Real-Time Control of Robotic Hand by Human Hand at Low Cost

Abstract

In this paper, the design and implementation of control system for robotic hand at low cost is achieved. The proposed control is based on the Flexible sensor and the Arduino controller. It is used glove to transferring the gestures to simulate the motion of the five fingers of human hand by using five fingers of the robotic hand. The task of the robotic hand is to catch any object under the real-time control. MEMS gyroscope is used to control the rotation of the elbow of robotic hand toward right or left. The robotic hand is a tendon finger manipulation type. It can be considered the developed robotic system in this paper is very important especially in the industrial sector where there are some places are not reachable by human hands, therefore it can be used this robotic hand easily.

Full text

Journal of Mechanical Engineering Research and Developments
ISSN: 1024-1752
CODEN: JERDFO
Vol. 43, No. 3, pp. 455-467
Published Year 2020
455
Real-Time Control of Robotic Hand by Human Hand at Low
Cost
Enas A. Khalid†, Wisam T. Abbood†, Oday I. Abdullah‡
†University of Baghdad, AL-Khwarizmi College of Engineering, Automated Manufacturing Engineering
Department, Iraq
‡University of Baghdad, College of Engineering, Energy Engineering Department, Iraq
ABSTRACT: In this paper, the design and implementation of control system for robotic hand at low cost is
achieved. The proposed control is based on the Flexible sensor and the Arduino controller. It is used glove to
transferring the gestures to simulate the motion of the five fingers of human hand by using five fingers of the
robotic hand. The task of the robotic hand is to catch any object under the real-time control. MEMS gyroscope
is used to control the rotation of the elbow of robotic hand toward right or left. The robotic hand is a tendon
finger manipulation type. It can be considered the developed robotic system in this paper is very important
especially in the industrial sector where there are some places are not reachable by human hands, therefore it can
be used this robotic hand easily.
KEYWORDS: Control of Robotic Hand; Low Cost of Robotic Control; Read Gestures Data to Control Robotic
Hand.
INTRODUCTION
The robotic arm has become a crucial technology for automation industries to perform different tasks such as
pick and place, welding, and cutting. It provides maximum accuracy with no human error when performing tasks.
Dexterous remote-control technology allows humans to control a robotic arm in an environment where it is
unsafe and hazardous. Some of these systems are operated by different kinds of variants such as keypad, buttons,
joysticks, and teach pendants.
Various types of teach pendants with the intuitive user interface have been developed by the robot manufacturers
such as a 6D mouse, icon-based programming, and a 3D joystick (ABB Robotics). However, there are few issues
still occur regarding the control of the robotic arm by the teach pendant. Controlling a manipulator in high
accuracy and precision is still very difficult to achieve. Each degree movement of the robotic arm needs a
predetermined sequence of button actions and it is very time-consuming. Functionality error of robotic arm will
occur if the teach pendant is improperly used. Apart from that, the efficiency of the robotic arm system controlled
by teach pendant is low since it cannot be controlled intuitively. Therefore, robotic arms controlled by teaching
a pedant is still not user-friendly. The process of interaction of hand glove is more accurate and natural than
normal static keyboard and mouse.
A solution is proposed in this paper which is to design and develop a hand glove to control the robotic arm more
intuitively and to improve the performance of robotic arm system in term of accuracy and efficiency as well as
to reduce the controlling complexity, time consumed, and at low-cost control components.
Cost control is the act of recognizing and diminishing operational expenses to expand benefits, and it begins with
the planning procedure. The cost control system is an indispensable portion of the synoptic organizational choice
supportive system. The cost control system focuses on intra-organizational data and contains the identifier,
assessor, effecter, and system segments. Comparative with the cost administration system, the cost control
system gives data to arranging and for deciding the proficiency of exercises while they are being arranged and
after they are performed. The robot control at low cost in researches of Rudd et.al. [1] The design structures have
done on link impelled exoskeleton structures by executing the equivalent kinematic usefulness, however, the
focus moved to the simplicity of getting together and cost-adequacy to permit patients and physicians to fabricate
and collect the equipment important to actualize treatment.
The exoskeleton was developed exclusively from 3D-printed and generally accessible off-the-rack parts. Semi

