MULTIPLE CONFIGURATIONS FOR PUNCTURING ROBOT POSITIONING

International Journal of Advance Robotics & Expert Systems (JARES) Vol.1, No.4
1
MULTIPLE CONFIGURATIONS FOR PUNCTURING ROBOT
POSITIONING
Omar Abdelaziz134
, Minzhou Luo23
, Guanwu Jiang13
and Saixuan Chen13
1
University of Science and Technology of China, Hefei, 230026, China
2
Key Laboratory of special robot technology of Jiangsu Province, Hohai University,
Changzhou, 213000, China
3
Institute of Intelligent Manufacturing Technology, Jiangsu Industrial Technology
Research Institute, Nanjing, 211800, China
4
Egyptian Russian University, Egypt
ABSTRACT
The paper presents the Inverse Kinematics (IK) close form derivation steps using combination of analytical
and geometric techniques for the UR robot. The innovative application of this work is used in the precise
positioning of puncture robotics system. The end effector is a puncture needle guide tube, which needs
precise positioning over the puncture insertion point. The IK closed form solutions bring out maximum 8
solutions represents 8 different robot joints configurations. These multiple solutions are helpful in the
puncture robotics system, it allow doctors to choose the most suitable configuration during the operation.
Therefore the workspace becomes more adequate for the coexistence of human and robot. Moreover IK
closed form solutions are more precise in positioning for medical puncture surgery compared to other
numerical methods. We include a performance evaluation for both of the IK obtained by the closed form
solution and by a numerical method.
KEYWORDS
MIS robotics system, inverse kinematics, puncture positioning, UR robot
1. INTRODUCTION
There are growing demands in the usage of robots nowadays and there has been a lot of research
carried out in robotics fields. The robotics applications can be seen in transportation, industry,
medical, defence, service, etc. Robotics research has moved rapidly in the last few years toward
the field of medical and health care. Today, medical robotics considered a reliable solution [1].
Strength points for robots over human in medical applications [2] i.e. achieving minimal
invasiveness, geometric accuracy, no fatigue or inattention, stable, repeatability, radiation
insensitive, and integration capability of numerical & sensor data. In literature, there are several

2
early attempts to categorize and classifies the applications of robotics systems in medical and
health care. They are mainly three classifications as in [3], [4]: macro-robotics, micro-robotics
and bio-robotics. Macro- robotics includes the development of assistive and rehabilitation robots
as well as new, more powerful tools and techniques for surgery. Micro-robotics could greatly
contribute to the field of minimally invasive surgery as well as to the development of a new
generation of tools for conventional surgery. Bio-robotics based on modelling and simulating
biological systems. Several examples of medical robotics systems currently exists such as robotic
orthopaedic surgery, robotically assisted percutaneous therapy, minimally invasive robotic
surgery, rehabilitation and assistive devices, and laboratory [5], [6]. Our interest in this paper
goes to the Minimally-Invasive Surgical (MIS) robotics system. Surgical robotics system in
general can be thought of as smart surgical tools that enable human surgeons to treat individual
patients with improved efficacy, greater safety, and less morbidity than would otherwise be
possible. It is an integration of a number of modern and complex high technologies that let
doctors (surgeons), through the robotics system, can perform surgical operations without touching
patients. MIS robot system is a combination of medical image processing technology and the
operation of the mechanical arm to perform puncture surgery on the patient [7]. It can be divided
in to two branches; an assistive capability, i.e. tool positioning, and an active capability, i.e. for
conducting transurethral resection of the prostate and arthroplasty (joint repair). MIS is an
operation performed using specialized instruments designed to fit into the body through several
tiny punctures instead of one large incision [8].
This paper presents a solution for an adequate workspace for surgical robotics system by using a
6 DOF robot with obtainable closed form IK. We mean by Adequate Workspace; that the
workspace is convenient for human to coexist with robot either in a collaborative manner or a
non-collaborative manner. Where by solving IK we can get maximum 8 solutions, which allow
doctors to choose the most suitable configuration during the operation. The suitable configuration
could be the one which give doctors more space, mobility, visibility, etc. For solving the problem
of IK, the kinematics model needs to be determined. The analysis of kinematic can solve the
problem of mapping the relation of the joints angle and the end effector pose. This is the
theoretical basis of motion control and one of the most important steps to realize close-loop
control accurately [9]. This paper work is applied on the UR3 robot, one of the popular
cooperative robots in the market [10]. We present the robot forward kinematics and give review
on the available methods for solving the IK problem. A complete IK closed form solution
obtained by mixing the geometric and analytical techniques is presented. The solution for the
joint1 ( ), joint5 ( ), joint6 ( ), and the summation of joints 2, 3 and4 ( = + +
) obtained analytically. Then the values for , , obtained geometrically. The closed form
solution resulting to maximum 8 solutions for a given end-effector pose in task space. However,
for some other serial robots it could be infeasible to obtain the closed form solution. For this
reason, we present the Steps for obtaining IK using The Gauss - Newton iterative method. We
include in this work performance evaluation between IK obtained from the closed form solution
and numerical solution using The Gauss - Newton iterative method.
The paper is organized in this manner. Section 1 describes the puncture robotic system. Section 2
describes the forward kinematics. Section 3 shows the different approaches of IK. Section 4
presents the Experimental Results and evaluation. Finally, Section 5 gives conclusions.

