Hole search strategy for robotic peg-in-hole assembly under initial positioning uncertainty

Abstract

Blind search methods are widely used in the search phase of robotic peg-in-hole assembly. However, these methods are sensitive to the initial contact position and are time-consuming. Additionally, in scenarios with a limited search space, such as thin-walled holes, the hole search process is prone to failure due to loss of contact between the peg and the hole. To address this issue, this paper proposes a hole search strategy that uses visual detection of the contact state between the peg and the hole and peg position adjustment based on the detection results. First, a contact-state classification model under fixed single-view conditions is constructed, converting the disordered relative positional relationships between the peg and the hole into discrete contact states, laying a theoretical foundation for the vision-guided hole search process. Second, search trajectories are generated based on the contact states, and trajectory optimization is further performed through visual error analysis, thereby overcoming hole search failures caused by visual occlusion and camera mounting deviations. Finally, convergence analysis shows that the peg slides into the hole when the classification accuracy is greater than 50%. Robotic assembly experiments further demonstrate the effectiveness of the proposed contact-state classification model and search strategy in tasks such as thin-walled hole insertion and USB Type-A(USB-A) connector insertion.