Authors: Dongshu Wang; Jia Wang; Xunlin Zhu; Yan Shao
Addresses: School of Electrical Engineering, Zhengzhou University, Zhengzhou, Henan Province, 450001, China ' Siemens Ltd., China, Zhengzhou Branch, Zhengzhou, Henan Province, 450000, China ' Department of Mathematics, Zhengzhou University, Zhengzhou, Henan Province, 450001, China ' Department of Electrical and Computer Engineering, University of Kentucky, 119 CRMS Building, Lexington, KY 40506, USA
Abstract: Selection of optimal measurement configurations for the kinematic parameter calibration is investigated in this paper. To minimise the effects of measurement and modelling errors on parameter estimation, a series of optimal calibration configurations is obtained with our modified simulated annealing algorithm. To accelerate the convergence rate, a suitable cooling schedule is designed. Independent and interactive effects of the parameters in the cooling schedule on algorithm performance are discussed. Two observability indices are optimised with the modified simulated annealing algorithm to obtain the optimal measurement configurations of the 5-DOF polishing robot. Simulated calibration shows that these optimal configurations improve the calibration accuracy significantly. Experimental results, compared with those of random pose selection and a local search algorithm, are presented to demonstrate the feasibility of the proposed approach.
Keywords: robot calibration; optimal measurement configuration; modified simulated annealing algorithm; MSAA; singular value; condition number; polishing robots; robotic polishing; modelling errors; parameter estimation; cooling schedule; robot kinematics.
International Journal of Modelling, Identification and Control, 2014 Vol.21 No.2, pp.211 - 222
Available online: 24 Mar 2014 *Full-text access for editors Access for subscribers Purchase this article Comment on this article