3
2. MIS ROBOTICS SYSTEM
The puncture robotics system is highly demanded in medicine field due to its advantages such as
achieving minimal invasiveness, accuracy, efficiency, and stability. The system is based on
Computerized Tomography (CT) image processing and its three-dimensional reconstruction that
guide a 6 DOF robot toward precise positioning for MIS. The system is illustrated in Figure 1; its
operation is explained in the following steps. First step the patient is required to do CT scan. Then
a three-dimensional model is reconstructed from the CT scan image of the patient. Through the
three-dimensional model doctor can observe and diagnose the disease. Second step the doctor
determines the position of the puncture target point and insertion point coordinates. The
connection between the target point and insertion point is the green line in Figure 1; this line
represents the puncture route. The route must avoid the patient’s bones, blood vessels, and other
organs. The accurate puncture route determines the quality of the puncturing operation. Then the
target point and insertion point coordinates are sent to the robot through the data processing
computer. The robot end-effector is a needle guide tube shown in Figure 2, accurately positions
the needle to the patient’s skin according to the puncturing route direction. Finally, the needle
insertion is done manually by the doctor.
2.1 Experimental Setup
We developed a computer Graphical User Interface GUI visualization system for doctors based
on the CT image. For simulating the system, we designed a 3D model typify the chest. The
experimental setup is shown in Figure 2. The marks on the 3D model in black and white colours
are for image processing purposes. Next step we do CT scan for the 3D model. We insert these
images in our developed GUI system. The doctor can choose the insert point and target point
through the GUI system, the full system include the vision implementation on an animal
experiment is described in details in our previous work in [11]. Then the robot is commanded to
position the end effector at the insertion point. This step is the concern of this paper work. As by
conducting the work in this paper, we are able to offer the doctor multiple robot configurations to
choose from them the most adequate one for him. The coming sections explain the steps to obtain
the IK solutions.

International Journal of Adv
Figure1. Puncture robotics system, consists of a 6Dof robot manipulator and the computer for image
Figure2. Experimental setup, showing the GUI, 3D chest model and ne
3. FORWARD KINEMATICS
Kinematic modelling based on the Denavit
parameters are minimal representation of the robot kinematics, which consists of 4 parameters (
a , d , α , θ ). The UR robot design and its free body diagram (FBD) with links reference frames
shown in Figure 3. The DH parameters are shown in
define the transformation from coordinat
elementary sequences of rotations and translations
then a translation about the z
rotation around x axis by angle
Puncture robotics system, consists of a 6Dof robot manipulator and the computer for image
processing and robot control
Experimental setup, showing the GUI, 3D chest model and needle guide tube end
INEMATICS
Kinematic modelling based on the Denavit-Hartenberg (D-H) parameters [12]
). The UR robot design and its free body diagram (FBD) with links reference frames
. The DH parameters are shown in Table 1Table 1. These 4 parameters can
define the transformation from coordinate frame link i + 1 to frame i in terms of four
elementary sequences of rotations and translations [13], [14], first a rotation around
axis by d followed by translation about x axis by
axis by angle α . This transformation can be represented as a matrix
pert Systems (JARES) Vol.1, No.4
4
Puncture robotics system, consists of a 6Dof robot manipulator and the computer for image
edle guide tube end-effector
[12]. The DH
). The UR robot design and its free body diagram (FBD) with links reference frames
. These 4 parameters can
in terms of four
, first a rotation around z axis by θ
axis by a and then
. This transformation can be represented as a matrix A

