DETECTION AND TRACKING FOR ROBOTIC VISUAL SERVOING SYSTEMS

Robot manipulators require knowledge about their environment in order to perform their desired actions. In several robotic tasks, vision sen sors play a critical role by providing the necessary quantity and qual ity of information regarding the robot's environment. For example, ''v isual servoing'' algorithms may control a robot manipulator in order t o track moving objects that are being imaged by a camera. Current visu al servoing systems often lack the ability to detect automatically obj ects that appear within the camera's field of view. In this research, we present a robust ''figure/ground'' framework for visually detecting objects of interest. An important contribution of this research is a collection of optimization schemes that allow tbe detection framework to operate within the real-time Limits of visual servoing systems. The most significant of these schemes involves the use of ''spontaneous'' and ''continuous'' domains. The number and location of continuous dom ains are,allowed to change over time, adjusting to the dynamic conditi ons of the detection process. We have developed actual servoing system s in order to test the framework's feasibility and to demonstrate its usefulness for visually controlling a robot manipulator. (C) 1997 Else vier Science Ltd.