Robust Control for the Motion Five Fingered Robot Gripper.
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International Journal of Mechanical Engineering
and Robotics Research
CONTENTS
Volume 4, Number 3, July 2015
Numerical and Experimental Investigations on Heat Transfer of Aluminum Microchannel Heat Sinks with
Different Channel Depths ................................................................................................................................... 204
Ngoctan Tran, Yaw-Jen Chang,, Jyh-tong Teng, and Thanhtrung Dang
Absolute Stability of Mechatronic Module with Intelligent Controller Based on Associative Memory ............ 209
Nikolai N. Karabutov, Valery M. Lokhin, Sergey V. Manko, and Mikhail P. Romanov
A Novel Tuning Algorithm for Fractional Order IMC Controllers for Time Delay Processes........................... 218
Cristina I. Muresan, Eva H. Dulf, and Roxana Both
Static Analysis on Suitable Arrangement of Tubes of Low-Cost Control Valve Using Buckled Tube .............. 222
Abdul Nasir, T. Akagi, S. Dohta, and O. Ayumu
Robust Control for the Motion Five Fingered Robot Gripper ............................................................................ 226
W. Widhiada, T. G. T. Nindhia, and N. Budiarsa
Extension of the Upper Extremity with Shoulder Movements ........................................................................... 233
Nobuaki Nakazawa and Toshikazu Matsui
Autonomous Mobile Robot Self-Learning In Motion Planning Problem .......................................................... 238
Sergey V. Manko, Valery M. Lokhin, Sekou A. K. Diane, and Alexander S. Panin
Modeling of Facility Location Problem for Reverse Logistics System with Uncertainty in Forward and Reverse
Flows of Products ............................................................................................................................................... 242
Saif Ullah, Guan Zailin, Xu Xianhao, He Zongdong, Wang Baoxi, and Mirza Jahanzeb
Comparisons of Break Points Selection Strategies for Piecewise Linear Approximation.................................. 247
Ming-Hua Lin and Jung-Fa Tsai
Application of Biogeography-Based Optimisation for Machine Layout Design Problem ................................. 251
Saisumpan Sooncharoen, Srisatja Vitayasak, and Pupong Pongcharoen
Solving Cold Start WithLebiD2.......................................................................................................................... 255
Lebi Jean Marc Dali and Qin Zhi Guang
International Journal of Mechanical Engineering and Robotics Research Vol. 4, No. 3, July 2015
Robust Control for the Motion Five Fingered
Robot Gripper
W. Widhiada, T. G. T. Nindhia, and N. Budiarsa
University of Udayana, Denpasar, Indonesia
Email: {widhiwyn, nindhia}@yahoo.com, budiarsa_nyoman@yahoo.co.id
proper gripper design can simplify the overall assembly,
improving overall reliability system, and reduce
implementation costs, and grippers have been widely
used for automated manufacturing, assembly and
packaging, etc. [3].
During the last three decades, the application of robotic
grippers has gradually developed for grasping a variety of
tasks from using a simple mechanism to multiple degree
of freedom of design. Most robotic grippers have been
specifically designed only to grasp on certain traditional
forms of object. In this study the author has researched
into the design, analysis and synthesis of sophisticated of
five fingered gripper.
The design of a gripper finger is a difficult task with
many considerations such as task requirements, geometry
of gripper and the complexity of mechanism[4].
Traditionally, a physical prototype is necessary to truly
test a hand’s ability to perform a variety of tasks, but this
can be quite costly with potentially many design
iterations being required. However to reduce prototyping
costs, simulation techniques provides another tool which
enables the modern designer to model (simulate) the
kinematics and dynamics of physical systems and to
quickly investigate the performance of the design.
Simulation has been recognized as a powerful tool for
supporting the design, planning, and analysis of dynamics
performance of robotic grippers [5]. In this work
simulation results and visualization of the dynamics of a
robotic gripper are presented.
In this research study, the author has focused upon
investigating how to develop the modeling and
controlling the dexterous of five fingered gripper. The
gripper finger can grasp and manipulate the engineering
component. In this study, authors will build both a design
and a prototype robot gripper five fingers. This gripper
design will resemble a human hand. This robot will have
11 rotary joints (revolute joint). PID control is used to
control the kinematics and dynamics robot gripper to
achieve the best performance include quickly response
and high accuracy respectively.
The application of PID control in simulation for the
five fingered gripper is capable to accelerate the motion
response gripper fingers. Quickly response makes driving
a small error signal so as the calm conditions (steady state)
will be obtained very quickly as well. PID control system
design with Matlab software is robust control to achieve
the good performance [6].
Abstract—The design of multi-fingered robot hands have
been one of the major research topics since grasping an
object and are crucial functionalities of several robotic
systems, including industrial robots, mobile robots and
service robots. The author considers the problem of modelbased control for a multi-fingered robot hand. This paper
introduces an integrated design process for the design of the
five fingered gripper suitable for dexterous motion by using
simulation and experiment of prototype. To facilitate an
integrated design of gripper finger, the author applied
Matlab/Simulink (SimMechanics) and Inventor software
packages, respectively. Multi-closed loop with the robust
control of PID is applied to control both kinematics and
dynamics motions of the five fingered gripper systems. To
obtain the optimal trajectory planning approach using
motion reference and integration of planning control for
virtual actuators at each joint of finger gripper system. The
analysis of experiment result shows the trajectory angular
position of each finger link moves towards quickly to
achieve the trajectory angle target with small error signal
and overshoot.
Index Terms—multi fingered robot, kinematics
dynamics motions, robust control of PID.
I.
and
INTRODUCTION
Robot technology has seen development to support
both the needs of industry and human life. In human
interaction the robot is usually considered to interact with
the end user using ‘hands’ whist in industrial activity the
‘hand is usually termed as a ‘gripper’. The robotics
programmed to accomplish complex issues that interact
with the environment.
