Development of an Intelligent Robotic Cell

Abstract

In order for a robot to grip an object in a two dimensional environment, the gripping point and the rotation angle of a defined axis of the object are required. This paper presents the results of studies focused on the experimental requirements of an adaptive neural network learning technique for objects recognition and orientation detection. The results show that linking the neural network output to a robot controller achieves good system performance in picking up randomly placed objects. This project continues the current trend of developing intelligent machines in manufacturing.