Enhanced Solution of Inverse Kinematics for Redundant Robot Manipulator Using PSO
Engineering and Technology Journal,
2019, Volume 37, Issue 7A, Pages 241-247
AbstractKinematics of the robot is divided into two parts: the forward
kinematics, which evaluates the end-effector’s position from joint angles, and the
inverse kinematics, which demonstrates the joint angles from the end-effector's
position. The solution of the inverse kinematics problem is too difficult and
complicated for the redundant robot arm manipulator. A Particle Swarm
Optimization (PSO) algorithm is an effective method to solve global optimization
problems. This paper presents the solution of inverse kinematics problem of a
three-link redundant manipulator robot arm using PSO without using the inverse
kinematics equations. The circle, square and triangle generated trajectories using
PSO are enhanced as compared with the trajectories of other works. The
enhanced PSO algorithm is successfully found the best generating three joint
angles and the best generating end-effector's position of a three-link robot arm.
Then according to these joints and positions the circle, square and triangle path
trajectories, results are smoother than the path trajectories of other work. This
enhanced solution of inverse kinematics using PSO algorithm is too fast due to
the short elapsed time in every iteration of trajectory. Besides that, these
velocities results have been given evaluated and give an indication that the threelink robot is moving fast during the PSO algorithm. The elapsed time of circle
trajectory equals to 20.903981 seconds, the elapsed time of square trajectory
equals to 11.747171 seconds and the elapsed time of triangle trajectory equals to
15.729663 seconds. MATLAB R2015b program is used in order to simulate all
results. The main benefit of this work is to solve two problems: 1) inverse
kinematics is too complex equations of the three-link robot. The solutions of best
joint angles using PSO are computed within joint limits without using inverse
kinematics equations. 2) Another problem, this work is enhanced three
trajectories with respect to the best joint angles and reaches 96% percent as
compared with another work. The error is too small according to the start and
goal PSO generated points for each trajectory.
 S. Bruno, K. Oussama, “Springer Handbook of
Robotics,” Springer, 2nd edition, Cham, 2016.
 B. Mordechai, M. Francesco, “Elements of
Robotics,” Springer, Cham, 2018.
 W.S. Mark, H. Seth, and V. Mathukumalli,
“Robot Modeling and Control,” John Wiley & Sons,
Inc., 1st edition, 2005.
A. Francesco, B. Alberto, A. Riccardo, and F.
Rodolfo, “A Fuzzy Logic to Solve The Robotic
Inverse Kinematic Problem,” Applied Mechanics and
Materials, Vol. 772, pp. 488-493, 2015.
 M. Shaher, S.A. Zaer, and M.A. Othman,
“Solution of Inverse Kinematics Problem using
Genetic Algorithms,” Applied Mathematics &
Information Sciences, Vol. 10, No. 1, pp. 225-233,
 A.R. Firas, R.K. Azad, and J.H. Amjad, “Inverse
Kinematics Solution of Robot Manipulator EndEffector Position Using Multi-Neural Networks,” Eng.
& Tech. Journal, Vol. 34, No.7, pp. 1360-1368, 2016.
 Z.K. Hind, “Inverse Kinematics Solution for
Redundant Robot Manipulator using Combination of
GA and NN,” Al-Khwarizmi Engineering Journal,
Vol. 14, No. 1, pp. 136-144, 2018.
 A. Zeineb, G. Adel, B.B. Lazhar, H. Mohamed,
and A.A.E. Nasser, “Review of Optimization
Techniques Applied for The Integration of Distributed
Generation From Renewable Energy Sources,”
ELSEVIER, Renewable Energy, Vol. 113, pp. 266-
 V.D. Adrian, “Neural Network based Inverse
Kinematics Solution for Trajectory Tracking of a
Robotic Arm,” ELSEVIER, The 7th Int. Conference on
Interdisciplinarity in Engineering, 2014.
 B. Luigi, M. Claudio, “Trajectory Planning for
Automatic Machines and Robots,” Springer, 2008.
 J.H. Edwin, S. Gilbert, “Calculus Volume 3,”
 S.Y. Xin, “Nature-Inspired Optimization
Algorithms,” ELSEVIER, 1st edition, 2014.
 R. Nizar, M.A. Adel, “Inverse Kinematics Using
Particle Swarm Optimization, A Statistical Analysis,”
ELSEVIER, Int. Conference on Design and
Manufacturing (IConDM), Vol. 64, pp. 1602-1611,
 Z. Panfeng, M. Xihui, M. Zhenshu, and D.
Fengpo, “An Adaptive PSO-Based Method for Inverse
Kinematics Analysis of Serial Manipulator,” Int.
Conference on Quality, Reliability, Risk, Maintenance,
and Safety Engineering (ICQR2MSE), Chengdu,
 A. Kaveh, “Advances in Metaheuristic
Algorithms for Optimal Design of Structures,” chapter
2, Springer, 2014.
 V.D. Adrian, “ANFIS Based Solution to the
Inverse Kinematics of a 3DOF Planar Manipulator,”
ELSEVIER, The 8th Int. Conference on
Interdisciplinary in Engineering, pp. 526-533, 2014.
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