3D Relative Position And Using Kalman Filter Orientation Estimation For Robot Control

A vision based position sensing system which provides three-dimensional (3D) relative position and orientation (pose) of an arbitrary moving object with respect to a camera for a real-time tracking control is studied in this paper. Kalman filtering is applied to vision measurements for the implicit solution of the photogrametric equations and to provide significant temporal filtering of the resulting motion parameters resulting in optimal pose estimation. Both computer simulation and real-time experimental results are presented to verify the effectivenss of the Kalman filter approach with large vision measurement noise.