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.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