A(a , θ , d
A =
Cθ −Sθ 0 0
Sθ Cθ 0 0
0
0
0
0
1 0
0 1
A =
C
S
Then the transformation matrix for the End Effector with respect to the base frame is obtained by
multiplying the transformation matrix for each join gradually from joint 1 to joint
(n = 6). Transformation matrix
A(q , … ,
From these formulas above, we should have a forward kinematics representation of the robot.
Figure 3
d , α ) = Rz(θ )Tz(d )Tx(a )Rx(α )
1 0 0 0
0 1 0 0
0
0
0
0
1 d
0 1
1 0 0 α
0 1 0 0
0
0
0
0
1 0
0 1
1 0 0 0
0 Cα −Sα 0
0
0
Sα
0
Cα 0
0 1
Cθ −Cα Sθ Sα Sθ a Cθ
Sθ Cα Cθ −Sα Cθ a Sθ
0 Sα Cα d
0 0 0 1
multiplying the transformation matrix for each join gradually from joint 1 to joint
). Transformation matrix A as function of joints position is
q ) = A ≡
R × P ×
0 1
3. UR Robot FBD with links reference frames
5
(1)
(2)
multiplying the transformation matrix for each join gradually from joint 1 to joint n, in our case
(3)

6
Table 1. UR Robot DH parameters
joint (rad)
(m) (m) (rad)
1 0 2⁄
2 0 0
3 0 0
4 0 2⁄
5 0 − 2⁄
6 0 0 0
4. INVERSE KINEMATICS
The problem of inverse kinematics can be stated as follow: what joints variatesq (i = 1 → 6) for
a desired End Effector position and orientation n , n , … p , p . In the field of engineering
application, inverse kinematics is more important than forward kinematics. It’s the base of motion
planning and trajectory control. Obtaining the closed form solution analytically is not feasible for
many cases. Thus the need for obtaining the inverse kinematics numerically is significant. For
the Closed form solution, there are two sufficient conditions in order to get analytical closed-form
solution [13], [15], [16]. First if there are 3 adjacent axes of the joints intersect at one point, such
as in manipulators with spherical wrist. Second if there are 3 adjacent axes of the joints parallel to
each other. Fortunately The UR3 robot meets the second condition. So, the closed-form solution
is feasible. Next, the closed form solution is derived, and then we show an alternative method
using The Gauss - Newton iterative algorithm.
4.1 Closed Form Solution
The problem of the inverse kinematics that it does not have unique solution and this could be a
problem in trajectory planning. The UR3 robot has 8 solutions for the end effector. We say that
the shoulder q have two configurations (Right-Left), the elbow q and q have two
configurations (Up-Down) then the wrist q has two configurations (Folded-Unfolded). Here we
present complete solution using a mix between analytical and geometric techniques. We start by
getting the analytical solution for q , q , q and q . The desired end effector pose is given in
this form
T =
n o a p
n o a p
n a a p
0 0 0 1
(4)
Where the desired orientation and position is

7
R ×
=
n o a
n o a
n o a
, P ×
=
P
P
P
(5)
From the kinematics transformation matrix in equation (3) we infer that
A(q , … , q ) = T (6)
Where;
A(q , … , q ) = A A A A A
(7)
T(q ) = ( A) ∗ T (8)
Then we do some manipulation to find the solutions. First using the equations (7) and (8), which
are equivalent, to find q , q and q .
q is found from comparing 3rd and 4th Columns for the 3rd Row of A and T , as
q = atan2 d , ± d a − p + (p − d a ) − d
− atan2 d a − p , p − d a
(9)
There are two solutions for q the (Right and Left) shoulder configurations. We notate the value
obtained from equation (9) using the (+ve) sign with q , and the one from the (–ve) sign
withq , .
q andq can found From comparing 1st and 2nd Columns for the 3rd row of A and T obtained
from the equations (7) and (8) , where
q = atan2 ± n S − n C + o S − o C , a S − a C (10)
q have two solutions, the one obtained from using the +ve sign in equation (10) and substituting
with q , notated as q , . The one obtained from using the -ve sign in equation (10) and
substituting with q , notated as q , . Later we will get another two solutions for q from the
wrist configurations, so we do it step by step.
q = atan2
−o S − o C
S
,
n S − n C
S
(11)

