Visual feedback control of a vehicle based on MHE directly using partial marker information

Abstract

Motion capture systems are widely used for measuring the position and the orientation of objects. It detects the markers attached to the objects, but they are sometimes lost sight by occlusion and dead angle of sensor. It becomes a problem that markers to determine the coordinates of the object are not measured. Thus, it is necessary to estimate state suppressing the influence of missing measurement. In this study, we propose a Moving Horizon Estimation for state estimation to tackle this issue. If any markers are not measured because of occlusion, MHE can estimate position of the robot uniquely because it optimizes the evaluation considering the error of available measurement and motion dynamics of the vehicle. In our previous study, we applied MHE for estimation of the position and heading angle of the vehicle robot with markers. In this paper, we will show the application of it to the visual feedback control for the robot using estimation value at real time. we will prove that MHE is effective because it can suppress the influence of occlusion and rapid change of input.