Adaptive 2.5D Visual Servoing of Kinematically Redundant Robot Manipulators

In this paper, the 3-Dimensional (3D) position and orientation of a camera held by the end-effector of a robot manipulator is regulated to a constant desired position and orientation despite (i) the lack of depth information of the actual or desired camera position from a target, (ii) the lack of a 3D model of the target object, and (iii) parametric uncertainty in the dynamic model of the robot manipulator. Specifically, by fusing 2D image-space and 3D task-space information (i.e., 2.5D visual servoing) while actively adapting for unknown depth information, a task-space kinematic controller is developed that is proven to ensure asymptotic regulation of the position and orientation of the camera. Based on the desire to enhance the robustness of the control design, the integrator backstepping approach is then utilized to develop a joint torque control input to ensure asymptotic regulation of the position and orientation of the camera, which is held by the end-effector of a kinematically redundant robot manipulator, despite parametric uncertainty in the dynamic model of the robot. The stability of each controller is proven through a Lyapunov-based stability analysis.