Sampled visual feedback pose estimation and regulation based on camera frame rates

Abstract

This paper presents visual feedback 3D pose estimation/regulation methodologies in the sampled data setting by camera frame rates. Vision-based estimation/control problems have been studied by a number of research groups. While most works focus on the limitation of measured outputs, they conduct convergence/performance analysis under the assumption that visual measurements extracted from a camera are continuously available. However, the camera frame rates including image processing time often cannot be neglected compared with other computation time. In view of this fact, this paper newly proposes visual feedback pose estimation/regulation techniques under the situation that visual measurements are sampled due to the frame rates. The problem settings are first provided. Then, the pose estimation/regulation methods with sampled visual measurements are proposed. The convergence/performance analysis is conducted by the fusion of a Lyapunov-based approach and an event-triggered control technique. The present analysis scheme provides us guidelines for the design of estimation/control gains guaranteeing desired convergence/performance. The effectiveness of the present technique is verified via simulation and an experiment with real hardware.

Keywords

• vision-based control
• rigid body motion
• passivity
• event-triggered control
• sampled data setting