A svd-least-square algorithm for manipulator kinematic calibration based on the product of exponentials formula
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In recent years, a great deal of research is conducted to improve the accuracy of manipulator kinematic calibration of which the product of exponential formula (PoE) is used to represent the manipulator kinematics, whose purpose is to solve the singularity problem of the Denavit-Hartenberg (D-H) parameters. However, the noise sensibility is still an open problem since a matrix inverse calculation of Jacobian matrix is inevitable during the process of solving the kinematic-linearized-equations to obtain the calibrated parameters. This problem may causes non-convergence, or low-accurate solution of calibration algorithm if the environmental noises and the error of endeffector’s actual frame measurement techniques are considerable. This paper presents a kinematic calibration method using singular value decomposition least square algorithm based on the product of exponentials formula (SVD-PoE-least-squares algorithm) to improve the accuracy of calibrated parameters. The proposed algorithm is evaluated in simulation level using a 6-DOF puma 560-type manipulator. The obtained results have shown that SVD-PoE-least-square algorithm is insignificantly affected by environmental noises, and, the proposed method can complete the robot calibration with respect to the work frame directly.
KeywordsKinematic calibration Product of exponentials formula SVD-least-square Sensibility reduce
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- K. M. Lynch and F. C. Park, Modern robotics: Mechanics, planning, and control, Cambridge University Press, England (2017).Google Scholar
- R. W. Brockett, Robotic manipulators and the product of exponentials formula, Proc. Int. Symp. Math. Theory of Networks and Systems, Beer Sheba, Isarel (1983) 120–129.Google Scholar
- Keli et al., Optimal measurement for kinematic calibration of a six–DOF spatial robotic manipulator, 2017 IEEE International Conference on Real–time Computing and Robotics (RCAR), Japan (2017) 252–257.Google Scholar
- W. S. Newman, C. E. Birkhimer, R. J. Horning and A. T. Wilkey, Calibration of a Motorman P8 robot based on laser tracking, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), USA (2000) 3597–3602.Google Scholar
- J. O’Brian, R. Bodenheimer, G. Brostow and J. Hodgins, Automatic joint parameter estimation from magnetic motion capture data, Proceedings of Graphics Interface, USA (2000) 53–60.Google Scholar
- P. Renaud, N. Andreff, F. Marquet and P. Martinet, Vision–based kinematic calibration of a H4 parallel mechanism, IEEE International Conference on Robotics and Automation (ICRA), Taiwan (2003) 1191–1196.Google Scholar