Author:
Fang Yuan, ,Xiaoyong Zhang,Zhiwu Huang,Yu Wentao,Wang Yabo
Abstract
In this paper, a switched Kalmanfilter (KF) is used to predict the status of feature points leaving the field of view (FOV), which is one of the most common constraints in FOV. By using the prediction of status to compensate for the real state of feature points, nonholonomic robots conduct visual servoing tasks efficiently. Results of simulation and experiments verify the effectiveness of the proposed approach.
Publisher
Fuji Technology Press Ltd.
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition,Human-Computer Interaction
Reference20 articles.
1. A. C. Sanderson and L. E. Weiss, “Image--based visual servo control using relational graph error signals,” Proc. IEEE Int. Conf. On Robotics and Automation, pp. 1074-1077, 1980.
2. S. Hutchinson, G. Hager, and P. I. Corke, “A tutorial on visual servo control,” IEEE Trans. Robot. Autom., Vol.12, No.5, pp. 651-670, Oct. 1996.
3. F. Chaumette and S. Hutchinson, “Visual servo control Part I: Basic approaches,” IEEE Robot. Autom. Mag., Vol.13, No.4, pp. 82-90, Dec. 2006.
4. F. Chaumette and S. Hutchinson, “Visual servo control Part II: Advanced approaches,” IEEE Robot. Autom. Mag., Vol.14, No.1, pp. 109-118, Mar. 2007.
5. Y. Mezouar and F. Chaumette, “Path planning for robust image-based control,” IEEE Trans. Robot. Autom., Vol.18, No.4, pp. 534-549, Aug. 2002.
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献