Real time implementation of a selective attention model for the intelligent robot with autonomous mental development

Abstract

We propose a biologically motivated selective attention model to find an object based on context free search for an intelligent robot with an autonomous mental development (AMD) mechanism. For real-time operation of the selective attention model in the robot system, we have considered a way to reduce the computational load of the selective attention model, which uses a simplified symmetry operation with retina-topic sampling and look-up table in the localized candidate attention region. As a result, our model can perform within 270 ms at Pentium-4 2.8Ghz, and obtain a plausible human-like visual scan path in order to pay attention to an object preferentially. Then, we implemented an intelligent mobile robot with selective attention for an AMD mechanism.