Robots designed to interact with humans in a human
manner will often require the hands and such robotic
systems are referred to as humanoid. There are several
published studies into the development of human hand
behaviour into humanoid [1]. Other humanoid research
has been more focused on applications such as humanoid
robot [2]. In each of these cases their hands have been
designed to conform to different criteria.
A robot gripper is the physical realization of an
electromechanical system to perform physical handling
tasks automatically. A robot griper is an essential element
of the robotic system and it is designed to suit industrial
application to typically grasp, carry, manipulate and
assemble the components. Greg Causey has shown that
Manuscript received March 10, 2015; revised June11, 2015.
© 2015 Int. J. Mech. Eng. Rob. Res.
doi: 10.18178/ijmerr.4.3.226-232
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International Journal of Mechanical Engineering and Robotics Research Vol. 4, No. 3, July 2015
II.
of mechanical systems. A fundamental of this work is the
use of Matlab/Simulink Toolboxes to support the
simulation and understanding of the various dynamics
systems and in particular how the SimMechanics toolbox
is used to interface seamlessly with ordinary Simulink
block diagrams to enable the mechanical elements and its
associated control system elements to be investigated in
one common environment.
The design process, simulation and experiment method
for the five fingered robot gripper is shown in the flow
chart of research in Fig. 2.
METHODOLOGY
A. Research Description
From 1978 to 2011, the work undertaken on gripper
design has gradually developed from simple kinematic
arrangements into the multi-degree of freedom design.
From the evaluation of gripper design, and the functional
needs for assembly the author’s has identified that a fivefingered gripper with multi-degree of freedom is the
minimum needs for the dexterous assembly of
engineering elements.
Computer aided design software package is a powerful
tool to design any physical system in 3D solid modelling
in a virtual environment. CAD is especially useful for
author to design multi-degrees of freedom (DOF) gripper
finger. However, the author needed several software tools
to design and control the dynamics performance of a five
fingered gripper. This research study addresses the
integration of two software packages; Inventor and
MATLAB/Simulink/SimMechanics.
Using SimMechanics, it becomes possible to model
and simulate mechanical systems with a suite of tools to
specify bodies and their mass properties, their possible
motions, kinematic constraints and coordinates system
and to initiate and measure body motions [7]. In this work
simulation results and visualization of the dynamics of a
robotic gripper are presented.
The design of robot finger is made in Inventor
Software as follow the dimension of human finger. The
illustration of finger design transfer from 3D to block
diagram in MATLAB/Simulink is shown in Fig. 1. The
finger design in 3D will be exported in form of xml-file
and
it
change
to
diagram
block
in
MATLAB/SimMechanics. SimMechanics tool provides a
reserve to deriving equations and performing them with
base blocks. To create a SimMechanic model, the
mechanical system should be break down into the
building blocks.
Figure 2. Flow chart of research
B. Architecture of Robot Finger
In order to demonstrate the expediency of the
described robot hand approach, authors have developed a
three fingered hand prototype by developing model in a 3
dimension model with Solid works software [9].
Actuators, position sensors and force sensors have been
integrated in the hand structure.
Figure 1. The process of design robot gripper
Simulation has been identified as a significant study
tool for robotic systems since the early of the 20th
century [8] and now simulation methods area powerful
tool supporting the design, planning, analysis, and
decisions in different areas of research and development.
Now, Simulink has developed in many directions: adding
more blocks, built-in algebraic loop solving, and a
physical modeling of toolboxes.
The author has shown through the demonstration of
simulation that it is suitable for the fundamental building
© 2015 Int. J. Mech. Eng. Rob. Res.
Figure 3. Five fingered gripper design
The dexterous robot gripper is equipped with four
identical fingers (index, middle, fourth, little finger) and a
thumb. An actuator is installed in each joint of the fingers
227
International Journal of Mechanical Engineering and Robotics Research Vol. 4, No. 3, July 2015
each of which is presented to a single joint to drive it
individually. The reference signals for these controllers
are supplied by a joint trajectory generator determining
the desired joint trajectory from the desired trajectory of
the mobile robot.
and thumb. The joints of the finger, the distal
interphalangeal (DIP), proximal interphalangeal (PIP)
and metacarpophalangeal (MCP) joints each have 1 DOF
to provide a rotation movement. The architecture of the
five fingers is show in Fig. 3.
The thumb has been designed in order to complete the
hand and it has two degrees of freedom. The thumb is
both able to flex and extend. The index, middle, forth and
little finger prototypes have been designed such that each
finger has three degrees of freedom. In order to simulate
the finger motions each revolute joint has an associated
Servo DC motor attached to it. The extension finger tip is
also controlled using a DC motor Servo driving a rack
and pinion.
C. Mathematics Model for DC Servo Motor
DC servo motor is used to drive six joints in finger
robot. The author presents the mathematics model for DC
servo motor as follows.
ߠሺݏሻ
ܭ௧
ൌ
ሺͳሻ
ܽܧሺݏሻ
ݏሾܮ ݏܬଶ ሺܮ ݂ ܴ ܬሻ ܴ ݂ ܭ௧ ܭ ሿ
where,
Ra= armature resistor, ohm
La= armature inductance, Henry
ia= armature current, ampere
ea= applied armature voltage, volt
eb= feedback voltage, volt
T= torque motor, N-m
J= Moment inertia motor, kg-m2
f=Coefficient viscous motor and load, N-/rad/sec
The equation 1 is the transfer function of DC servo
motor which is used to drive the motor in each finger link.
The mathematics model is applied in block simulink and
illustrate in Fig. 4.
Figure 4. The transfer function of DC servo motor
D. Trajectory Line
The trajectory planning is necessary to generate the
reference inputs to the motion control system, which
ensures that the gripper robot executes the planned
trajectories. The minimal set of requirement for a gripper
robot is to be able to run from an initial position to a final
assigned position.
The input of trajectory planning algorithm is the path
description, the path constraints and the constraints
imposed by a gripper robot dynamics, whereas the
outputs are the joint trajectories in terms of a time
sequence of the values attained by position, velocity and
acceleration.
