6D Image-based Visual Servoing for Robot Manipulators with uncalibrated Stereo Cameras

Abstract — This paper introduces 6 new image features to provide a solution to the open problem of uncalibrated 6D image-based visual servoing for robot manipulators, where the goal is to control the 3D position and orientation of the robot end-effector using visual feedback. One of the main contributions of this article is a novel stereo camera model which employs virtual orthogonal cameras to map 6D Cartesian poses defined in the Task space to 6D visual poses defined in a Virtual Visual space (Image space). This new model is used to compute a full-rank square Image Jacobian matrix (Jimg), which solves several common problems exhibited by the classical image Jacobians, e.g., Image space singularities and local minima. This Jacobian is a fundamental key for the image-based controller design, where a chattering-free adaptive second order sliding mode is employed to track 6D visual motions for a robot manipulator. Exponential convergence of errors in both spaces without local minima are demonstrated. The complete control system is experimentally evaluated on a real industrial robot. The robustness of the control scheme is evaluated for cases where the extrinsic parameters of the uncalibrated stereo camera system are changed on-line and unknown when the stereo system is manually moved to obtain a clearer view of the task. I