计算机视觉
单目视觉
人工智能
对接(动物)
刚体
单眼
计算机科学
运动学
姿势
关节式人体姿态估计
三维姿态估计
医学
经典力学
物理
护理部
作者
Hua Luo,Ke Zhang,Yu Su,Kai Zhong,Zhongwei Li,Jun Guo,Chao Guo
出处
期刊:Measurement
[Elsevier]
日期:2022-11-01
卷期号:204: 112049-112049
被引量:5
标识
DOI:10.1016/j.measurement.2022.112049
摘要
Large rigid-body automatic docking is a crucial but tough task in aerospace assembly. Traditional large rigid-body spacecraft assembly is achieved manually, which is limited by high labor-intensity, low assembly quality, and long assembly cycle. This study proposes the monocular vision pose determination-based large rigid-body automatic docking method (MVPDLD) in which targets with circular feature points are attached to the surfaces of both mobile and fixed rigid-bodies; Thus, the proposed monocular vision system can track the relative pose between them. The measured relative pose is converted into kinematic parameters for a lightweight five-degree-of-freedom pose adjustment mechanism (5-DOFPAM), which can be guided via monocular vision pose determination to adjust the mobile rigid-body’s pose and achieve accurate docking. The MVPDLD method was validated on real datasets. MVPDLD’s accuracy is similar to traditional methods but achieves accurate docking much quicker. It can replace traditional manual methods for the automatic docking of large rigid-bodies.
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