Position control is used when the robot finger must be
moved with or without load along a prescribed trajectory
through the mobile robot workspace. The control system
of mobile robot is merely a collection of joint controllers
© 2015 Int. J. Mech. Eng. Rob. Res.
228
E. Robust Control Strategy
The control of robot hand is responsible for ensuring
that the hand firmly grasps and that corresponding finger
in the presence of external forces applied to the object.
These forces may require high values of contact force at
the fingertip to get the stability response. To solve these
problems Kazerooni in 1990 published a control law
adopted the relationship between the interaction force and
position trajectory [10].
A considerable body of research has been undertaken
on robotic hand system with robot force control and
planning related to the entire device and the significant
developments are as follows,
Okada developed robotic hand to handle objects which
is suitable to suppress the rapid change of the grasping
condition during a complex finger motion. The finger
control consists of a hybrid position/torque servo
implemented in hardware. Robot hand Okada has shown
to understand and manipulate objects under position
control mode [11].
Salisbury had presented control algorithms for
achieving the stable force control and involving the
relation between position and applied force, stiffness
control with feedback of position only and stiffness
control with force feedback correction [12]. This force is
converted to joint torque commands and the resulting
endpoint motions. Force control has been applied to robot
hands [13] and [14]. The implementation of a controller
and a brief of description of programming language for
the Salisbury hand were presented [15]. He introduced
the concept of a grasp frame that is calculated as a
function of the positions of the finger tips. A summary of
issues involved in low level control of the Utah-MIT
hand was presented [16].
The impedance control methods are developed for
dexterous robot fingers which has relation between
velocity and applied force [17]-[18] and [19].
In 1997 DLR’s dexterous four robot hand is designed
as a dexterous robot hand with a semi anthropomorphic
design. The application of robotics hand systems in
unstructured environments required the dexterous
manipulation abilities and facilities to perform complex
remote operations. Therefore this robot hand has
developed both of new design sensors as 6 DOF fingertip
force torque sensor and integrated electronics with new
communication architecture [20].
Bekey proposed the control strategy of Belgrade robot
hand focused on how to find suitable grasp postures and
poses for the task and how to use the multi-dimensional
grasping quality in grasp mode selection and performance
evaluation in an industrial assembly domain [21]. The
Belgrade robot hand is used to graspa variety of objects
and capable to adapt while applying simple control
architecture based on the principles of non-numerical
control to drive the hand.
International Journal of Mechanical Engineering and Robotics Research Vol. 4, No. 3, July 2015
The real time control and coordination of the
manipulation package (RCCL/RCI) has been adopted in
UB robot hand. RCCL/RCI developed for the control of a
single robot has been modified in order to cope with
peculiar characteristic of the UB hand system [22].
Position control is used when the robot finger must be
moved with or without load along a prescribed trajectory
through the robot finger workspace. The control system
of robot fingers is simply a collection of joint controllers
each of which is dedicated to a single joint and drives it
individually. The reference signals for these controllers
are supplied by a joint trajectory generator determining
the desired joint trajectory from the desired trajectory of
the gripper.
The joint controller is a feedback controller having two
terms respectively proportional to position and velocity
errors and introducing proportional and derivative actions
(PID control). An advance PID control with auto tuning
has been applied to control the kinematics motion in the
joint angles of each of the fingers. By tuning suitable
values of the three constant gains in the PID controller
algorithm, the controller has been found to provide the
necessary control action for specific process requirements.
The suitable gains of Proportional gain (Kp), Integral (Ki)
and Differential gain (Kd) value are determined by auto
tuning to achieve a fast response to steady state (setting
tune) without excessive overshoot. The error signal is the
difference between reference input angle and actual
output angle of the system. Parameter Kd works on the
change of the error signal, so it can reduce dramatically
overshoot effects to reach steady state response.
and close. In this task there are five position
configuration set points of finger which can operate by
simulation in Matlab/SimMechanics. Curve signal as
input desired is provided in this task to produce the
various fingers motion. In this paper, the author’s shows
the angular position graph in five fingered gripper robot
as shown in Fig. 7.
Figure 7. Simulation of angular position gripper finger control
The various input references are examined into
simulation to determine some responses from each
actuator in 20 second. The visualization of the motion
gripper simulation is show in Fig. 6. The simulation of
actual response shows the servo DC motor motion has
achieved the steady response at ± 1,301 with minimum
overshoot at ± 6,35% .
The thumb moves to touch the index finger where an
actual angular position in thumb moved from 0o to 70o in
5 seconds. The signal error towards closed less than 1%
which it indicates the response dynamic system response
is stable.
Figure 5. Robot gripper control
Figure 8. The process of five fingered gripper building
B. Experiment Result
The second method is examination of prototype of the
five fingered robot gripper. The process to build of robot
gripper prototype can be seen in the Fig. 8.
The prototype of five fingered robot gripper is
connected to an Arduino Mega AT 2560 as a
microcontroller and it shows in Fig. 9 as follows.
The input references are provided to simulation and
Figure 6. Visualization of griipper finger motion
III.
RESULT AND DISCUSSION
A. Simulation Result
The simulation results visualization of gripper five
fingers kinematics motion are shown in Fig. 6. In this
gripper robot animation, the fingers gripper move to open
© 2015 Int. J. Mech. Eng. Rob. Res.
229
International Journal of Mechanical Engineering and Robotics Research Vol. 4, No. 3, July 2015
experiment process. The actual angular position response
into an experiment of robot finger is shown in Fig. 10 to
Fig. 15 as follows.
Figure 14. An actual angular position in 1st joint of thumb
Figure 9. Five fingered gripper experiment
Figure 15. An actual angular position in 2nd joint of thumb
The overshoot signal in experiment of prototype is
higher than in simulation process because there are many
disturbance inputs in experiment process such as torque
disturbance, viscous disturbance etc., respectively. When
a given reference value is fixed with a long time, small
oscillations will occur in prototype testing. While the
simulation test looks linear oscillation does not occur.
