Path planning with uncalibrated stereo rig for image-based visual servoing under large pose discrepancy

Although image-based visual servoing provides superior performance in many vision-based robotic applications, it reveals fatal limitations when initial pose discrepancy is large. The feature points may leave the camera's field of view, and also, the robot may not converge to the goal configuration. In this paper, a novel approach is proposed to resolve these limitations by planning trajectories in the image space using uncalibrated stereo cameras. Intermediate views of the robot gripper are synthesized to generate the image trajectories such that the gripper can track a straight path in the three-dimensional workspace. The proposed method utilizes screw motions of the gripper represented in the projective space with the help of the fundamental properties of projective geometry. Computational issues are also considered to enhance the estimation of the projective transformation from initial to goal configuration. The validity of this approach is demonstrated through computer simulations and limited experiments.