The Geometry of Visual Coordination

Abstract

We present a new model for the perceptual reasoning involved in hand/eye coordination, and we show how this model can be developed into a control mechanism for a robot manipUlator with a visual sensor. This new approach overcomes the hig, h computational cost, the lack of robustness, and the need for precise calibration that plague traditional approaches. At the heart of our model is the Perceptual Kinematic Map (PKM), a direct mapping from the control space of the manipulator onto a space defined by a set of measurable image parameters. By exploring its workspace, the robot learns, qualitatively, the topology of its PKM and thus acquires the dexterity for future tasks, in a striking parallel to biological systems.