Compensation of Aprupt Motion Changes in Target Tracking by Visual Servoing

This paper describes a real time visual target tracking using the generalized likelihood ratio (GLR) algorithm. We first introduce the visual servoing approach and the application of the task function concept to vision-based tasks. Then, we present a complete control scheme which explicitly enables to pursue a moving object. In order to make the tracking errors as low as possible, we use the GLR test, an algorithm able to detect, estimate and compensate abrupt jumps in target motion. Finally, real-time experimental results using a camera mounted on the end effector of a six-d.o.f. robot are presented. 1 Introduction Visual servoing [5] [6] [8] [10] is now a classical approach to realize various robotics tasks (positioning, grasping, target tracking, etc) in closed loop with respect to visual data. As far as target tracking is concerned, Papanikolopoulos et al. [8] use classical approaches in control theory to track a moving object. However, they consider the object motion as disturb..