Vision Based Pose Estimation of Multiple Peg-in-Hole for Robotic Assembly

Vision sensors are used to estimate the pose (position and orientation) of mating components in a vision assisted robotic peg-in-hole assembly which is a crucial step in aligning the mating hole-component with the corresponding moving peg-component. The accuracy of this estimation decides the performance of peg-in-hole robotic assembly with an appropriate mapping between the image and task environment using a fixed overhead camera or camera on robot arm. The wheel and hub assembly in automobile has multiple holes and pegs in their mating parts which lead to more complex pose estimation procedure. The success rate of the assembly process (without jamming) is affected by an inaccurate pose estimation which leads to lateral and/or axial misalignment between the mating components during its insertion phase. On this consideration, this work proposes a pose estimation algorithm for a multiple peg-in-hole assembly with the use of genetic algorithm based two-stage camera calibration procedure. The proposed algorithm has also been tested for its performance in estimating the pose of the multiple pegs in wheel-hub of a car. The result reveals that the proposed method estimates the pose of the pegs accurately with minimum re-projection error.