Real-time vision feedback for servoing robotic manipulator with self-tuning controller

The visual information obtained from a camera and an image processing unit are incorporated in an adaptive control algorithm to make a robotic manipulator grasp a moving object. Because of the inherent time delay caused by the image processing, the motion of the moving target is predicted in real time and is used in the online planning of the trajectory for the manipulator motion. Since the dynamics of the target are assumed to be unknown, the prediction is accomplished by means of an autoregressive discrete-time model. On the basis of the predicted motion of the object, the planner determines online at each control sampling instant the desired trajectory point (subgoal) for the controller. The subgoal point is tracked by controlling the end effector with self-tuner until grasping occurs. A simulation study and laboratory experiments are presented to demonstrate the performance of this visual feedback system