The number of oscillations that occur in the joints of the
thumb is due to the weight-bearing joints of the thumb
movement. Effects of External mode is used in the initial
prototype testing that the motor moves at 90 ° so that the
test results is obtained initial chart movements condition
is not from zero.
The results of prototype testing showed that the time
required to drive the motor is longer than the simulation
testing. Prototype testing results are not much different
from the simulation test results, that the servo motor takes
a few seconds to achieve a given reference angle. The
occurrence of oscillations in the prototype test results is
caused the sensor to experience disturbances outside the
non-linear.
Figure 10. An actual angular position in a little finger joint
Figure 11. An actual angular position in a fourth finger joint
IV.
Figure 12. An actual angular position in a middle finger joint
Figure 13. An actual angular position in an indext finger joint
© 2015 Int. J. Mech. Eng. Rob. Res.
CONCLUSION
The physical model of the five finger robot gripper is
built using SimMechanics software and the application
Simmechanics has also been verified with identical
outputs when compared with Simulink simulations. These
studies indicate that each finger of the gripper can be
controlled using the robust control of PID formulation.
PID control is very effectively used to control the
trajectory of the fingers. The simulation results have been
demonstrated that the radius of finger movement is
achieved in stable response. The signal error towards
closed less than 1% which it indicates the response
dynamic system response is stable.
The error signal for the five fingered robot gripper
prototype experiment is around 1.5% with less high than
230
International Journal of Mechanical Engineering and Robotics Research Vol. 4, No. 3, July 2015
error signal in simulation process because there are many
disturbance inputs in experiment process such as torque
disturbance, viscous disturbance etc., respectively. By
using the robust PID control can control the robot gripper
with the best performance.
[19]
[20]
ACKNOWLEDGMENT
[21]
We are deeply and invaluable gratitude a Minister
Department of Education and Culture Republic of
Indonesia for supporting and finding this Decentralizes
research (APBN 2015) though Letter of assignment in the
contract of implementation of Decentralizes in year
2015:311-160/UN 14.2/PNL.01.03.00/2015
[22]
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Robotics and Automation, California, 1987, pp.1718-1724.
K. B. Biggers, S. C. Jacobsen, and G. E. Gerpheide, “Low level
control of the utah/M.I.T. dexterous hand,” in Proc. IEEE. Int.
Conf. Robotics and Automation, San Francisco, Ca, 1986, pp. 6166.
R. H. Colbaugh, H. Seraji, and K. Glass, “Impedance control for
dexterous space manipulators,” in Proc. 31st Conf. on Decision
and Control, Tucson, Arizona, 1982, pp. 1881–1886.
H. Hanafusa and H. Asada, “A robot hand with elastic fingers and
its application to assembly process,” in Proc. Ifacsymp. on
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Information and Contr., Problems in Manufacturing Technology,
Tokyo, 1977, pp. 127–138.
N. Hogan, “Impedance control, an approach to manipulation,” Int .
J. of Robotics Res., vol.107, pp.1–24, 1985.
J. Butterfass, M. Fischer, M. Grebenstein, S. Haidacher, and G.
Andhirzinger, “Design and experiences with dlr hand ii,”
Automation Congress, Proceedings, World, vol. 15, pp. 105-110,
2004.
G. Bekey, R. Tomovic, and I. Zeljkovic, Control Architecture for
the Belgrade/Usc Hand in Dextrous Robot Hands, New York:
Springer-Verlag, 1999, pp. 136-149.
A. C. Eusebi, C. Fantuzzi, and C. Melchiorri, “The U.B. hand ii
control system,” IEEE Transactions on Robotics and Automation,
pp. 782-787, 1994.
Wayan. Widhiada, ST, MSc, PhD has
worked as a lecturer in Mechanical
Engineering Department, Engineering Faculty
of Udayana University, Denpasar, Bali,
Indonesia since 1996.He was born in Badung,
Bali, Indonesia on 19 November 1968.He
completed Postgraduate Doctor Program in
Mechanical
Engineering
at
School
Engineering of Liverpool John Moores
University-United Kingdomon November
2012. His study research is about Robotic and control.
He focuses to develop the research in robotic and control research. He
was a reviewer paper in IEEE/RSJ International Conference on
Intelligent Robots and Systems 2014.
Tjokorda Gde Tirta Nindhia was born in
Denpasar, Bali, Indonesia on January 16th,
1972. Received Doctor Degree in Mechanical
Engineering from GadjahMada University
(UGM) Yogyakarta, Indonesia on August
2003, with major field of study was Material
Engineering. He participated in various
international research collaboration such as
with Muroran Institute of Technology
Japan(2004), Toyohashi University of
Technology Japan (2006), Leoben Mining University Austria (20082009), Technical University of Vienna Austria (2010) and Recently
with Institute Chemical Technology of Prague Czech Republic (2012now). His current job is as Full Professor in the field of Material
Engineering at Department of Mechanical Engineering, Engineering
Faculty, Udayana University, Jimbaran, Bali, Indonesia. His research
interest covering subjects such as, biomaterial, waste recycle, failure
analyses, ceramic, metallurgy, composite, renewable energy, and
environmental friendly manufacturing.
Prof. Nindhia is a member of JICA Alumni, ASEA-UNINET alumni,
International Association of Computer Science and Information
Technology (IACSIT), Asia-Pacific Chemical, Biological &
Environmental Engineering Society (APCBEES) and also member of
association of Indonesian Nanotechnology. Prof Nindhia received best
researcher award in 1997 and in 2013 fromUdayana University the
place where he is working and again in 2012 received both Best lecturer
award from Engineering Faculty of Udayana University. In the same
years 2012, The research center of Udayana university awarded Prof
Nindhia as the best senior researcher. In 2013 Prof. Nindhia awarded as
15 best performance Indonesian lecturers from Ministry of Education
and Culture The Republic of Indonesia.