8
Also there are two solutions for q . First isq , , which obtained from substituting in equation
(11) by q , andq , . Second isq , , which obtained from substituting in equation (11)( by
q , and q , . The full derivation steps for q , q and q are presented in our previous work in
[15].
Next, q = (q + q + q ) is obtained from coming two new equations (12) and (13).
A(q , … , q ) = A A A A (12)
T(q , q ) = T A ( A) (13)
These two equations are equivalent. By observing the equations we found that the 3rd row of the
1st column in A is
A(3,1) = sin(q ) (14)
And the 3rd row of the 3rd column in A is
A(3,3) = −cos(q ) (15)
And there equivalences in in T are;
T(3,1) = n C C − a S − o C S
(16)
T(3,3) = −o C − n S (17)
Where C = cos (q ) , and S = sin(q ) , similarly C = cos (q ) , and S = sin(q ) . Hence,
q = atan2( A(3,1), − A(3,3)) = atan2( T(3,1), − T(3,3))
(18)
q = atan2(n C C − a S − o C S , o C + n S ) (19)
Consequently, we have two solutions for q . The one obtained by Substituting q , and q , in
equation (19) is q , , and q , when substituting by q , and q , .
Next step is to get q and q from the geometry of the robot. In Figure 3, the robot FBD, it is
shown that joints 2, 3 and 4 are parallel, and it can be seen that reference frame 4 is shifted from
joint 4 by the distance d . And by excluding joint 5 and 6, the problem is reduced into a planer
robot to be illustrated as shown in Figure 4. For solving the problem, the position at joint 4 is
required. We can get the position at the origin of reference frame 4 from T in equation (13), as
the position p is the 4th column with respect to the base frame. We found the values for
p = p p p are;

9
p = p − a d + d o C + d n S (20)
p = p − a d + d o C + d n S (21)
p = p − a d + d o C + d n S (22)
p has two solutions for each q . So we get p , = p , p , p , from substituting in
equations (20) (21) (22) by q , , respectively for p , substituting by q , .
Then from the robot geometry top view shown in
Figure4(b) we can extract some other date. First the projection length (r ) of links 2 and 3, can be
derived as follow
l = p + p (23)
r = l − d
(24)
By using the r value, we can estimate the other parameters from the side view in Figure 4(a),
where the height in the z direction r is
r = p − d (25)
And
r = r + r
(26)
Here also have two solutions for each of (l,r r and r ) according to which p is used. Where
(l ,r , r , r , ) obtained by p , , and (l ,r , r , r , ) obtained byp , .
Also q3 can be calculated from Figure 4(a), the side view. As we can get these two relations
r = a C + a C
(27)
r = a S + a S (28)
Then By squaring and summing the two equations (27) and (28) and applying the sum and
difference trigonometric we get
r + r − (a + a ) = 2a a (C C + S S ) = 2a a cos(q − q ) (29)

10
Since;
cos(q − q ) = cos (q ) ≡ C (30)
Then
C =
r + r − (a + a )
2a a
(31)
So
sin(q ) = ± 1 − C (32)
Therefore
q = atan2 ± 1 − C , C (33)
There are four solutions for q depends on which (l,r r and r ) is used. Where q , obtained
from +ve solution in equation (33) and q , obtained from -ve solution substituting by
(l ,r , r , r , ). Similarly, q , obtained from +ve solution in equation (33) and q , obtained
from -ve solution substituting by (l , r , r , r , ). For now we have solutions for q
Next, to compute q we need to extract α and β, shown in Figure 4(a). αand β can be calculated
as follow
α = atan 2(r , r ) (34)
β = atan2(a S a + a C )
(35)
Where α have two solutions based on which r , r are used, where (l ,r , r , r , → α ) and
(l , r , r , r , → α ). In the other side, β have four solutions based on which q is used, where
( q , → β ), ( q , → β ), ( q , → β ) and ( q , → β ). From the same figure it is shown that
q = α − β (36)
q have four solutions , where ( q , =α − β ), ( q , =α − β ), ( q , =α − β ) and ( q , =α −
β ). For the four solutions of q and q , a set of two of them ( q , , q , , q , q , ) were obtained
at the right shoulder configuration (q , ), and the other set ( q , , q , , q , q , ) are obtained at
the left configuration (q , ). The set from the right configuration have no problem. The left
configuration have no problem withq and q because they were calculated based on the
configuration of q , but the problem is in the other 3 joints as to calculate q . Therefore, for the
left configuration at q , , q must be subtracting from pi, equivalent to mirroring around z-axis
and q3 must be negate by take the negative of it, equivalent to mirroring around x-axis. Hence,
the new values at the left configuration are

