Computationally efficient and robust kinematic calibration methodologies and their application to industrial robots

Abstract

Robot kinematic calibration is the process of enhancing the positioning accuracy of a given manipulator and must be performed after robot manufacture and assembly or during periodical maintenance. This dissertation presents new computationally efficient and robust kinematic calibration algorithms for industrial robots that make use of partial measurements. These include a calibration method that requires the supply of Cartesian coordinates of the calibration points (3DCAL) and another calibration technique that only requires the radial measurements from the calibration points to some reference (1DCAL). Neither method requires orientation measurements nor the explicit knowledge of the whereabout of a reference frame. Contrary to most other similar works, both methods make use of a simplified version of the original Denavit-Hartenberg (DH) kinematic model. The simplified DH(-) model has not only proven to be robust and effective in calibrating industrial manipulators but it is also favored from a computational efficiency viewpoint since it consists of comparatively fewer error parameters. We present a conceptual approach I also would like to thank the director of Yaskawa Motoman Robotics, Inc. Mr. Wade Hickle, Senior Engineer Mr. Eric Marcil and Chief Engineer Mr. George Sutton for their guidance and for making the much needed materials available to me. I appreciate Dr. John Loomis and Dr. Ruihua Liu for participating in my committee. Thanks go to Mr. Tom Schenck of Measurement Specialties, Inc. for allowing me to conduct experiments in his workplace. Finally, I would like to give my special thanks to my dearest friends for all their help and encouragement. vi

A Novel Optimal Design of Measurement Configurations in Robot Calibration

“…It should be noted that some of the kinematic parameters are redundant, marked as "-" in these tables, which will be ignored during the calibration. The determining methods of redundant parameters can be found in the paper [26]. in an interval of 30 ∘ on each joint angle to generate configurations for the candidate configuration set pool .…”

On-Board Correction of Systematic Odometry Errors in Differential Robots

“…This process can be undertaken easily if precision exteroceptive sensors are present, such as LIDAR [6], sonar or depth sensor [7,8], and cameras [9,10]. Many studies have proposed calibration methods for industrial robots [11][12][13][14]. Localization of the robot, and therefore calibration, can also be based on active or passive beacons, but this kind of solution is not always possible in nonlaboratory or industrial environments.…”

Kinematic Calibration Based on the Multicollinearity Diagnosis of a 6-DOF Polishing Hybrid Robot Using a Laser Tracker

“…There have been many algorithms applied to robot calibration: the Levenberg-Marquardt (LM) method [24] is a classical nonlinear optimization algorithm that can effectively overcome the problem of the overparameterization and singularities. To overcome the deficiency in the LM method in which the convergence rate decreases if the search path is far from the optimal solution, a Trust Region (TR) method [25] is investigated to identify the source errors of the robot. Nevertheless, the number of iterations and optimization results of the nonlinear algorithm are significantly affected by the initial value, so the least square (LS) method [26,27] based on the linear model is widely employed in practice because it is simpler and easier to use.…”