Compensation of abrupt motion changes in target tracking by visual servoing

Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. Abstract This paper describes a real time visual target tracking using the generalized likelihood ratio (GLR) algorithm. We rst 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 eeector of a six-d.o.f. robot are presented.