw
the reaction forces
are correspoonding to the softness of the
t materials and
thus, proporrtional to thhe generated voltages at the
sensors.
-8
G enerated voltage (v)
1.5
Tip displlacement (m)
CONCL
LUSION
A new design for a MIS ggrasper is developed whichh
can provide the sensing abilitty of force ap
pplied by thee
surg
geon. A num
merical approoach based finite
fi
elementt
metthod is utilizeed to investigaate the perforrmance of thee
new
w design in sennse of force.
Figure 7 Grasper jaw after
a
applied forrce
x 10
Muscle
Foam
Rubber
1.4
1
Figu
ure 9 Reaction force by appliied displacemen
nt for differentt
subjject
For materrials with highh stiffness gennerated strainn and
respect to sttrain generateed voltage iss higher thann the
material withh lower stiffneess. Consideriing the softnesss of
materials annd applied dissplacement onn each subjecct, a
reaction forcce will generaated at the jaaw tip which this
result for eacch material shoown in Figuree 9.
1.6
0.5
1.2
1
0.8
0.6
0.4
AKNOWLD
DGEMENT
Thee authors wish
w
to thannk Sharif University
U
off
Tecchnology, inteernational Cam
mpus, Kish Island
I
for thee
supp
ports providedd through thiss work.
0.2
0
0~0.024
0.048~0.073
0.097~0.122
PVD
DF sensor location
0
0.146~0.171
0.1996~2.2
Figure 8 Geenerated voltagees by applied displacement
d
forr
different subjeect
24
REFERENCES
[1] Dean J. Callaghan, and Mark M. McGrath,” A Force
Measurement Evaluation Tool for Telerobotic
Cutting Applications: Development of an Effective
Characterization Platform” International Journal of
Mathematical, Physical and Engineering Sciences,
Vol 1, no 3 (2007).
[2] M. Tavakoli, R.V. Patel and M. Moallem.” A Force
Reflective Master-Slave System for Minimally
Invasive Surgery”, Intl. Conference on Intelligent
Robots and Systems, Las Vegas. Nevada, Oct 2003.
[3] S. Sokhanvar, M. Packirisamy and J. Dargahi, “A
multifunctional PVDF-based tactile sensor for
minimally invasive surgery, “Smart Mater. Struct.
Vol.16 (2007) 989–998.
[4] Shikida M, Shimizu T, Sato K and Itoigawa K 2003
Active tactile sensor for detecting contact force and
hardness of an object Sensors Actuators A, vol. 103
(2003) 213–8.
[5] J. Dargahi, “A piezoelectric tactile sensor with three
sensing elements for robotic, endoscopic, and
prosthetic applications”, Sensors and Actuators, vol.
80 (2000) pp 23–30.
[6] N. B. Narayanan, A. Bonakdar, J. Dargahi, M.
Packirisamy and R. Bhat,” Design and analysis of a
micromachined piezoelectric sensor for measuring
the viscoelastic properties of tissues in minimally
invasive surgery,” Smart Materials and Structures,
vol. 15 (2006) pp.1684–1690.
[7] J. Rosen, B. Hannaford, M. P. MacFarlane, and M.
N. Sinanan, “Force Controlled and Teleoperated
Endoscopic Grasper for Minimally Invasive Surgery
Experimental Performance Evaluation”, IEEE
Transaction on Biomedical Enginering, vol. 46, no.
10, Oct (1999).
[8] G. Tholey, T. Chanthasopeephan, T. Hu, J. P. Desai,
and A. Lau, “Measuring grasping and cutting forces
for reality-based haptic modeling”, Pro.17th Int.
Congress and Exhibition Computer Assisted
Radiology and Surgery, London, U.K., vol. 1256,
(2003) pp. 794-800.
[9] W.Sjoerdsma, JL.Herder, MJ.Horward, A.Jansen,
J.Ban enberg,CA.Grimbergen, “Force transmission
of laparoscopic grasping instruments”, Minimally
Invasive Therapy & Allied Technologies vol. 6, no.4,
(1997) pp 274-278.
[10] A. M. Okamura, R. J. Webster, J. T. Nolin, K. W.
Johnson, and H. Jafry, “The haptic scissors: Cutting
in virtual environments”, Proc. IEEE Int. Conf.
Robot. Autom., Sep. (2003), pp. 828–833.
