Pose Estimation Robust to Background Variation for Automated Alignment of Flat Cable to Receptacle

To automate the alignment task of a flat cable and its receptacle, this paper proposes flat cable pose estimation which is robust to background variation and control framework. To estimate the flat cable pose, we obtain entire three-channel edge map with sub-pixel order and segmentation mask which is initially generated entirely inside the cable region. To isolate only flat cable boundary edges, the initial mask iteratively expanded until its outermost pixels contact edges. The final cable boundary edges are obtained by retaining only those edge pixels contacted during expansion from the entire edge map. For the receptacle, corner positions are yielded using SIFT-based matching by leveraging the consistency of background texture. The obtained corners are used for pose estimation via stereo matching. Experimental results demonstrate that the proposed method localizes the corners of the flat cable with a maximum error of less than one pixel under background variation. In the control experiments, cable pose reached target pose within 5 seconds that are required within industrial site, in all 50 trials. This paper presents pose estimation method that is robust to background variation achieves sub-pixel order, along with automated alignment framework based on estimated results.