On Visual Servoing to Improve Performance of Robotic Grasping

We introduce image based visual servoing (IBVS) into a shared autonomy grasping system to improve its performance. Visual servoing is a technique that uses visual input to control a dynamic system, such as a robot. Autonomous grasp planning is used to calculate stable grasps to simplify the user control over a robot hand to 1 degree of freedom (DOF) open and close in contrast to controlling every finger. Visual servoing serves to increase the performance of completing the calculated grasp by using visual input to move some of the robot fingers to their grasp points. In this paper, we detail what we have accomplished, the challenges we have faced and what we have learned from them throughout the development of our system.