Uncertainty-Driven Spiral Trajectory for Robotic Peg-in-Hole Assembly

The peg-in-hole assembly is an essential robotic task that is widely involved in the industry and daily life. Hole search is a crucial step in peg-in-hole since it aligns the peg and hole where the positional uncertainty is presented. This study introduces a hole search strategy by computing an exploration distribution based on uncertainty analysis. Our method firstly utilizes vision to estimate the hole's pose. It then performs an uncertainty analysis based on vision estimation and systematic configures to compute the exploration distribution of the hole search. The computed exploration distribution calculates a search trajectory through the distribution and finds the hole. The effectiveness of the search strategy is experimentally verified using a robot manipulator in the peg-in-hole of the optical transceiver, which is a challenging task that has not yet been addressed. The results confirm that the proposed search strategy can achieve a 90$\%$ success rate on the hole search. Through the rational design of the recovery strategy, our method can secure a 100$\%$ success rate on the robotic peg-in-hole of apparatus with a small clearance (0.1 mm).