Bionic tracking method by hand & eye-vergence visual servoing

Abstract

Animals rotate their eyes to gaze at the target prey, enhancing the ability of measuring the distance to the target precisely for catching it. These animals, visual tracking includes the triangular eye-vergence control and their body’s motion control by visual servoing. The research aims to realize a bionic robot tracking performance, in which the body links moves together with eyes’ view orientation. This paper proposed a hand & eye-vergence dual control system which included two feedback loops: an outer loop for conventional visual servoing to direct a manipulator toward a target object and an inner loop for active motion control of binocular cameras to change the viewpoint along with the moving object to give an accurate and broad observation. This research also foused on how to compensate a fictional motion of the target seen by camera images in an eye-in-hand system, where the camera was fixed on the end-effector and moved together with the hand motion. A robust motion-feedforward (MFF) recognition method is proposed to compensate the fictional motion of the target based on the manipulator’s joint velocity, then the real motion of the target seen by camera images is extracted, which can improve the feedback image sensing unit to make the whole servoing system dynamically stable. The effectiveness of the proposed hand & eye-vergence visual servoing method is shown by tracking experiments using a 6-DoF robot manipulator and a 3-DoF binocular vision system.