Title: Kinematic calibration for industrial robots using articulated arm coordinate machines

Authors: Guanbin Gao; Hongwei Zhang; Hongjun San; Guoqing Sun; Xing Wu; Wen Wang

Addresses: Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming 650500, China ' Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming 650500, China ' Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming 650500, China ' Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming 650500, China ' Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming 650500, China ' School of Mechanical Engineering, Hangzhou Dianzi University, Hangzhou 310018, China

Abstract: To improve the position accuracy of industrial robots, a novel kinematic model and calibration method using articulated arm coordinate machines (AACMM) is proposed in this paper. The end of the industrial robot is connected to the probe of an AACMM, thus forming a closed kinematic chain. The coordinate systems of the double arms were established, based on which the mapping of the joint angles and the position of the end were derived as well as the nominal value of the kinematic parameters of the industrial robot. A two-step search method was presented for kinematic parameter identification of the industrial robot. The identified kinematic parameters were used to compensate the errors of the nominal kinematic parameters in the controller of the industrial robot. Experiments were conducted to verify the calibration method, which show that after calibration, the average position errors of the industrial robot were decreased greatly.

Keywords: kinematic calibration; parameter identification; industrial robot; genetic-tabu search algorithm; articulated arm coordinate measuring machine; AACMM.

DOI: 10.1504/IJMIC.2019.096816

International Journal of Modelling, Identification and Control, 2019 Vol.31 No.1, pp.16 - 26

Received: 23 Jan 2018
Accepted: 23 Jan 2018
Published online: 11 Dec 2018 *

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