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Direct Drive activation as a competent worldview for robot force-controlled manipulation in human conditions
required at low cost [2]. Dexterous multi-fingered robotic hands at low-cost [3]. The control system at a low cost
becomes utilized if, in the same efficient, there are some research deals with low-cost control in deferent fields
and applications, low-cost tests for the laboratory of a feedback control system course and portable laboratory
kit [4] [5], low-cost sensors for ambient monitoring [6], low-cost machine vision-based quality control system
inside a learning factory [7], a low-cost humidity control system [8], a low-cost solution for the feedback control
of thermal protection system [9], low-cost temperature control chamber [10], and solar water pumping system
control using a low-cost microcontroller [11].
The robotic hand control is developed to be easy to use with fast response to achieve a certain task. The robot
hand controlled at deferent sensors and actuators, there are many research for robotics applications skills using
appropriate control: It was used the computer vision by applying the image processing technique to control the
Hand robotic according to the human gestures [12]. The operation of robotic grasping for the robotic hand using
tactile sensing control which used to detect slipping object from the grasp [13]. Robotic grasp skills will be
transferred from human grasping using the trained system based on the neural networks [14] and [15]. A robotic
arm reaches and grasps by applying the neural controlled [16]. It should be evaluated the mechanical design of
prosthetic hands and the performance according to the actuation mechanism of fingers and grasp methods [17].
Also, it was applied EMG (Electromyography) data to control the robotic hand [18-21] with the coupling module
to detect the classification of hand motion [22]. Other researchers applied DESC (Discrete Event-driven Sensory
feedback Control) to control of the robotic hand [23]. Other researches were studied the dual robotic hand
movement based on the Kinect method that allows double hand movements communicated to dual robot [24]. It
was developed different designs for the tendon robotic to grasp the objects [25-27]. The control of the system is
using the neural control to be artificial hands [28]. It should be taken into consideration the frictional self-locking
for the operation of robotic grasping for objects [29]. Recently, the challenge is to produce the design dexterous
robot hand [30]. It is a novelty type designed to able grasping with low control complexity [31]. It can be
performed the vision-based object reorientation using the reinforcement learning [32]. A novel soft robotic finger
was improved using the soft actuator with 3 DOF [33]. The bidirectional soft robotic glove is designed to assist
and rehabilitate hand impaired patients [34]. Tactile feedback is using to grasping and manipulation that provided
from visual continuous feedback [22]. One of the important things is use the learn hand-eye coordination
approach for grasping [35]. Thin soft muscles provided to the robotic hand accompanying with using control the
finger grasping [36]. Soft robotic hand design for flexible grasping is used three-stage cavity structure for the
fingers [37]. It was used the triboelectric quantization sensor for joint motion design to control robotic hand
grasping [38]. The robotic hand was controlled for grasping by applying the deferential kinematics mapping
between the motor space and the Cartesian space [39]. MEMS-sensor is designed for the control motion of
robotic objects and capturing systems [40]. Also, the robotic hand was controlled by gesture recognition. These
gestures go through processes for recognition which are sensor information assortment, gesture distinguishing
proof, gesture following, gesture characterization, and gesture mapping [41]. The control of the robotic hand
process and autonomy levels is responsible for task selection, motion planning, motion control, and hardware
[42].
Hand rehabilitation robot achieved by applying a series of decisions on the design of the hardware system and
training paradigm [43]. The actuation technologies that used in the biomedical soft robot are flexible fluidic
actuators, shape-memory materials, electroactive polymers, tendon-driven actuators, material jamming, and
different type of materials (electrorheological, magnetorheological, etc.) [44]. Robotic gripers utilized in sorting
the colour and shape objects [45]. There are different types of gesture recognition sensors used in the robotic
hand. It can be classified these sensors according to the image approach. The first group is image-based which
included maker, depth sensor, stereo camera, and single camera. The second group is non-image based which
included the glove, band, and non-wearable [41].
In this research paper, the design and implementation of the robotic hand that controlled by the human hand
using glove gestures is presented. The control designed in real-time data transfer to movement fingers and wrist
rotation. This robotic hand can catch any objects such as the human hand. The glove designed using the flexible
sensor for sensing any movement at the human fingers. The microcontroller Arduino is used to translate the
signals from a flexible sensor to servo motors of hand fingers.
This work aims to implement a developed robotic arm that controlled by the human arm, present a better
understanding of concept of the servo motor control, apply the concept of accelerometer, implement hardware