[11] Y.C. Fung, Biomechanics: Mechanical Properties of
Living Tissues, 2nd ed., New York: Springer Verlag,
(1993).
[12] J. Dargahi, S. Najarian, “An endoscopic forceposition sensor grasper with minimum sensors”,
Canadian Journal of Electrical and. Computer
Engineering, vol. 28, no. 3/4, (2003) pp. 155-16.
25
Manipulability Analysis for Gimbal Driven Robotic Arms
Foad Mohammadi, Iman Hemmatian, Kambiz Ghaemi Osgouie
Abstract: Gimbal transmissions are non-linear direct transmissions and can be used in robotic arms
replacing the traditional revolute joints. To investigate manipulability of robotic manipulators, the
classical criterion of Manipulability Ellipsoid has been formulated. Thus by keeping a constant norm for
robot joint torques vector, the effects of replacing some traditional revolute joints in robotic arms with
Gimbal transmissions, have been analyzed. The results show that the magnitude of the maximum force
applicable when employing Gimbal transmission can be considerably larger. Also, the joint angles in
which this maximum occurs, can be adjusted, thanks to the behavior of Gimbal transmission. Two
simple robotic arms – a 3R manipulator and Stanford Arm – are selected to investigate the effects of
Gimbal transmissions.
Keywords: Gimbal joint, Manipulability ellipsoid, Direct transmission, Maximum task-space force
force
1.
gyroscope is rotated. The Gimbal mechanisms are also
implemented in control moment gyroscopes (CMG).
CMGs have traditionally been used for attitude control of
spacecraft. They are torque-generating mechanisms
consisting of a rotating flywheel as well as a wheel-tilting
actuator. These single- or double-Gimbaled actuators are
typically used for agile, high-rate maneuvers. The use of
this mechanism in Control Moment Gyroscopes (CMGs)
is investigated in [8].
In this paper kinematics of a typical Gimbal
transmission has been considered in the first section. The
relations between input and output variables and
adjustment parameters are investigated. In section III the
concept of manipulability ellipsoid is formulated. It is
employed to evaluate the manipulability of robotic arms.
Manipulators with traditional revolute joints and those
with Gimbal transmission joints are then compared in
section IV. It is shown that employing Gimbal
transmissions, increases the maximum applicable force at
the desired work-point.
INTRODUCTION
By the necessity of more accurate and efficient robotic
systems in technology, the drive systems for robot
manipulators became important. The problems associated
with traditional transmission methods like gearboxes, such
as friction, backlash and compliance, and the development
of electric motors for robotic applications, led to a new
design approach called direct-drive (DD) transmission [1].
In this method the shaft of the motor is directly coupled to
the joint of the manipulator. The problem associated to
this kind of transmission is that the weight of the motors
attached to robot joints reduces the payload. So existence
of an intermediate element that provides relocation
becomes important, leading to a design, named direct
transmission (DT) [2]. This transmission method has
higher performance than DD, however, because dynamic
complexities – like coupling and non-linearity – are
directly reflected on the motor shaft, one cannot use
common single-input single-output (SISO) control
techniques to control the robot [3]. This problem can be
resolved using more advanced control methods like
model-based [4] or computed torque control [5]. Another
way is to redesign the manipulator to reduce dynamic
complexity [6]. Vines [2] proposed non-linear drive
transmission which has the advantages of DT and
reduction ratio properties of gearboxes. It has very little
friction, backlash, and compliance compared to the
traditional methods, while providing actuator relocation,
directness of DD, and a varying reduction ratio. The
Gimbal drive, shown in Figure 1, is a good example of
non-linear direct transmission elements. It has all the
advantages mentioned for DT mechanisms.
Gimbal mechanisms are also used in mechanical
gyroscopes [12]. The Gimbal provides the gyroscope the
freedom to rotate about its axis as the base of the
2.
THE GIMBAL DRIVE
In Figure 1 a typical, one degree-of-freedom, Gimbal
drive is shown. To describe its kinematics, the following
matching function is considered [2]:
θ
θ
_
tan
tan θ . cos θ
Manuscript has been presented at IEEE International Conference on
Robotics and Biomimetics (ROBIO 2009).
Foad Mohammadi and Iman Hemmatian are with Sharif University
of Technology – International Campus in Kish Island, Iran.
