On-line estimation of image jacobian matrix by improved Broyden's method in uncalibrated visual servoing

Xiangjin Zeng; Xinhan Huang; Min Wang

doi:10.1117/12.750188

15 November 2007 On-line estimation of image jacobian matrix by improved Broyden's method in uncalibrated visual servoing

Xiangjin Zeng, Xinhan Huang, Min Wang

Author Affiliations +

Proceedings Volume 6788, MIPPR 2007: Pattern Recognition and Computer Vision; 67881S (2007) https://doi.org/10.1117/12.750188
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

A novel improved broyden's method has been presented to estimate image jacobian matrix for uncalibrated visual servoing. In this paper, we apply chebyshev polynomial as a cost function to approximate best value. Compared with recursive least square (RLS) algorithm which is restricted by the prior knowledge for obtaining some performances, chebyshev polynomial algorithm has a great adaptability to estimate jacobian parameter, even without the prior knowledge. A microscopic image jacobian model has been developed for the four degree-of-freedom micromanipulator in our microassembly system. The performance has been confirmed by simulations and experiments.

Citation Download Citation

Xiangjin Zeng, Xinhan Huang, and Min Wang "On-line estimation of image jacobian matrix by improved Broyden's method in uncalibrated visual servoing", Proc. SPIE 6788, MIPPR 2007: Pattern Recognition and Computer Vision, 67881S (15 November 2007); https://doi.org/10.1117/12.750188

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