Closed-form camera pose and plane parameters estimation for moments-based visual servoing of planar objects

Yuhan Chen, Xiao Luo*, Baoling Han, Jianfeng Jiang, Yang Liu

*此作品的通讯作者

科研成果: 期刊稿件文章同行评审

2 引用 (Scopus)

摘要

Image moments are global descriptors of an image and can be used to achieve control-decoupling properties in visual servoing. However, only a few methods completely decouple the control. This study introduces a novel camera pose estimation method, which is a closed-form solution, based on the image moments of planar objects. Traditional position-based visual servoing estimates the pose of a camera relative to an object, but the pose estimation method directly estimates the pose of an initial camera relative to a desired camera. Because the estimation method is based on plane parameters, a plane parameters estimation method based on the 2D rotation, 2D translation, and scale invariant moments is also proposed. A completely decoupled position-based visual servoing control scheme from the two estimation methods above was adopted. The new scheme exhibited asymptotic stability when the object plane was in the camera field of view. Simulation results demonstrated the effectiveness of the two estimation methods and the advantages of the visual servo control scheme compared with the classical method.

源语言英语
期刊International Journal of Advanced Robotic Systems
19
3
DOI
出版状态已出版 - 5月 2022

指纹

探究 'Closed-form camera pose and plane parameters estimation for moments-based visual servoing of planar objects' 的科研主题。它们共同构成独一无二的指纹。

引用此