Passivity-Based Visual Feedback Pose Regulation Integrating a Target Motion Model in Three Dimensions

This paper investigates passivity-based visual feedback pose regulation whose goal is to control a vision camera pose so that it reaches a desirable configuration relative to a moving target object. For this purpose, we present a novel visual feedback estimation/control structure including a vision-based observer called visual motion observer under the assumption that a pattern of the target motion is available for control. We first focus on the evolution of the orientation part and the resulting estimation/control error system is proved to be passive from the observer/control input to the estimation/control error output. Accordingly, we also prove that the control objective is achieved by just closing the loop based on passivity. Then, we prove convergence of the remaining position part of the error system. We moreover extend the present velocity input to force/torque input taking account of camera robot dynamics. Finally, the effectiveness of the present estimation/control structure is demonstrated through simulation.