Nyoman Budiarsa, MT, Ph.D is an associate
Professor
of
Mechanical
engineering
Materials in the Dept. Mechanical
Engineering University of Udayana Bali
Indonesia. Completing the S3 at Liverpool
John Moores University. UK in the field
Mechanical Materials and until now active in
research, especially in Finite Element
Modeling, Materials characterization and
simulated based on instrumented indentation,
Surface effects in solid mechanics models
&simulations, and Surface mechanics. As senior members No.80347540
on IACSIT (International Association of Computer Science and
International Journal of Mechanical Engineering and Robotics Research Vol. 4, No. 3, July 2015
Information Technology), WASET (World Academy of Science
Engineering and Technology), ISAET (International Scientific
Academy of Engineering & Technology).Active participation in the
Scientific Committee and as editor for several International conferences.
until now active in teaching and in the organization or association in
their fields, especially in the field of Material Characterization, Surface
Effects in Solid Mechanics Models And Simulations Surface Mechanics,
& Mechanics Of Solid.
© 2015 Int. J. Mech. Eng. Rob. Res.
232
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International Journal of Mechanical Engineering
and Robotics Research
CONTENTS
Volume 4, Number 3, July 2015
Numerical and Experimental Investigations on Heat Transfer of Aluminum Microchannel Heat Sinks with
Different Channel Depths ................................................................................................................................... 204
Ngoctan Tran, Yaw-Jen Chang,, Jyh-tong Teng, and Thanhtrung Dang
Absolute Stability of Mechatronic Module with Intelligent Controller Based on Associative Memory ............ 209
Nikolai N. Karabutov, Valery M. Lokhin, Sergey V. Manko, and Mikhail P. Romanov
A Novel Tuning Algorithm for Fractional Order IMC Controllers for Time Delay Processes........................... 218
Cristina I. Muresan, Eva H. Dulf, and Roxana Both
Static Analysis on Suitable Arrangement of Tubes of Low-Cost Control Valve Using Buckled Tube .............. 222
Abdul Nasir, T. Akagi, S. Dohta, and O. Ayumu
Robust Control for the Motion Five Fingered Robot Gripper ............................................................................ 226
W. Widhiada, T. G. T. Nindhia, and N. Budiarsa
Extension of the Upper Extremity with Shoulder Movements ........................................................................... 233
Nobuaki Nakazawa and Toshikazu Matsui
Autonomous Mobile Robot Self-Learning In Motion Planning Problem .......................................................... 238
Sergey V. Manko, Valery M. Lokhin, Sekou A. K. Diane, and Alexander S. Panin
Modeling of Facility Location Problem for Reverse Logistics System with Uncertainty in Forward and Reverse
Flows of Products ............................................................................................................................................... 242
Saif Ullah, Guan Zailin, Xu Xianhao, He Zongdong, Wang Baoxi, and Mirza Jahanzeb
Comparisons of Break Points Selection Strategies for Piecewise Linear Approximation.................................. 247
Ming-Hua Lin and Jung-Fa Tsai
Application of Biogeography-Based Optimisation for Machine Layout Design Problem ................................. 251
Saisumpan Sooncharoen, Srisatja Vitayasak, and Pupong Pongcharoen
Solving Cold Start WithLebiD2.......................................................................................................................... 255
Lebi Jean Marc Dali and Qin Zhi Guang
International Journal of Mechanical Engineering and Robotics Research Vol. 4, No. 3, July 2015
Robust Control for the Motion Five Fingered
Robot Gripper
W. Widhiada, T. G. T. Nindhia, and N. Budiarsa
University of Udayana, Denpasar, Indonesia
Email: {widhiwyn, nindhia}@yahoo.com, budiarsa_nyoman@yahoo.co.id
proper gripper design can simplify the overall assembly,
improving overall reliability system, and reduce
implementation costs, and grippers have been widely
used for automated manufacturing, assembly and
packaging, etc. [3].
During the last three decades, the application of robotic
grippers has gradually developed for grasping a variety of
tasks from using a simple mechanism to multiple degree
of freedom of design. Most robotic grippers have been
specifically designed only to grasp on certain traditional
forms of object. In this study the author has researched
into the design, analysis and synthesis of sophisticated of
five fingered gripper.
The design of a gripper finger is a difficult task with
many considerations such as task requirements, geometry
of gripper and the complexity of mechanism[4].
Traditionally, a physical prototype is necessary to truly
test a hand’s ability to perform a variety of tasks, but this
can be quite costly with potentially many design
iterations being required. However to reduce prototyping
costs, simulation techniques provides another tool which
enables the modern designer to model (simulate) the
kinematics and dynamics of physical systems and to
quickly investigate the performance of the design.
Simulation has been recognized as a powerful tool for
supporting the design, planning, and analysis of dynamics
performance of robotic grippers [5]. In this work
simulation results and visualization of the dynamics of a
robotic gripper are presented.
In this research study, the author has focused upon
investigating how to develop the modeling and
controlling the dexterous of five fingered gripper. The
gripper finger can grasp and manipulate the engineering
component. In this study, authors will build both a design
and a prototype robot gripper five fingers. This gripper
design will resemble a human hand. This robot will have
11 rotary joints (revolute joint). PID control is used to
control the kinematics and dynamics robot gripper to
achieve the best performance include quickly response
and high accuracy respectively.
The application of PID control in simulation for the
five fingered gripper is capable to accelerate the motion
response gripper fingers. Quickly response makes driving
a small error signal so as the calm conditions (steady state)
will be obtained very quickly as well. PID control system
design with Matlab software is robust control to achieve
the good performance [6].
Abstract—The design of multi-fingered robot hands have
been one of the major research topics since grasping an
object and are crucial functionalities of several robotic
systems, including industrial robots, mobile robots and
service robots. The author considers the problem of modelbased control for a multi-fingered robot hand. This paper
introduces an integrated design process for the design of the
five fingered gripper suitable for dexterous motion by using
simulation and experiment of prototype. To facilitate an
integrated design of gripper finger, the author applied
Matlab/Simulink (SimMechanics) and Inventor software
packages, respectively. Multi-closed loop with the robust
control of PID is applied to control both kinematics and
dynamics motions of the five fingered gripper systems. To
obtain the optimal trajectory planning approach using
motion reference and integration of planning control for
virtual actuators at each joint of finger gripper system. The
analysis of experiment result shows the trajectory angular
position of each finger link moves towards quickly to
achieve the trajectory angle target with small error signal
and overshoot.
