Industrialists interested automates their factories to increase production, reduce costs
and improve quality by using robots in leadership and finishing most of the production
processes, where robots characterized as mechanical structures programma
ble to perform
tasks accurate, speed and reliability.
Research depend in concluding the optimal path on generating virtual paths
(triangular, curved, square) reflects the robotic arm movement to reach the target point,
where as it has been known moving time and angles of rotation and torque in the joints
under the influence of gravity through the study of horizontal and vertical movement of the
robotic arm.
A study of suggested trajectories for the robotic arm shows that the best paths on the
safety of robotic arm motors is semi-circular path as limiting the occurrence of mechanical
shocks or the appearance of high values of the joints torques. while showing that the path
that achieves less time to reach the target point and less amount of energy is the triangular
path in the case of horizontal motion of the robotic arm despite the emergence of sharp
deviations in the torque and power schemas as a result of the sudden change in the
direction of movement.
The negative impact of gravity is especially apparent when the second joint up or
down movement, causing the appearance of peaks in energy curve reflects the high values
of determination in this joint.
The robotic manipulator's control process involves many
engineering challenges from mechanical design phase to the phase
of programming. The inverse kinematics problem is one of the most
difficult challenges, as it requires determining the angles
of joints
for a desired position of the end-effector, the difficulty of this
problem comes from the none linearity and the possibility of
multiple solutions or lack of solutions in some cases. Many
solutions were proposed to solve the issue of inverse kinematics;
analytically and numerically in addition to the solutions which
based on artificial intelligence. In this research the solution of
inverse kinematics using Adaptive Neuro-Fuzzy Inference System
was discussed and amendments were proposed and indicated their
usefulness.
