https://scholars.lib.ntu.edu.tw/handle/123456789/635952
標題: | CFVS: Coarse-to-Fine Visual Servoing for 6-DoF Object-Agnostic Peg-In-Hole Assembly | 作者: | Lu, Bo Siang Chen, Tung I. Lee, Hsin Ying WINSTON HSU |
公開日期: | 1-一月-2023 | 卷: | 2023-May | 來源出版物: | Proceedings - IEEE International Conference on Robotics and Automation | 摘要: | Robotic peg-in-hole assembly remains a challenging task due to its high accuracy demand. Previous work tends to simplify the problem by restricting the degree of freedom of the end-effector, or limiting the distance between the target and the initial pose position, which prevents them from being deployed in real-world manufacturing. Thus, we present a Coarse-to-Fine Visual Servoing (CFVS) peg-in-hole method, achieving 6-DoF end-effector motion control based on 3D visual feedback. CFVS can handle arbitrary tilt angles and large initial alignment errors through a fast pose estimation before refinement. Furthermore, by introducing a confidence map to ignore the irrelevant contour of objects, CFVS is robust against noise and can deal with various targets beyond training data. Extensive experiments show CFVS outperforms state-of-the-art methods and obtains 100%, 91%, and 82% average success rates in 3-DoF, 4-DoF, and 6-DoF peg-in-hole, respectively. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/635952 | ISBN: | 9798350323658 | ISSN: | 10504729 | DOI: | 10.1109/ICRA48891.2023.10160525 |
顯示於: | 資訊工程學系 |
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