By using these new values for q
At this level, four different solutions of the inverse kinematics are obtained. The solutions have
two configurations for the shoulders (Right
still two solutions for the wrist configuration (Folded
that q in equation (11) is dependent on
configuration, then q is the only
dependent on q and q . Therefore by flipping
newq . The two new flipped values for
(q1,2
). Then By following the same steps from equation
end up with new four solutions. The eight solutions are arranged and shown in
Figure4. Robot geometry for joints 2, 3 and 4 FBD (a) side view, (b) top view
q , = π − q ,
q , = π − q ,
q , = −q ,
q , = −q ,
q and q , the four solutions of q can be calculated from
q = q − q − q
two configurations for the shoulders (Right- Left) and two for the elbows (Up- Down). There are
still two solutions for the wrist configuration (Folded-Unfolded) as shown in Figure
is dependent on q and q ; and since q is fixed in both wrist
is the only dependent variable. Similarly for q in equation
. Therefore by flippingq , it can leads to new q , consequently for
. The two new flipped values forq are (q , = −q , ) at (q , ), and ( q
). Then By following the same steps from equation (19) to (38) using the new values, it will
end up with new four solutions. The eight solutions are arranged and shown in Table
geometry for joints 2, 3 and 4 FBD (a) side view, (b) top view
11
(37)
can be calculated from
(38)
Down). There are
Figure 5. We found
is fixed in both wrist
in equation (19) is
, consequently for
q5,4
= −q5,2
) at
using the new values, it will
Table 2.
geometry for joints 2, 3 and 4 FBD (a) side view, (b) top view

Figure 5. Joints 4, 5 and 6 at two different configurations Folded (a) and Unfolded (b)
Table 2. The inverse kinematics solutions for 8 configurations
Configuration
Right-Down-Fold
Right-Up- Fold
Left-Down- Fold
Left-Up- Fold
Right-Down-Unfold
Right-Up- Unfold
Left-Down- Unfold
Left-Up- Unfold
4.2 Numerical Solution
Numerical method is an alternative way for finding the inverse kinematics, The Gauss
iterative method can be used due to the nonlinearity of the model
due to the presence of the sines and cosines in the model. For implementing the Gauss
iterative method, the Jacobian matrix need to be calcul
consist of the two parts; 1st is the linear Jacobian
Jacobian ( 3 × n) matrix, where
J =
Jv
Jw
; where Jv =
. Joints 4, 5 and 6 at two different configurations Folded (a) and Unfolded (b)
. The inverse kinematics solutions for 8 configurations
Joint1 Joint2 Joint3 Joint4 Joint5 Joint6
q1,1
q2,1
q3,1
q4,1
q5,1
q
q1,1
q2,2
q3,2
q4,2
q5,1
q
q1,2
q2,3
q3,3
q4,3
q5,2
q
q1,2
q2,4
q3,4
q4,4
q5,2
q
q1,1
q2,5
q3,5
q4,5
q5,3
q
q1,1
q2,6
q3,6
q4,6
q5,3
q
q1,2
q2,7
q3,7
q4,7
q5,4
q
q1,2
q2,8
q3,8
q4,8
q5,4
q
Numerical method is an alternative way for finding the inverse kinematics, The Gauss
iterative method can be used due to the nonlinearity of the model [17]. The nonlinearity caused
due to the presence of the sines and cosines in the model. For implementing the Gauss
iterative method, the Jacobian matrix need to be calculated. The Jacobian matrix is (
consist of the two parts; 1st is the linear Jacobian Jv (3 × n) matrix, and the 2nd is the angular
) matrix, where n is the robot DOF, in our casen = 6.
δPx
δq1
δPx
δq2
…
δPx
δq6
δPy
δq1
δPy
δq2
…
δPy
δq6
δPz
δq1
δPz
δq2
…
δPz
δq6
and Jw = z1
0
z2
0
… z6
0
12
. Joints 4, 5 and 6 at two different configurations Folded (a) and Unfolded (b)
Joint6
q6,1
q6,1
q6,2
q6,2
q6,3
q6,3
q6,4
q6,4
Numerical method is an alternative way for finding the inverse kinematics, The Gauss - Newton
. The nonlinearity caused
due to the presence of the sines and cosines in the model. For implementing the Gauss - Newton
ated. The Jacobian matrix is (6 × n) matrix
) matrix, and the 2nd is the angular
(39)