Index Terms—multi fingered robot, kinematics
dynamics motions, robust control of PID.
I.
and
INTRODUCTION
Robot technology has seen development to support
both the needs of industry and human life. In human
interaction the robot is usually considered to interact with
the end user using ‘hands’ whist in industrial activity the
‘hand is usually termed as a ‘gripper’. The robotics
programmed to accomplish complex issues that interact
with the environment.
Robots designed to interact with humans in a human
manner will often require the hands and such robotic
systems are referred to as humanoid. There are several
published studies into the development of human hand
behaviour into humanoid [1]. Other humanoid research
has been more focused on applications such as humanoid
robot [2]. In each of these cases their hands have been
designed to conform to different criteria.
A robot gripper is the physical realization of an
electromechanical system to perform physical handling
tasks automatically. A robot griper is an essential element
of the robotic system and it is designed to suit industrial
application to typically grasp, carry, manipulate and
assemble the components. Greg Causey has shown that
Manuscript received March 10, 2015; revised June11, 2015.
© 2015 Int. J. Mech. Eng. Rob. Res.
doi: 10.18178/ijmerr.4.3.226-232
226
International Journal of Mechanical Engineering and Robotics Research Vol. 4, No. 3, July 2015
II.
of mechanical systems. A fundamental of this work is the
use of Matlab/Simulink Toolboxes to support the
simulation and understanding of the various dynamics
systems and in particular how the SimMechanics toolbox
is used to interface seamlessly with ordinary Simulink
block diagrams to enable the mechanical elements and its
associated control system elements to be investigated in
one common environment.
The design process, simulation and experiment method
for the five fingered robot gripper is shown in the flow
chart of research in Fig. 2.
METHODOLOGY
A. Research Description
From 1978 to 2011, the work undertaken on gripper
design has gradually developed from simple kinematic
arrangements into the multi-degree of freedom design.
From the evaluation of gripper design, and the functional
needs for assembly the author’s has identified that a fivefingered gripper with multi-degree of freedom is the
minimum needs for the dexterous assembly of
engineering elements.
Computer aided design software package is a powerful
tool to design any physical system in 3D solid modelling
in a virtual environment. CAD is especially useful for
author to design multi-degrees of freedom (DOF) gripper
finger. However, the author needed several software tools
to design and control the dynamics performance of a five
fingered gripper. This research study addresses the
integration of two software packages; Inventor and
MATLAB/Simulink/SimMechanics.
Using SimMechanics, it becomes possible to model
and simulate mechanical systems with a suite of tools to
specify bodies and their mass properties, their possible
motions, kinematic constraints and coordinates system
and to initiate and measure body motions [7]. In this work
simulation results and visualization of the dynamics of a
robotic gripper are presented.
The design of robot finger is made in Inventor
Software as follow the dimension of human finger. The
illustration of finger design transfer from 3D to block
diagram in MATLAB/Simulink is shown in Fig. 1. The
finger design in 3D will be exported in form of xml-file
and
it
change
to
diagram
block
in
MATLAB/SimMechanics. SimMechanics tool provides a
reserve to deriving equations and performing them with
base blocks. To create a SimMechanic model, the
mechanical system should be break down into the
building blocks.
Figure 2. Flow chart of research
B. Architecture of Robot Finger
In order to demonstrate the expediency of the
described robot hand approach, authors have developed a
three fingered hand prototype by developing model in a 3
dimension model with Solid works software [9].
Actuators, position sensors and force sensors have been
integrated in the hand structure.
Figure 1. The process of design robot gripper
Simulation has been identified as a significant study
tool for robotic systems since the early of the 20th
century [8] and now simulation methods area powerful
tool supporting the design, planning, analysis, and
decisions in different areas of research and development.
Now, Simulink has developed in many directions: adding
more blocks, built-in algebraic loop solving, and a
physical modeling of toolboxes.
The author has shown through the demonstration of
simulation that it is suitable for the fundamental building
© 2015 Int. J. Mech. Eng. Rob. Res.
Figure 3. Five fingered gripper design
The dexterous robot gripper is equipped with four
identical fingers (index, middle, fourth, little finger) and a
thumb. An actuator is installed in each joint of the fingers
227
International Journal of Mechanical Engineering and Robotics Research Vol. 4, No. 3, July 2015
each of which is presented to a single joint to drive it
individually. The reference signals for these controllers
are supplied by a joint trajectory generator determining
the desired joint trajectory from the desired trajectory of
the mobile robot.
and thumb. The joints of the finger, the distal
interphalangeal (DIP), proximal interphalangeal (PIP)
and metacarpophalangeal (MCP) joints each have 1 DOF
to provide a rotation movement. The architecture of the
five fingers is show in Fig. 3.
The thumb has been designed in order to complete the
hand and it has two degrees of freedom. The thumb is
both able to flex and extend. The index, middle, forth and
little finger prototypes have been designed such that each
finger has three degrees of freedom. In order to simulate
the finger motions each revolute joint has an associated
Servo DC motor attached to it. The extension finger tip is
also controlled using a DC motor Servo driving a rack
and pinion.
C. Mathematics Model for DC Servo Motor
DC servo motor is used to drive six joints in finger
robot. The author presents the mathematics model for DC
servo motor as follows.
ߠሺݏሻ
ܭ௧
ൌ
ሺͳሻ
ܽܧሺݏሻ
ݏሾܮ ݏܬଶ ሺܮ ݂ ܴ ܬሻ ܴ ݂ ܭ௧ ܭ ሿ
where,
Ra= armature resistor, ohm
La= armature inductance, Henry
ia= armature current, ampere
ea= applied armature voltage, volt
eb= feedback voltage, volt
T= torque motor, N-m
J= Moment inertia motor, kg-m2
f=Coefficient viscous motor and load, N-/rad/sec
The equation 1 is the transfer function of DC servo
motor which is used to drive the motor in each finger link.
