Training Robot Arm 5 Degree of Freedom for Tracking the desired route using MLP

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Zahed Kamangar Soran Saeed Asrin Zardoie

Abstract

This paper work presents a new method of controlling the robot arm. The control system is the most important part of industrial robot. In industrial robot arms, it is very important to control the desired path and direction. In this paper, the presented control method is a multilayer neural network. Which controls and compares the location of the joins at the end point of the path relative to the zero position (the beginning of the path-static state). And try to learn the ultimate position of each joints due to changes in angles and direction of movement to carry out the motion process. The superiority of this method is that it can operate without considering 3D space (working space), the dynamic equations, and have Cartesian coordinates of the points on the desired path. Innovating this method of controlling the choice of the route is based on feedback from the vision system and human intelligence. This way, the operator selects and applies how to move the joints and the links of the robot and the method of walking the path. Applying the path through the movement of links and motion of joints and changing their angles in order to reach the end effector to the end point of the path. In this system, using the potentiometers (volumes) as an encoder connected to the axis of the joints, it is possible to obtain the location of the joints on the basis of variations in the voltage range and convert it to the equivalent digital 1024-0 values as has been used the MLP neural network input.

Keywords

Joints, MLP, Degree of freedom, End effector, Zero position, Encoder.

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