Performance tests of partitioned approaches to visual servo control

Visual servoing has been a viable method of robot manipulator control for more than a decade. Image-based visual servoing (IBVS), in particular, has seen considerable development in recent years. Recently, a number of researchers have reported tasks for which traditional IBVS methods fail, or experience serious difficulties. In response to these difficulties, several methods have been devised that partition the control scheme, allowing troublesome motions to be handled by methods that do not rely solely on the image Jacobian. To date, there has been little research that explores the relative strengths and weaknesses of these methods. In this paper we present such an evaluation. We have chosen three recent visual servo approaches for evaluation, in addition to the traditional IBVS approach. We posit a set of performance metrics that measure quantitatively the performance of a visual servo controller for a specific task. We then simulate each of the candidate visual servo methods for four canonical tasks, under perfect and nonideal experimental conditions.