The mathematics model is applied in block simulink and
illustrate in Fig. 4.
Figure 4. The transfer function of DC servo motor
D. Trajectory Line
The trajectory planning is necessary to generate the
reference inputs to the motion control system, which
ensures that the gripper robot executes the planned
trajectories. The minimal set of requirement for a gripper
robot is to be able to run from an initial position to a final
assigned position.
The input of trajectory planning algorithm is the path
description, the path constraints and the constraints
imposed by a gripper robot dynamics, whereas the
outputs are the joint trajectories in terms of a time
sequence of the values attained by position, velocity and
acceleration.
Position control is used when the robot finger must be
moved with or without load along a prescribed trajectory
through the mobile robot workspace. The control system
of mobile robot is merely a collection of joint controllers
© 2015 Int. J. Mech. Eng. Rob. Res.
228
E. Robust Control Strategy
The control of robot hand is responsible for ensuring
that the hand firmly grasps and that corresponding finger
in the presence of external forces applied to the object.
These forces may require high values of contact force at
the fingertip to get the stability response. To solve these
problems Kazerooni in 1990 published a control law
adopted the relationship between the interaction force and
position trajectory [10].
A considerable body of research has been undertaken
on robotic hand system with robot force control and
planning related to the entire device and the significant
developments are as follows,
Okada developed robotic hand to handle objects which
is suitable to suppress the rapid change of the grasping
condition during a complex finger motion. The finger
control consists of a hybrid position/torque servo
implemented in hardware. Robot hand Okada has shown
to understand and manipulate objects under position
control mode [11].
Salisbury had presented control algorithms for
achieving the stable force control and involving the
relation between position and applied force, stiffness
control with feedback of position only and stiffness
control with force feedback correction [12]. This force is
converted to joint torque commands and the resulting
endpoint motions. Force control has been applied to robot
hands [13] and [14]. The implementation of a controller
and a brief of description of programming language for
the Salisbury hand were presented [15]. He introduced
the concept of a grasp frame that is calculated as a
function of the positions of the finger tips. A summary of
issues involved in low level control of the Utah-MIT
hand was presented [16].
The impedance control methods are developed for
dexterous robot fingers which has relation between
velocity and applied force [17]-[18] and [19].
In 1997 DLR’s dexterous four robot hand is designed
as a dexterous robot hand with a semi anthropomorphic
design. The application of robotics hand systems in
unstructured environments required the dexterous
manipulation abilities and facilities to perform complex
remote operations. Therefore this robot hand has
developed both of new design sensors as 6 DOF fingertip
force torque sensor and integrated electronics with new
communication architecture [20].
Bekey proposed the control strategy of Belgrade robot
hand focused on how to find suitable grasp postures and
poses for the task and how to use the multi-dimensional
grasping quality in grasp mode selection and performance
evaluation in an industrial assembly domain [21]. The
Belgrade robot hand is used to graspa variety of objects
and capable to adapt while applying simple control
architecture based on the principles of non-numerical
control to drive the hand.
International Journal of Mechanical Engineering and Robotics Research Vol. 4, No. 3, July 2015
The real time control and coordination of the
manipulation package (RCCL/RCI) has been adopted in
UB robot hand. RCCL/RCI developed for the control of a
single robot has been modified in order to cope with
peculiar characteristic of the UB hand system [22].
Position control is used when the robot finger must be
moved with or without load along a prescribed trajectory
through the robot finger workspace. The control system
of robot fingers is simply a collection of joint controllers
each of which is dedicated to a single joint and drives it
individually. The reference signals for these controllers
are supplied by a joint trajectory generator determining
the desired joint trajectory from the desired trajectory of
the gripper.
The joint controller is a feedback controller having two
terms respectively proportional to position and velocity
errors and introducing proportional and derivative actions
(PID control). An advance PID control with auto tuning
has been applied to control the kinematics motion in the
joint angles of each of the fingers. By tuning suitable
values of the three constant gains in the PID controller
algorithm, the controller has been found to provide the
necessary control action for specific process requirements.
The suitable gains of Proportional gain (Kp), Integral (Ki)
and Differential gain (Kd) value are determined by auto
tuning to achieve a fast response to steady state (setting
tune) without excessive overshoot. The error signal is the
difference between reference input angle and actual
output angle of the system. Parameter Kd works on the
change of the error signal, so it can reduce dramatically
overshoot effects to reach steady state response.
and close. In this task there are five position
configuration set points of finger which can operate by
simulation in Matlab/SimMechanics. Curve signal as
input desired is provided in this task to produce the
various fingers motion. In this paper, the author’s shows
the angular position graph in five fingered gripper robot
as shown in Fig. 7.
Figure 7. Simulation of angular position gripper finger control
The various input references are examined into
simulation to determine some responses from each
actuator in 20 second. The visualization of the motion
gripper simulation is show in Fig. 6. The simulation of
actual response shows the servo DC motor motion has
achieved the steady response at ± 1,301 with minimum
overshoot at ± 6,35% .
The thumb moves to touch the index finger where an
actual angular position in thumb moved from 0o to 70o in
5 seconds. The signal error towards closed less than 1%
which it indicates the response dynamic system response
is stable.
Figure 5. Robot gripper control
Figure 8. The process of five fingered gripper building
B. Experiment Result
The second method is examination of prototype of the
five fingered robot gripper. The process to build of robot
gripper prototype can be seen in the Fig. 8.
The prototype of five fingered robot gripper is
connected to an Arduino Mega AT 2560 as a
microcontroller and it shows in Fig. 9 as follows.
The input references are provided to simulation and
Figure 6. Visualization of griipper finger motion
III.
RESULT AND DISCUSSION
A. Simulation Result
The simulation results visualization of gripper five
fingers kinematics motion are shown in Fig. 6. In this
gripper robot animation, the fingers gripper move to open
© 2015 Int. J. Mech. Eng. Rob. Res.