Kambiz Ghaemi Osgouie, Ph.D, Department of Mechatronics,
Sharif University of Technology, International Campus Kish Island,
Iran. (Corresponding author to provide phone: +98-764-4422299 Ext:
Figure 1 The Gimbal drive 339; fax: +98-764-4422828; e-mail: osgouie@sharif.edu).
26
(1)
reduction ratio increase as
increases.
The relationship between the reduction ratio and output
angle θ
is shown in Figure 3b. It shows that for every
output angle there are two reduction ratios associated with
equal value and opposite sign, it is based on the fact that
for every output angle there exist two input angle
configurations (Figure 2). From eq.
(1) and Figure 2 it
can be deduced that for every output angle there are two
possible input angles. However, Figure 3 a depicts that for
every input angle, there exists just one reduction ratio.
Thus for every output angle there should be two reduction
ratios associated. This fact signifies the importance of
as a design parameter. For greater values of
, greater
values of reduction ratios are achievable.
Figure 2 Transfer characteristics of Gimbal drive is the input angle (angle of rotation of the
In which,
vertical shaft), θ is the output angle (angle of rotation of
the horizontal shaft/frame),
is the gradient of the
truncated cylinder, and
is the offset angle at the
_
output. In Figure 2 the input/output relationship for a
Gimbal drive is shown, considering different truncation
gradient angles. It can be deduced that the gradient of the
, is a design parameter because it
truncated cylinder,
sets the range of output angle. As is increased, the
range of the output angle,
, increases. To get a desired
range for the output angle, proper truncation gradient shall
be taken.
The derivative of the matching function
(1), with
respect to the input angle,
, represents the reduction
ratio ( ) of the Gimbal drive:
. sin
tan
1 tan . cos
3.
PROBLEM DECLARATION
So far, the qualities of the single-input single-output
Gimbal transmission were discussed. Achieving adjustable
transmission ratio, suggests using Gimbal transmissions in
robotic arms to obtain a desired manipulability. That is to
say, considering the workspace of a manipulator and the
desired velocity/force values at certain work-points, one
may employ Gimbal transmissions to the joints of the
manipulator, to be able to adjust desired manipulability.
To investigate manipulability qualities, here the classical
criterion of r ellipsoid is formulated for manipulators with
traditional revolute joints. It is compared to the same
quality of the same arm in which some joints are
substituted with Gimbal transmissions.
In order to find the maximum achievable force at the
manipulator’s tip point, the classical hypothesis is to
assume that the Euclidian norm of the joint torques
remains unity (this is to bound the joint torques)[9]. That
is:
(2)
In Figure 3a the variations of reduction ratio of the Gimbal
for
transmission is shown versus the input angle
different values of . It can be seen that for positive
values of the input angle, the reduction ratio becomes
negative, thus changing the motion direction of the output
angle. It is good to mention that for input angles equal to
90 and -90 degrees, reduction ratio has its minimum and
maximum values, respectively. The sign of reduction ratio
changes when the input shaft rotates 180 degrees. It is also
shown that the maximum and minimum values of
(3)
.
1
The
relation of task-space force
and the vector of joint
torques is:
(4)
τ JT . F
In which J is the Jacobian of the whole manipulator.
By substituting (4) in (3), one obtains:
. .
.
1
Figure 3 Reduction ratio property of Gimbal drive: (a) reduction ratio vs. input angle, (b) reduction ratio vs. output angle 27
(5)
are traditional revolute joints, is:
Relation (5) changes the hyper-sphere of the joint forces
(3), into a hyper-ellipsoid that is called the resistivity
ellipsoid. This method is largely employed to evaluate the
manipulability qualities of robotic arms [10].
The aim here, is to achieve greater force in a specified
direction using Gimbal mechanism. The task-space force
vector is expressed as:
.
.
In which is the magnitude of
length on the direction of .
Substituting (6) in (5) yields:
.
. .
.
1
2
1
2
0
is a vector of unit
1
(8)
(7)
(9)
Thus, one may determine the magnitude of the applicable
force in a desired direction at a specific point of
manipulator’s workspace. By comparing the magnitude of
the applicable force, f , for different types of manipulators
one is able to recognize the efficient robot design, and if
using Gimbal transmissions instead of the traditional
revolute joints improves robot’s manipulability.
4.
1
2
1
2
1
2
Now it is desired to use Gimbal transmissions at joints 2
and 3. To obtain new Jacobian matrix, one shall substitute
from
(1) for
and of the 3R spatial robot.
