Probabilistic Integration of 2D and 3D Cues for Visual Servoing

Abstract

In this paper we present a new integration method for improving the performance of visual servoing. The method integrates image-based visual servoing (IBVS) and position-based visual servoing (PBVS) approaches to satisfy the widely varying requirements of the visual servoing process. We define an integration rule for IBVS and PBVS controllers. Density functions that determine the weighting factor of each controller are defined to satisfy the above constraints. We prove that this integration method provides global stability, and avoids local minima. The new integration method is validated on positioning tasks and compared with other switching methods