Image-Based Visual Servoing using improved image moments

Abstract

Visual servoing has played an important role in automated robotic manufacturing systems, of which there is a challenge on how to choose proper image features to enhance system performances. This paper addresses such a challenge by proposing a method consisting of an ameliorative image preprocessing algorithm and an improved image based visual servoing (IBVS) using image moments algorithm. Comparing with traditional IBVS, choosing image moment as the image features can efficiently increase the stability of the visual servoing system and extend the applied range of objects. The obtained image features will then be used to generate the control signals for the robot to track the target object. The Jacobian matrix describing the relationship between the motion of camera and velocity of image features is also discussed. In order to decouple the obtained Jacobian matrix for controlling the motion of camera with individual image features, a sequence control strategy is also introduced.