Calibration method for structural parameters of the articulated arm coordinate measuring machine utilizing a modified hybrid algorithm

Abstract

Abstract In order to increase the precision and decrease the movement uncertainty of the articulated arm coordinate measuring machine (AACMM), a calibration method is proposed in this paper, where the accuracy of single-point repeatability and volumetric accuracy (indicated by distance precision) are simultaneously considered. Considering the good ability of global exploitation and local exploration granted by chicken swarm optimization (CSO) and tabu search (TS), respectively, the CSO and TS are hybridized to construct the tabu searching-based CSO (TSCSO). To help the TSCSO jump out of the local optimal area when it is trapped in it, a transformational criterion of convergence precision is designed to integrate TSCSO with simulated annealing (SA) to formulate the hybrid algorithm called TSCSO with TSCSO-SA, which simultaneously possesses the good ability to globally exploit, locally explore, and jump out of the local optimal area when the population is trapped in it. Moreover, calibration experiments are conducted based on the accuracy of single-point repeatability and volumetric accuracy to verify the effectiveness, efficiency and suitability of the method and algorithm used in this paper. The results of the experiments and verifications show that the precision and movement uncertainty of the AACMM are immensely increased and decreased, respectively, further revealing that the method and algorithm proposed in this paper are able to effectively, efficiently and suitably calibrate the structural parameters of the AACMM.