Bee Colony Algorithm application for manipulating metalcastings in SME

The paper presents an application of Bee Colony Algorithm (BCA) for template matching that is used for manufacturing automation in a metalcasting foundry. The paper presents a novel application of BCA for robot pick-and-place operation. To enable robust manipulation by a six axis industrial robot manipulator, it is important that the correct orientation of the parts is input to the manipulator. This orientation is input by a vision system which is then used to orient the robot gripper to correctly handle the part. BCA is used for the purpose of robust template matching by the vision system. The BCA algorithm is inspired by the collective behavior of honey bees to find food sources around the hive, which is one of the Swarm Intelligence (SI) techniques. The Normalized cross-correlation (NCC) function is used as an objection function in the BCA optimization procedure. The results of the BCA computer simulations are shown for different number of food sources.