229
International Journal of Mechanical Engineering and Robotics Research Vol. 4, No. 3, July 2015
experiment process. The actual angular position response
into an experiment of robot finger is shown in Fig. 10 to
Fig. 15 as follows.
Figure 14. An actual angular position in 1st joint of thumb
Figure 9. Five fingered gripper experiment
Figure 15. An actual angular position in 2nd joint of thumb
The overshoot signal in experiment of prototype is
higher than in simulation process because there are many
disturbance inputs in experiment process such as torque
disturbance, viscous disturbance etc., respectively. When
a given reference value is fixed with a long time, small
oscillations will occur in prototype testing. While the
simulation test looks linear oscillation does not occur.
The number of oscillations that occur in the joints of the
thumb is due to the weight-bearing joints of the thumb
movement. Effects of External mode is used in the initial
prototype testing that the motor moves at 90 ° so that the
test results is obtained initial chart movements condition
is not from zero.
The results of prototype testing showed that the time
required to drive the motor is longer than the simulation
testing. Prototype testing results are not much different
from the simulation test results, that the servo motor takes
a few seconds to achieve a given reference angle. The
occurrence of oscillations in the prototype test results is
caused the sensor to experience disturbances outside the
non-linear.
Figure 10. An actual angular position in a little finger joint
Figure 11. An actual angular position in a fourth finger joint
IV.
Figure 12. An actual angular position in a middle finger joint
Figure 13. An actual angular position in an indext finger joint
© 2015 Int. J. Mech. Eng. Rob. Res.
CONCLUSION
The physical model of the five finger robot gripper is
built using SimMechanics software and the application
Simmechanics has also been verified with identical
outputs when compared with Simulink simulations. These
studies indicate that each finger of the gripper can be
controlled using the robust control of PID formulation.
PID control is very effectively used to control the
trajectory of the fingers. The simulation results have been
demonstrated that the radius of finger movement is
achieved in stable response. The signal error towards
closed less than 1% which it indicates the response
dynamic system response is stable.
The error signal for the five fingered robot gripper
prototype experiment is around 1.5% with less high than
230
International Journal of Mechanical Engineering and Robotics Research Vol. 4, No. 3, July 2015
error signal in simulation process because there are many
disturbance inputs in experiment process such as torque
disturbance, viscous disturbance etc., respectively. By
using the robust PID control can control the robot gripper
with the best performance.
[19]
[20]
ACKNOWLEDGMENT
[21]
We are deeply and invaluable gratitude a Minister
Department of Education and Culture Republic of
Indonesia for supporting and finding this Decentralizes
research (APBN 2015) though Letter of assignment in the
contract of implementation of Decentralizes in year
2015:311-160/UN 14.2/PNL.01.03.00/2015
[22]
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Wayan. Widhiada, ST, MSc, PhD has
worked as a lecturer in Mechanical
Engineering Department, Engineering Faculty
of Udayana University, Denpasar, Bali,
Indonesia since 1996.He was born in Badung,
Bali, Indonesia on 19 November 1968.He
completed Postgraduate Doctor Program in
Mechanical
Engineering
at
School
Engineering of Liverpool John Moores
University-United Kingdomon November
2012. His study research is about Robotic and control.
He focuses to develop the research in robotic and control research. He
was a reviewer paper in IEEE/RSJ International Conference on
Intelligent Robots and Systems 2014.
Tjokorda Gde Tirta Nindhia was born in
Denpasar, Bali, Indonesia on January 16th,
1972. Received Doctor Degree in Mechanical
Engineering from GadjahMada University
(UGM) Yogyakarta, Indonesia on August
2003, with major field of study was Material
Engineering. He participated in various
international research collaboration such as
with Muroran Institute of Technology
Japan(2004), Toyohashi University of
Technology Japan (2006), Leoben Mining University Austria (20082009), Technical University of Vienna Austria (2010) and Recently
with Institute Chemical Technology of Prague Czech Republic (2012now). His current job is as Full Professor in the field of Material
Engineering at Department of Mechanical Engineering, Engineering
Faculty, Udayana University, Jimbaran, Bali, Indonesia. His research
interest covering subjects such as, biomaterial, waste recycle, failure
analyses, ceramic, metallurgy, composite, renewable energy, and
environmental friendly manufacturing.
Prof. Nindhia is a member of JICA Alumni, ASEA-UNINET alumni,
International Association of Computer Science and Information
Technology (IACSIT), Asia-Pacific Chemical, Biological &
Environmental Engineering Society (APCBEES) and also member of
association of Indonesian Nanotechnology. Prof Nindhia received best
researcher award in 1997 and in 2013 fromUdayana University the
place where he is working and again in 2012 received both Best lecturer
award from Engineering Faculty of Udayana University. In the same
years 2012, The research center of Udayana university awarded Prof
Nindhia as the best senior researcher. In 2013 Prof. Nindhia awarded as
15 best performance Indonesian lecturers from Ministry of Education
and Culture The Republic of Indonesia.
Nyoman Budiarsa, MT, Ph.D is an associate
Professor
of
Mechanical
engineering
Materials in the Dept. Mechanical
Engineering University of Udayana Bali
Indonesia. Completing the S3 at Liverpool
John Moores University. UK in the field
Mechanical Materials and until now active in
research, especially in Finite Element
Modeling, Materials characterization and
simulated based on instrumented indentation,
Surface effects in solid mechanics models
&simulations, and Surface mechanics. As senior members No.80347540
on IACSIT (International Association of Computer Science and
International Journal of Mechanical Engineering and Robotics Research Vol. 4, No. 3, July 2015
Information Technology), WASET (World Academy of Science
Engineering and Technology), ISAET (International Scientific
Academy of Engineering & Technology).Active participation in the
Scientific Committee and as editor for several International conferences.
until now active in teaching and in the organization or association in
their fields, especially in the field of Material Characterization, Surface
Effects in Solid Mechanics Models And Simulations Surface Mechanics,
& Mechanics Of Solid.
© 2015 Int. J. Mech. Eng. Rob. Res.
232
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