13
Zi
0
(i = 1 → 6) Is the 3rd column of the transformation matrixAi
0
, which represents the Z axes of
the rotation matrix. The differential kinematics is represented in this form
X˙ = Jq˙ (40)
Where X˙ is a 6x1 vector of the linear and angular velocities, and q˙ is a 6x1 vector for the joints
velocities. For a time instance
∆X = J. ∆q
Xd − X0 = J qd
− q0
(41)
Where Xdand X0 are the desired and initial position respectively. qd
andq0
are the desired and
initial joint positions respectively. Then the desired velocity can be estimated by inverting the
Jacobian matrix in this way
qd
= q0
+ J 1
∆X (42)
So
qd
= q0
+ J 1 ∆Xv
∆XR
(43)
Where ∆Xvis 3 × 1 vector of the end effector linear velocity.∆XR Is 3 × 1 vector representing the
angular velocity ω in x, y, zdirections.∆Xvis the difference between the desired position Pd and the
current initial positionP0 in x, y, z.
∆Xv = Pxd,yd,zd − Px0,y0,z0 (44)
And the angular velocity ∆XR is represented as
∆XR = R˙ . R0
T
= s ωx,y,z (45)
Where R˙ is the derivative of the rotation matrix, R0 is the initial orientation, and S (·) is a skew-
symmetric matrix that, for the 3-dimensional case, has the form
s(ω) =
0 −ωz ωy
ωz 0 −ωx
−ωy ωx 0
(46)
By Combining the position and orientation we get the equation for the inverse deferential

14
kinematics as follow
qd
= q0
+ J ∗
Pxd − Px0
Pyd − Py0
Pzd − Pz0
ωx
ωy
ωz
(47)
Where J is the pseudo inverse of the Jacobian. As In some cases due to singularity it is not
possible to invert the Jacobian matrix; therefore we need to use a numerical approximation
method such as pseudo inverse. In case if J matrix is full rank, the pseudo inverse will be same as
the inverseJ = J 1
, otherwise it will be calculated as J = JT
JJT 1
.
For now The Gauss - Newton iterative method in equation (47) is ready for implementation; it
required an initial guess for the joints position. The good initial guess usually has good
convergence properties [18].
5. METHODS EVALUATION
The closed form solution is an optimum solution for the inverse kinematics, in case if it’s
obtainable. The 8 solution of the UR robot shown in Figure6, for the shoulder, elbow, and wrist
configurations, at end effector pose T .
T =
−0.8421 −0.4673 0.2693 0.1942
−0.5196 0.5690 −0.6374 −0.3593
0.1446 −0.6766 −0.7220 0.1701
0 0 0 1
The axis angle representation for T . is Xdesired= {0.1942, -0.3593, 0.1701, -0.8567, 2.7197, -
1.1407}. The 8 solutions for the joints at this pose are shown in
Table 3.
However there are some restrictions should be handled due to singularities. For instance, the
robot has singular value if S5 = 0 at (q5
= 0, q5
= π), therefore q6
in equation (11) is not defined,
and we can get q6
just when (S5 ≠ 0). Also the physical limits for the robot should be considered,
especially when getting the values forq2
, q3
andq4
, and to be sure that the desired end effector
pose within the robot workspace. In the other side, the numerical method can provide only one

