To better simulate the attention selection in human visual system

an improved bionic cognitive neural network for robot is proposed.Firstly

to simulate human visual cortex structure

an improved bionic cognitive neural network is established on the basis of the existing models;it adds top-down visual attention from position motor(Position Motor

PM) to receptive field(Receptive Field

RF)

and meanwhile

inferior temporal (Inferior Temporal

IT) no longer receives global visual information and turns to receive local information with bottom-up visual attention

not only reducing the complexity of data processing

but also keeping with human Gestalt psychology.Finally

the model is utilized to realize the robot target recognition and tracking in complex background.Experimental results show that the method can reduce data redundancy and processing time

and also effectively improve the target recognition accuracy in the robot vision system.