Optimization of pose samples for calibration of large component docking mechanisms

The compensation for the positioning error of large component docking mechanisms (LCDM) is the core technology for improving the assembly quality of aircraft. The pose samples (PSs) of the LCDM for kinematic parameter calibration significantly impact the final effect of error compensation. This paper proposes a PSs optimization method for kinematic parameter calibration of LCDM. Firstly, the kinematic model and the principle of kinematic parameter identification of LCDM are introduced. Then, an optimization model for the PSs is established based on the proposed observability index of the kinematic parameters, and a dynamic weighted particle swarm optimization (PSO) algorithm is used to optimize the PSs. Thirdly, the effectiveness of the proposed PSs optimization method is verified by Monte Carlo simulation, and the impacts of the number of measurement points (MPs) and PSs on calibration accuracy are analyzed. Finally, a docking system for simulated LAC is built in the laboratory, and the calibration experiments of the LCDM are conducted based on the optimized PSs. The experimental results show that the assembly accuracy of large components can be significantly improved by reasonably arranging the MPs and using the PSs optimization method proposed in this article.