Real-Time Control of Robotic Hand by Human Hand at Low Cost
457
installation, and learn Arduino programming. The objectives are to design and develop a simple hand-glove
controller for robotic arm system, analyse the performance of hand glove controlled robotic arm system in terms
of accuracy and repeatability, and developing a hand robotic control at low cost.
Many methods to enhance the control of the grasping is presented in the previous literature. There are many
control sensors are used for controlling the robotic hand such as; Image processing control that depends on the
sensor to picture (camera), tactile sensor, EMG sensor, DESC sensor, industrial muscles, triboelectric
quantization sensor, electrorheological, magnetorheological, and depth sensor. The sensors and components are
used to build the control system in this research paper are low cost compared with the available systems in the
markets and also mentioned in the available literature. The control system in this work is build based on the
MEMS sensor (accelerometer MPU 6050), resistive flexible, and Arduino with his shield. Where the total cost
of the developed control; system is equal to 24$ (Resistive flexible 2.5 * 5 = $12.5, Arduino UNO = $5, Shield
Arduino = $5, and MPU 6050 Accelerometer = $1.5).
DESCRIPTION AND PERFORMANCE OF ROBOTIC HAND SYSTEM
The mechanical structure of the Robotic Arm is made utilizing effectively available minimal effort plastic sheets.
It was intended to permit the settlement of the actuators and the control circuit. The goals of this exploration
paper are fixed all Flexible sensor above of glove fingers, fixed gyroscope at the glove, structure the adaptable
program that controls the motions information, and sign. The fingers comprise of three linkages, with the goal
that their development resembles that of the human finger. It was associated with the contradicting thumb to the
palm utilizing a rotate joint, at that point it will be moved like a human thumb. The entire part at that point
connected to a plastic sheet, where the base is joined the compressed wood to keep it in position. The human
hand glove comprises of a triple-hub accelerometer and five flex sensors that appended to it to control the hand
development. The total part will be worked remotely to empower the framework to accomplish the errands from
a separation utilizing a ZigBee transmitter-beneficiary module. Figure 1 shows the square chart of the
components to control the hand-glove, where there is the capacity to announce that when the client moves the
arm or the fingers. The sensors fixed to the hand glove that gives analog voltage yields. This analog voltage will
be given to the inbuilt ADC of the microcontroller. The prepared advanced sign is sent to the control hardware
of the automated arm utilizing wires. The circuit diagram of the robotic hand system is shown in Figure 2.
The robotic hand system consists of a Flexible sensor and gyroscope which are fixed at the glove. The Flexible
sensor is a variable resistor with different ranges from 25KΩ to 125KΩ and sizes from 1 to 3 inches. The
gyroscope measures angular rate using the Coriolis Effect. Robotic arm framework comprises of connections,
joints, actuators, sensors, and controllers. The associations are related to joints to shape the open kinematic chain.
One end of the chain is affixed to the robot base, and another end is outfitted with an instrument (hand) which is
undifferentiated from people present a solicitation to perform gathering extraordinary, endeavors and to connect
with the environment [42]. There are two sorts of the joint which are prismatic and revolving joints and it
interfaces adjoining connection. The glove is equipped with 5 flex sensors for the five fingers, and the gyroscope
accelerometer is used for the wrist movement where it connected to the Arduino and then to the servo motors on
the robotic arm. It was used five servos for moving the fingers and one servo for moving the writ as shown in
Figure 3.
Although, the microcontroller type PIC is generally utilized in the programming field. They are profoundly
delicate and servo engines are utilized related to electronic or programmable circuits. Table 1 lists the
specifications of servo motors used in this work.

