Image-based visual servoing and graph matching: a strategy for high-precision robotic assembly

Purpose This study aims to achieve reliable sub-millimeter robotic assembly for small-scale components using vision-based control under calibration-limited industrial conditions. Design/methodology/approach A vision-based assembly strategy is proposed by integrating segmented image-based visual servoing and feature-based graph matching in an eye-in-hand configuration. The assembly state is regulated directly through two-dimensional image feature relationships without explicit 3D pose estimation. Findings Experiments on representative connector assembly tasks demonstrate sub-millimeter positioning accuracy and stable convergence under significant initial pose uncertainties using commercially available cameras, coarse calibration and reliably identifiable image features. Originality/value The proposed framework provides a practical solution for small-scale precision assembly by emphasizing feature-driven control and system-level robustness rather than high-precision sensing.