0
,
45° , the Jacobian matrix for
Assuming
_
the manipulator with Gimbal transmissions at joints 2 and
3, becomes:
(6)
and
1
2
1
2
1
2
1
2
1
2
1
1
2
1
2
CASE STUDIES
Two cases are selected to investigate the effects of Gimbal
transmissions in robotic manipulators. For each case a
simple manipulator is considered and using eq. (7) its
manipulability is investigated.
A. 3R Spatial Robot
1
1
1
1
1
2
1
1
2
1
1
0
First a 3R spatial robot, shown in Figure 4, is
investigated to analyze the advantages of Gimbal drive in
robot joint transmission.
Here, for convenience, … and … are used instead of
and
functions,
respectively. Assuming
0.5 ,
1 ,
the Jacobian matrix of the 3R spatial robot, when all joints
1
2
1
1
2
1
1
1
In which JG is the Jacobian of the manipulator when a
Gimbal transmission is used at joints 2 and 3.
Figure 5 Variations of the applicable force versus
and for the 3R robot with traditional revolute joints
Figure 4 3R Spatial Manipulator [11] 28
,
and ,
for the 3R robot with Gimbal transmissions at joints 2 and 3
Using Manipulability ellipsoid, we compare f for the
simple and Gimbal equipped 3R spatial robots. Figure 5
shows variations of the applicable force, f , with respect
and , for the robot with traditional revolute joints
to
0. The desired direction of the force vector is
when
described as dx dy dz 1. Figure 6 shows variations
of the applicable force,
, versus joint variables θ and
θ for the robot equipped with Gimbal transmission at
joints 2 and 3.
By comparing Figure 5 and Figure 6, it can be deduced
that the Gimbal equipped robot represents better behavior
in terms of smoothness and higher achievable forces.
Maximum force achievable for the simple 3R spatial robot
is 1.9962 N and the corresponding value for the same
robot with Gimbal transmissions at joints 2 and 3 is 2.4495
N. This means the same manipulator can exert greater
forces when its simple revolute joints are substituted with
Gimbal transmissions. Also it is considerable that for
positions near
0 the magnitude of force is
maximum when Gimbal transmissions are used and by
getting far from this point it is decreased. As explained in
section II, Gimbal transmissions are adjustable
mechanisms. Thus the maximal point shown in Figure 6
can be set to occur in a desired work-point. This is one of
the outstanding achievements of employing Gimbal
transmissions.
Figure 7 Stanford Arm and corresponding joint frames and
variables [12]
1
1
1
1
1
1
1
(11)
1
0
1
1
In which JG is the Jacobian of the manipulator when a
Gimbal transmission is used at joint 2.
Again using Manipulability ellipsoid analysis, we
compare the maximum applicable force, , for Stanford
arm with traditional revolute joints and the arm equipped
with Gimbal transmissions at revolute joint 2. To this end,
(the joint variable of the arm’s mere prismatic joint) is
set to 1 . The direction of the desired force vector is
assumed to be
1. Figure 8 shows
variations of the applicable force, f , versus joint variables
and
for Stanford Arm with traditional type joints.
Figure 9 depicts variations of the applicable force, f ,
versus joint variables
and
for Stanford Arm
equipped with Gimbal transmission at joint 2.
As it can be concluded from Figure 8 and Figure 9, the
maximum applicable force exerted by the Gimbal
equipped Stanford Arm is much greater than that without
Gimbal transmission. The maximum value of f for the
simple Stanford Arm is 1.7212 N while the corresponding
value for the Stanford Arm with Gimbal at joint 2 is
5.3783 N.
Another case investigated here is the Stanford Arm
shown in Figure 7.
The Jacobian matrix for Stanford Arm , assuming
1 ,
0.5 is:
0
1
2
1
B. Stanford Arm
1
2
1
2
1
2
(10)
Using Gimbal drive at joint 2 the new Jacobian matrix is
obtained by substituting from
(1) for
in
(10).