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458
Figure 1. Block diagram of hand-glove controlled
Figure 2. Circuit diagram of the Robotic hand system

Real-Time Control of Robotic Hand by Human Hand at Low Cost
459
Figure 3. Robotic hand components a-back view b- front view
Table 1. Specifications of Five Finger Servo Motors
Specifications
MG996R * 1
SG90 * 5
Weight
55(g)
14.7(g)
Dimension
40.7 x 19.7 x 42.9(mm
approx.)
22.5 x 12 x 35.5(mm approx.)
Stall torque
9.4 kgf·cm (4.8V), 11
kgf·cm (6V)
1.8 kgf·cm (4.8V), 2.2 kgf·cm
(6V)
Operating speed
0.17 s/60º (4.8V), 0.14 s/60º
(6V)
0.1 s/60º (4.8V), 0.08 s/60º (6V)
Operating voltage
4.8 V - 7.2 V
4.8-6.0 V
Running Current
500mA-900mA(6V)
-
Stall Current
2.5 A (6V)
-
Dead band width
10 μs
5 μs
Temperature range
0 ºC –55 ºC
-
METHODOLOGY AND THEORETICAL OF ROBOTIC HAND SYSTEM
This section presents the details of the methodology and theoretical background of the Robotic Hand System. In

Real-Time Control of Robotic Hand by Human Hand at Low Cost
460
this time, the robotics engineers focused to develop the robotic hand by enhancing the response and accuracy. In
this research work, the tendon robotic hand could be grasping any object by the tendon tension for any finger
that used. It can be utilized from the institution vector, 


to address how a lot of a tendon is established. Every
component of 


runs between 0 (no actuation, zero force) and 1 (full actuation, maximum force). Further
reciprocity may be found in Reference [46]. On the off chance that will characterize F0 as an inclining framework
of maximum tendon tensions, R as the moment finger framework matrix (or structure lattice) relating ligament
strains to joint torques, and J as the stance subordinate Jacobian relating joint speeds to fingertip speeds, at that
point can be got the fingertip force vector 
 from ligament actuations [47] if the Jacobian is square and invertible:

   
For the given fixed finger situation, the, R, and F0 networks can be gathered into a straight mapping from
actuations into fingertip force, which can be called an activity matrix A [46, 47]. Every element of A denotes the
force vector in every ligament which produces at the fingertip in that stance if the system is completely actuated.
Equation (1) represents the force vector of on fingertip that contained from F0 maximum tendon tensions, the
moment matrix R, and degree vector of the tendon that is activated.
The portrayal including a lot of straight disparities (like a direct programming imbalance limitation definition)
takes the structure as,
  
Where A will be the matrix of constants characterizing for the imbalances, x is a vector of variables of length d,
where d is the dimensionality of the cambered structure of fingertip, and b is a vector of constants. On the off
chance which means that Ai is the ith row of A. At that point, the direct disparity  ≤ bi characterizes a half-
space, which likewise characterizes an aspect of the raised structure. The opposite (i.e., most brief) Euclidean
separation (or counterbalance) of this aspect from the beginning, in general, it can be given as,


The hull yield (q), nonetheless, consequently sets each  equivalent to 1, so the ith counter balance from the
inception is essentially the marked consistent bi Estimation of the MIV in this examination includes just finding
the base of b compared to the possible force set. A physical understanding of the fingers-thumb resistance is
recommended, so the chief term of control sign should be created in the following form,
 


   
Where r indicates the radius of the fingertip hemispheres, Ji (qi) is the Jacobian torques matrix of the position
vector of qi as for finger joint vectors qi.
The equations (2) and equation (3) are the collection matrix of all fingers in the robotic hand. The equation4 the
control of each finger by calculated the torques at the finer joints to catch the object, supposed the contact point
between the fingertip and object for each finger as shown in figure 4.
The tension force and the torque are calculated experientially using the Forsentek model FMZK load cell
instrument as shown in Figure 5. The torque of fingertip can be calculated by applying the torque equation
(Torque = tension force * radius of rotation). The velocity is found by applying the LS300A- a portable velocity
meter 0.01 – 4 m/s instrument and encoder to calculate the angles. All of these are calculated together to give the
change in velocity with the angle of the fingertip. The acceleration is calculated by using Avt300 Digital potable
acceleration instrument with the encoder that applying at a fingertip.

