On Robust Assembly of Flexible Flat Cables Combining CAD and Image Based Multiview Pose Estimation and a Multimodal Robotic Gripper

Abstract

In robotic assembly of flexible flat cables (FFCs), a unique challenge is the inherent difficulty in manipulating such flexible objects compared to their rigid counterparts and the precise estimation of the cable pose. This work proposes a framework that combines object pose estimation using computer-aided design (CAD) models and multiview fusion to perform precise FFC assembly. Our key insight is that a multiview fusion combined with pretrained 6-D pose estimation models offers a more flexible and precise object pose estimation. In a series of experiments involving FFC insertion tasks requiring assembly tolerances down to 0.1 mm, our approach achieves an insertion success rate of 399 out of 400 total attempts. Furthermore, the assembly tasks include the releasing and securing of FFCs from cable connectors, where the system is successful in 200 out of 200 trials. We have also demonstrated the generalization capability of the methodology by successfully completing insertion tasks for common electronic cables like DisplayPort and USB-A, achieving 199 successes in 200 trials. The results not only validate the feasibility of the proposed approach, but also demonstrate its robustness for real-world industrial applications.