0,
45° , the Jacobian matrix is
Assuming
_
derived:
29
Figure 8 Variations of the applicable force versus θ and
θ , for Stanford Arm with traditional revolute joints
and
, for Stanford Arm with Gimbal transmission at joint 2 To have a better comparison between the two
configurations, Figure 10 and Figure 11, show the
when the joint variable of the
variations of f versus
first joint is kept
0 . As for the 3R robot discussed in
previous part, it is considerable that when the joint is
Gimbal equipped, maximum applicable force occurs at
0. The magnitude of the maximum force applicable
when employing Gimbal transmission is considerably
larger. Besides, one can set not only the joint angle
in
which this maximum occurs, but also the slope of the
curve by which the applicable force decreases when
is
changed. These two settings are made by adjusting
_
and respectively.
5.
Figure 10 Variations of the applicable force versus θ ,
for Stanford Arm with traditional revolute joints
Figure 11 Variations of the applicable force versus θ ,
for Stanford Arm with Gimbal transmission at joint 2
by which one is able to adjust an offset for the
_
Gimbal transmission. At the next step, the effects of
Gimbal drive on the force exerted by robotic manipulators
were investigated using Manipulability Ellipsoid. Two
famous manipulators, 3R spatial robot and Stanford Arm
were selected to investigate the effects of Gimbal
transmissions. When some simple revolute joints were
replaced with Gimbal transmissions, the maximum
applicable force at the tip point of robot, were compared to
the case with traditional revolute joints. Smoothness of the
relation between input and output of the Gimbal drive
shown represents the most desirable motion and force
behavior for a manipulator. The results confirm that
Gimbal drive is a novel design as a joint of a manipulator
and can be optimized for improving the performance of
robots based on their applications. The magnitude of the
maximum force applicable when employing Gimbal
transmission can be considerably larger. Besides, one can
set not only the joint angles in which this maximum
occurs, but also the slope of the curve by which the
applicable force decreases when joint angles are changed.
CONCLUSION
The effects of using Gimbal mechanisms as non-linear
direct transmissions in robotic arms have been analyzed.
The input/output behavior of the Gimbal drive and its
reduction ratio were formulated. Depending on the
,
application, different values of truncation gradient,
can be used to satisfy the range of output angle and
reduction ratio needed. Another setting parameter is
30
These two settings are made by adjusting
respectively.
_
and
REFERENCES
[1] H. Asada, K. Youcef-Toumi, Direct-drive robots:
theory and practice, Cambridge, MA: MIT Press,
1987.
[2] P.J. Turner, P. Nigrowsky, G. Vines, “A new
approach for the design of robot joint transmission,”
Mechatronics, vol. 11, 2001, pp. 1053-1062.
[3] H. Asada, K. Youcef-Toumi, “Analysis and design
of a direct-drive arm with a five-bar-link parallel
drive mechanism,” ASME Transactions: Journal of
Dynamic Systems, Measurment, and Control, vol.
106, 1984, pp. 225–30.
[4] H. Berghuis, H. Nijmeijer, “A passivity approach to
controller-observer design for robots”, IEEE
Transactions on Robotics and Automation, vol.
9(6), 1993, pp. 740-754.
[5] CH An, CG Atkenson, JD Griffiths, JM Hollerbach,
“Experimental evaluation of feed-forward and
computed torque control,” IEEE Transactions on
Robotics and Automation, vol. 5(3), 1989, pp. 368373.
[6] H. Kazerooni, S. Kim, “On the design and
construction of direct-drive robots,” ASME
Transactions: Journal of Engineering for Industry,
vol. 112, 1990, pp. 197–201.
[7] B. Siciliano, O. Khatib, Springer Handbook of
Robotics, Springer-Verlag Berlin Heidelberg, 2008,
pp. 478-485.
[8] Robert J. Bauer, “Kinematics and dynamics of a
double-Gimbaled control moment gyroscope,”
Mechanism and Machine Theory, vol. 37, 2002, pp.
1513-1529.
[9] J.P.Merlet, Parallel Robots, , Springer-Verlag
Berlin Heidelberg, 2nd edition, , 2006, pp. 260-266.
[10] Kambiz Ghaemi Osgouie, Ali Meghdari, and Saeed
Sohrabpour, Optimal configuration of dual-arm
cam-lock robot based on task-space manipulability.
In: Robatica 2008, Cambridge University Press.
[11] J. J. Craig, Introduction to Robotics: Mechanics and
Control, Pearson Prentice Hall, 2005, pp. 90-100.
[12] K. S. Fu, R.C. Gonzalez, C.S.G. Lee, Robotics :
Control, Sensing, Vision,
And intelligence,
MacGraw Hill, 1987, pp. 37-40.
31

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