Real-Time Control of Robotic Hand by Human Hand at Low Cost
461
Figure 4. The control of one finger to catch the objects
Figure 5. The load cell fixation method for the finger of hand
RESULTS OF THE ROBOTIC HAND SYSTEM
The results of the tendon robotic hand system are the force and acceleration that needed for any finger to catch
the objects. Each flex sensor at the glove sends a signal to Arduino and it’s translated to transform to the servo
motor that connected to it. Furthermore, the tension force and torque are calculated for the fingertip to catch
objects as shown in Figures 6 and 7. The tension force increased for the tendon rope of finger to the maximum
value at t=2.5s and then decreased to arrive at the forehand (middle angle of a finger). The meaning for this
behavior is the finger tendon has a maximum value of force in the middle angle of the moving finger.
Additionally, the torque reached the maximum at the end of the moving of finger to the forehand (t=3.5s). The
velocity of the finger increased with the angle because the angular distance decreased as shown in Figure 8. The
acceleration at the same value approximating that gives the regular grasping as shown in Figure 9.
In this paper, it was obtained the results with acceptable accuracy by using the newly developed low-cost control
system. Figure 10 shows the prices for different types of the control sensor, where it can be seen that the sensor
that selected to build the developed model in this paper the lowest one (resistive flexible) compared with other
sensors.

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462
Figure 6. The tension force of tendon fingertip
Figure 7. The torque of tendon fingertip
Figure 8. The velocity of tendon fingertip

Real-Time Control of Robotic Hand by Human Hand at Low Cost
463
Figure 9. The acceleration of tendon fingertip
Figure 10. The price of different types of the available control sensors
DISCUSSION THE RESULTS OF THE ROBOTIC HAND SYSTEM
The results obtained from calculating the performance of the robotic hand utilizing measurement instruments.
Figure 6 shown the force tension of the tendon of a fingertip from applying matrix calculation of all parts of the
finger. The tension force needs to a maximum value at 90° to move parts of the finger to fingertip. This tension
force reduced at end of grasping of the object. In figure 7 the torque calculates from the Jacobian matrix for the
experimental value of all joints in the finger to fingertip. The torque starts with a few values and increases until
grasping the object. The velocity calculating as shown in figure 8 where the positive relationship between the
velocity and the angle from start moving fingertip until grasp the object the velocity decreases value with increase
the angle. The changes in the values due to the fingertip arrive at the object by grasp operation. Acceleration of
fingertip was an increase in few values with a high increase in angle values because the acceleration of the robotic
finger was approximated fixed that make the average moving was fixing in increased values shown in figure 9.
Through study, the market of control components and sensors, the components, and sensors to control this robotic
hand which selected at low cost and there are have good performance as shown in figure 10.

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464
CONCLUSIONS AND REMARKS
In this paper, the developed model of the robotic hand was presented based on reducing the complexity in the
control system and by using the low-cost materials. The robotic hand was controlled by the human hand utilizing
a glove. The robotic hand was tested experimentally to simulate the real human hand to achieve tasks such as
moving and catching the objectives. The other important objectives of this design for the robotic hand are
enhancing the response and improve the accuracy to grasp any object. The velocity and acceleration of the robotic
hand are acceptable with the human hand. Furthermore, in the first experiments, the noise of signals appeared
explicitly when moved all fingers at the same time. By adding a subprogram to the Arduino microcontroller, the
noise disappeared and the robotic hand moved smoothly. In future work, it can be developed the robotic hand
system by applying the wireless control between the glove gestures and robotic hand. This research is considered
the first step in this area and will be followed by a series of researches that will study this subject with more
details.
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