A Visual-Tactile Fusion Coordinate System Alignment Method for a Mobile Hybrid Robot

In-situ manufacturing with mobile equipment offers an effective solution for producing large-scale, complex components. In mobile manufacturing, measurement is essential for achieving coordinate system (CS) alignment between the equipment and workpiece. However, obtaining precise and efficient measurements is challenging. To address this, a visual-tactile fusion CS alignment method is proposed, utilizing fast visual recognition to guide the tactile probe for accurate measurement. To resolve datums’ misrecognition caused by lighting conditions and material variations, a structured-light aided visual recognition method with color-space enhancement is introduced, enabling high-efficiency and robust datum recognition. To counteract deviations due to the probe’s anisotropic behavior in tactile measurement, an analytical mapping model between the probe’s anisotropic trigger error and the parallel robot’s parasitic motion is established, and a precise trigger error compensation table for CS alignment is generated. Experiments conducted on a mobile hybrid machining robot demonstrate that the proposed method achieves an alignment accuracy of 0.026 mm and 0.013°, with measurement times under 10 min. The accuracy fully meets the machining requirements for large-scale structures at 0.2 mm, and efficiency is improved threefold compared to traditional laser tracker measurement methods.