solution, with a surprising configuration from one of the 8 solutions. We can control over the
output of the numerical method by setting arbitrarily the initi
desired configuration is elbow (up) then the initial condition for
Similarly for (left and right) shoulder the
From the point of computational time, the closed form solution for sure can fulfil the real time
control requirement. The numerical method is much slower; enhancing its computational time is
mainly depends on the initial conditions. Notice that if the initial condition for t
method is far away from the desired pose, then it could take long time or it might not converge at
all. So when we evaluated the computational time for both methods, we just considered the cases
which have good estimate of the initial conditio
time to get the inverse kinematics of a single point for the numerical method is 30~50
for the closed form solution is 1~2
in term of computational time.
For evaluating the accuracy of both methods, we considered the Max Absolute Error (MAE)
between the desired position and the results of IK of both methods solutions. The pose (position +
orientation) MAE of the numerical method is about (
solution about ( 0.2 ∗ 1e ). The closed form solution absolutely more accurate, since the
numerical method is an approximation method; however both methods are acceptable regarding
to the limitations of each of them.
configurations, thus for adequate workspace in our puncturing robotics system. It can be seen
from figure that each configuration gives more space in certain locations in the workspace;
demonstrated by the shaded shapes. Doctors can choose the most suitable configuration according
to their preferences during the operation. Doctors heights might vary from one to another, so
elbow (U-D) configurations could be very helpful in that case. In case if doctors
the left or the right side of the puncture insertion point, the shoulder (R
very helpful in that case. Anyhow the best configuration can differ from one doctor to another, so
this option in our system could make
more adequate.
a) Left- Up-
output of the numerical method by setting arbitrarily the initial conditions. For instance, if the
desired configuration is elbow (up) then the initial condition for q2
can be set in that range.
Similarly for (left and right) shoulder the q1
can have initial condition in the desired range.
omputational time, the closed form solution for sure can fulfil the real time
mainly depends on the initial conditions. Notice that if the initial condition for t
which have good estimate of the initial condition for the numerical method. The computational
time to get the inverse kinematics of a single point for the numerical method is 30~50
for the closed form solution is 1~2ms. The difference is very obvious between the two methods
orientation) MAE of the numerical method is about ( 0.6 ∗ 1e ), and for the closed form
). The closed form solution absolutely more accurate, since the
to the limitations of each of them. The IK closed form helped us in finding several robot
the shaded shapes. Doctors can choose the most suitable configuration according
D) configurations could be very helpful in that case. In case if doctors prefer to stand at
the left or the right side of the puncture insertion point, the shoulder (R-L) configuration could be
this option in our system could make the coexistence of human and robot in the same workspace
- Unfold b) Left- Up- Folded
15
al conditions. For instance, if the
can be set in that range.
can have initial condition in the desired range.
omputational time, the closed form solution for sure can fulfil the real time
mainly depends on the initial conditions. Notice that if the initial condition for the numerical
n for the numerical method. The computational
time to get the inverse kinematics of a single point for the numerical method is 30~50ms, while
. The difference is very obvious between the two methods
), and for the closed form
). The closed form solution absolutely more accurate, since the
The IK closed form helped us in finding several robot
the shaded shapes. Doctors can choose the most suitable configuration according
prefer to stand at
L) configuration could be
the coexistence of human and robot in the same workspace

c) Left- Down
e) Right- Up
g) Right- Down
Figure6. UR robot IK solutions, the shaded shapes demonstrate the free space for each configuration
Down- Unfold d) Left- Down- Folded
Up- Unfold f) Right- Up- Folded
Down- Unfold h) Right- Down- Folded
UR robot IK solutions, the shaded shapes demonstrate the free space for each configuration
16
UR robot IK solutions, the shaded shapes demonstrate the free space for each configuration

17
Table 3. TheUR3 inverse kinematics for X= {0.1942, -0.3593, 0.1701, -0.8567, 2.7197, -1.1407}
Configuration Joint1 Joint2 Joint3 Joint4 Joint5 Joint6
Right-Down-Fold -0.73508 2.370465 1.882823 -1.96721 1.274286 0.113862
Right-Up- Fold -0.73508 -2.21214 -1.88282 6.381036 1.274286 0.113862
Left-Down- Fold -0.73508 3.086748 0.813237 -4.7555 -1.27429 -3.02773
Left-Up- Fold -0.73508 -2.44049 -0.81324 2.398207 -1.27429 -3.02773
Right-Down-Unfold 1.756916 0.776095 -1.87212 -1.22744 -1.42357 -0.36595
Right-Up- Unfold 1.756916 5.367374 1.872123 -9.56297 -1.42357 -0.36595
Left-Down- Unfold 1.756916 0.054278 -0.82719 1.591031 1.423566 2.775645
Left-Up- Unfold 1.756916 5.568666 0.827187 -5.57773 1.423566 2.775645
6. CONCLUSION
In this paper we presented the derivation steps of the IK using a combination of analytical and
geometric techniques. Closed form IK ensured the most important characteristics of real-time and
accuracy of the robot. The innovative application of this work is used in the precise positioning of
medical puncture surgery. We showed that how utilizing a robot with obtainable closed form
solution IK, such as UR, in puncture robotics system can lead for more adequate workspace. The
multiple solutions of IK allow us to develop the system, so that we can offer doctors more robot
configurations during the operation. The selection of the configuration might be according to the
one best fit the doctors physically, gives more space in certain direction, gives more visibility,
etc. the best configuration can differ from one doctor to another, so this option in our system
makes the coexistence of human and robot in the same workspace more adequate.
REFERENCES
[1] M. Piesing, “Medical robotics: Would you trust a robot with a scalpel?,” The Guardian, 2014.
[2] Integris, “Benefits of Robotic Surgery,” UC Health. 2013.
[3] P. Dario, E. Guglielmelli, B. Allotta, and M. C. Carrozza, “Robotics for medical applications,” IEEE
Robot. Autom. Mag., vol. 3, no. 3, pp. 44–56, 1996.
[4] O. A. Olanrewaju, A. A. Faieza, and K. Syakirah, “Current trend of robotics application in medical,”
in IOP Conference Series: Materials Science and Engineering, 2013, vol. 46, no. 1, p. 012041.
[5] B. Preising, T. C. Hsia, and B. Mittelstadt, “A Literature Review: Robots in Medicine,” IEEE Eng.
Med. Biol. Mag., vol. 10, no. 2, pp. 13–22, Jun. 1991.
[6] R. H. Taylor, “A perspective on medical robotics,” Proceedings of the IEEE, vol. 94, no. 9. pp. 1652–
1664, Sep-2006.
[7] G. Jiang, M. Luo, K. Bai, and S. Chen, “A Precise Positioning Method for a Puncture Robot Based on
a PSO-Optimized BP Neural Network Algorithm,” Appl. Sci., vol. 7, no. 12, p. 969, Sep. 2017.

