Contact-based pose detection method for small components to optimise the digital twin-driven robotic assembly process

The robotic assembly has become pivotal in manufacturing, demanding precise pose detection of assembly components for efficient operations. This paper presents a contact-based pose detection method tailored for digital twin-based optimisation for the robotic assembly process, focusing on small component assembly challenges. The proposed technique achieves robust pose estimation by leveraging a strain gauge load cell-based calibration method. Experimental validation demonstrates close alignment between induced and measured errors, showcasing the efficacy of the method in mitigating assembly challenges. Despite minor deviations, the approach outperforms traditional vision-based methods, promising enhanced efficiency in robotic assembly tasks. Further refinement could bolster accuracy, fostering advanced robotic assembly capabilities.