Gabor Filters for Object Localization and Robot Grasping

We present a system for learning the 3 DOF finepositioning task of a robot manipulator (Puma 260) using a gripper mounted camera. Small lateral gripper-target misalignments are corrected in one step. Larger ones employ a previous coarse adjustment move in order to bound the parallax effects of the close camera focus. We build objectspecialized, neural network-based pose estimators with a rather small set of Gabor filters. Gabor filters perform a spatially localized frequency analysis and resemble the spatial response profile of receptive fields found in visual cortex neurons. The system demonstrates efficiency w.r.t. speed and accuracy, as well as robustness against changing illumination and object conditions.