Fusion of ART-1 and advanced logistic belief neural network for object grasping robot arm

This paper discusses the combination of adaptive resonance theory (ART-1) and advanced logistic belief neural network for controlling robot arms grasping objects. In order for the robot manipulator, end-effectors keep its stability at any given movement; the derivation and maximization of the logarithm-like hood function of the learning rule of the logistic belief network is used.