An integrated position estimation by using optical flow for visual robot navigation

Abstract

A visual integrated position estimation by using simple Optical Flow (OF) is presented for visual robot’s precise navigation. This position estimation consists of a relative and an absolute position estimation. In the relative position estimation, an OF method inspired by honeybee-vision is improved to obtain robot’s relative position. It can measure robot’s translation precisely with regardless of robot’s rotation, while its position errors will be accumulated unavoidably. In the absolute position estimation, an OF-based Kalman Filter (KF) is used to iteratively correct robot’s position errors according the actual and the predicted OF, so the accumulated errors within the relative position estimation is eliminated. As the OF method and the OF-based KF adopt the same method to measure the OF information, the relative position and the absolute position estimation can share input signal and some executive stages for timesaving and costsaving. The experiments using a visual mobile robot in workshop have demonstrated the proposal’s efficiency.