Enhanced solution of inverse kinematics for redundant robot manipulator using PSO

Abstract EN

Kinematics 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.