18
[8] C. Bernard, H. Kang, S. K. Singh, and J. T. Wen, “Robotic system for collaborative control in
minimally invasive surgery,” Ind. Robot An Int. J., vol. 26, no. 6, pp. 476–484, Aug. 1999.
[9] M. Ito, K. Kawatsu, and M. Shibata, “Maximal admission of joint range of motion based on
redundancy resolution for kinematically redundant manipulators,” SICE Annu. Conf. 2010, …, pp.
778–782, 2010.
[10] Universal Robots, “UR3 Robot,” 2017. [Online]. Available:
https://www.universal- robots.com/products/ur3-robot/. [Accessed: 14-May-2018].
[11] G. Jiang, K. Bai, L. Lu, M. Luo, O. Abdelaziz, and S. Chen, “Vision solution for an assisted puncture
robotics system positioning,” Appl. Opt. Vol. 57, Issue 28, pp. 8385-8393, vol. 57, no. 28, pp. 8385–
8393, Oct. 2018.
[12] J. Denavit and R. S. Hartenberg, “A kinematic notation for lower-pair mechanisms based on metrics,”
Trans. ASME. J. Appl. Mech., vol. 22, pp. 215–221, 1955.
[13] P. I. Corke, Robotics,Vision and Control Fundamental Algorithms in MATLAB. Springer, 2011.
[14] B. Siciliano, L. Sciavicco, L. Villani, and G. Oriolo, Robotics: Modeling, Planning, and Control.
London: Springer London, 2009.
[15] S. Chen, M. Luo, O. Abdelaziz, and G. Jiang, “A general analytical algorithm for collaborative robot
(cobot) with 6 degree of freedom (DOF),” in Proceedings of the 2017 IEEE International Conference
on Applied System Innovation: Applied System Innovation for Modern Technology, ICASI 2017,
2017, pp. 698–701.
[16] Y. Li and Q. Xu, “Kinematic analysis of a 3-PRS parallel manipulator,” Robot. Comput. Integr.
Manuf., vol. 23, no. 4, pp. 395–408, Aug. 2007.
[17] W. Khalil and E. Dombre, Modeling, Identification and Control of Robots. Kogan Page Science,
2004.
[18] J. Hollerbach, W. Khalil, and M. Gautier, “Model Identification,” in Springer Handbook of Robotics,
Cham: Springer International Publishing, 2016, pp. 113–138.
AUTHORS
Omar Abdelaziz persued his PhD in University of science and technology of
China. He is associate lecturer in Egyptian Russian University, Egypt. And
Graduate researcher at Institute of intelligent Manufacturing Technology, Jiangsu
industrial and technology research institute, China. In 2011 He had received master
degree of mechanical engineering from UTHM, Malaysia. Omar’s research interest
in robotics and intelligent technology. Including topics such as human robots
collaboration, serial robots kinematics and dynamics, and Robot control.

19
Minzhou Luo had received his M.S. degree in Mechanical Engineering from
Hefei University of Technology in 2002. He was awarded his Ph.D. degree from
University of Science and Technology in 2005.he achieved the researcher of Hefei
Institute of Physical Science, Chinese Academy of Science. His research direction
is the humanoid robot, industrial robot, Mechatronics, intelligent machine and so
on.
Guanwu Jiang is a Ph.D. candidate at University of Science and Technology of
China since September 2015. He received the master degree at Southwest
University Science and Technology. He studied the kinematics technology and
medical image processing technology of medical robots.
Saixuan Chen is a Ph.D. candidate at University of Science and Technology of
China since September 2015. He received the bachelor and master degree at
Changzhou University. His research interests include the humanoid robot, the
structure design of the flexible mechanism, kinematic control of robots, and
algorithms for collision detection/reaction.

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