Autonomous switching of top-down and bottom-up attention selection for vision guided mobile robots

Abstract

In this paper an autonomous switching between two basic attention selection mechanisms, top-down and bottom-up, is proposed, substituting manual switching. This approach fills the gab in object search using conventional top-down biased bottom-up attention selection: the latter one fails, if a group of objects is searched whose appearances can not be uniquely described by low-level features used in bottom-up computation models. Two internal robot states, observing and operating, are included to determine the visual selection behavior. A vision guided mobile robot, equipped with an active stereo camera, is used to demonstrate our strategy and evaluate the performance experimentally.