DEVELOPMENT OF ROBOT MANIPULATOR CALIBRATION TECHNIQUES USING MODEL BASED IDENTIFICATION AND UNMODELED COMPENSATION METHODS

Abstract

In recent years, interest in the application of robot manipulator to automated manufacturing soared. The advent of highly capable computer-controlled manipulators indicate d that tru-ly flexible automation was feasible, and many manufacturers rushed to take advantage of this technology. Robots are used in a wide range of tasks in industrial applications such as material handling, milling, painting welding, and roughing. Although the modeled-based robotic calibration methods have been widely researched for decades. It is difficult to cre-ate models that consider all the causes engendering the end effecter error. Therefore, to archive further accuracy, a good deal of attention has been paid to the area of un-modeled calibration for the sources of errors that could not be taken into account by model-based calibration. In this study, new robotic calibration methods are introduced. By combining the joint deflection model with the conventional kinematic model of a manipulator, the geometric errors and joint deflection errors can be considered together to increase its positional accu-racy. A new method includes the kinematic calibration and non-geometric compensation with a RBF compensator that compensates for compliance errors based on the effective torques. To improve the effectiveness of the calibration process, a neural network is de-signed to additionally compensate the unmodeled errors, specially, non-geometric errors. Then, the weights and biases of the neural network is determined by conventional back-propagation method. For increasing the ability of the neural network, heuristic optimization methods such as teaching learning optimization and invading weed optimization methods are hired for better convergence capability than the back propagation neural network in this calibration process. This work also presents a new method includes the kinematic calibration and teaching learning-based optimization for directly determining joint compliance parameters. The ad-vantages of the suggested method are easy for implementing, removing the need for torque sensors, high ability to enhance the precision of the manipulator. In order to demonstrate the effectiveness of the proposed method, experimental studies are carried out on manipulators. The enhanced position accuracy of the manipulator after the calibration confirms the feasibility and more positional accuracy over the other calibra-tion methods.