Accurate Flexible Printed Circuit (FPC) Position Identification Using Haptic Information in Industrial Robotic Mobile Phone Assembly

In the industrial assembly of flexible printed circuits (FPCs), the FPC connectors and receivers are required to connect successfully with the least possible buckling times. However, precise and autonomous positioning of the FPC connectors is still a great challenge, as they are very small and visually blocked during assembly. This article proposes a strategy for the industrial assembly of FPC by: 1) unlike the traditional vision based methods, the task of FPC position identification in this work is considered as a haptic signals alignment problem. We mount a haptic sensor at the top end of the robotic arm manipulator and record various mismatched haptic signals around the ideal FPC connector position; 2) converting both the correct and incorrect haptic signals into images; and 3) we introduce a novel deep Siamese-network (DSN) structure to align the incorrect haptic images to the ground truth. The experiments are carried out on a practical FPC assembly platform for the Redmi Note 11 mobile phone. It is found that the haptic images combined with DSN can significantly improve the FPC location accuracy. When the buckle times are limited to 10, 5, and 1, the proposed method outperforms the state-of-the-art methods in a realistic FPC assembly platform.