Computer vision based robot calibration and control

To use a robot for tasks that require high accuracy, parametric calibration, a one-time affair, or an external sensing system is necessary. An external measuring system is more advantageous because it can be used to maintain high accuracy performance on-line. Such a system should be capable of measuring the end effector pose (position and orientation) of the robot in real-time. With such a measuring system, robot repeatability and accuracy can be measured and then used in task design. The objective of this dissertation is to demonstrate the use of a single camera 3D computer vision (SCV) system as a pose (position and orientation) sensor in order to perform robot calibration. The proposed SCV system (furnished by IBM) used in this dissertation is capable of accurately measuring movements in the 0.001 inch (0.005 cm), and 0.05 degree ranges. Other systems will perform differently since measurements are dependent upon the field of view and the camera resolution. A vision feedback scheme, termed Vision-guided Robot Control (VRC), is described which can improve the accuracy of a robot in an on-line iterative manner. This system demonstrates the advantage that can be achieved by a Cartesian space robot control scheme when end effector position/orientation is sensed instead of calculated from the kinematic equations. The degree of accuracy is determined by setting a tolerance level that is within the camera system's accuracy for each of the six robot Cartesian space coordinates. In general, a small tolerance level requires many iterations to position the end effector, and a large tolerance level requires fewer iterations. The viability of using a vision system for robot calibration is demonstrated by experimentally showing that the accuracy of an industrial robot can be drastically improved. In addition, the vision system can be used to measure the repeatability and accuracy of a robot in a simple, efficient, and quick manner. Experimental work utilizing an IBM Electric Drive Robot (EDR) and an SCV system produced a 97 and a 145 fold improvement in the position and orientation accuracy of the robot, respectively. For biomedical applications, this system can serve as a safety precaution during surgery, i.e. the surgical removal of bone by a robot. The use of a robot system insures a tight fit between the prosthesis and the bone interface for a total hip replacement procedure (a medical robotic system under development at U.C. Davis). However, the SCV system can also be used for other tasks that require high accuracy such as electronic assembly and materials handling.