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Pose Estimation of a Small Connector Attached to the Tip of a Cable Sticking Out of a Circuit Board

Changjian Ying, Yaqiang Mo, Yuichiro Matsuura, Kimitoshi Yamazaki

Year
2022
Citations
10

Abstract

In this study, we present the pose estimation of a small connector attached to the tip of a cable sticking out from a circuit board. Since such connectors are generally small and float in various configurations on their workpieces, it is difficult to achieve automation of grasping and inserting the connector into the corresponding socket. We focus on the task of grasping a connector and propose methods for detecting the location of the connector and estimating its 6DoF pose. In this regard, we use a high-precision three-dimensional digitizer to capture the object point cloud and combine several methods, such as deep learning and registration, to perform data processing. We conducted grasp experiments on several connectors using an actual industrial robot and confirmed the effectiveness of our approach in terms of pose estimation.

Keywords

Cable glandGRASPPrinted circuit boardComputer sciencePoint cloudPoseFocus (optics)Float (project management)RobotArtificial intelligence

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