Fast recognition and precise localization of humanoid soccer robot vision system

被引：2

作者：

Du, Xin-Feng ^{[1
]}

Xiong, Rong ^{[1
]}

Chu, Jian ^{[1
]}

机构：

[1] State Key Laboratory of Industrial Control Technology, Institute of Advanced Process Control, Zhejiang University

来源：

Zhejiang Daxue Xuebao(Gongxue Ban)/Journal of Zhejiang University (Engineering Science) | 2009年 / 43卷 / 11期

关键词：

Feature extraction; Humanoid robot; Localization model; Object recognition; Radial symmetry detection; Region segmentation;

D O I：

10.3785/j.issn.1008-973X.2009.11.006

中图分类号：

学科分类号：

摘要：

As the vision demands of humanoid soccer robot, an object recognition approach that concurrently segmenting regions and extracting features was proposed, and a monocular localization method based on the kinematic model of humanoid robot was presented. In the object recognition approach, 8-connected neighboring method was adopted to track the boundary of color region; meanwhile the features for recognition were extracted geometrically from the boundary. Then the radial symmetry detector was employed to improve the recognition accuracy. Compared to normal methods, the efficiency of this approach was doubled. The localization method combined the pin-hole camera model and three-links robot model to precisely locate the object in the field of view. The effects of the proposed methods were experimentally validated on a real humanoid soccer robot.

引用

页码：1975 / 1981

页数：6

共 17 条

[1]

Rencken W.D., Concurrent localization and map building for mobile robots using ultrasonic sensors, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 2192-2197, (1993)

[2]

Gutmann J.S., Schlege C., AMOS: Comparison of scan matching approaches for self-localization in indoor environments, Proceedings of 1st Euromicro Workshop on Advanced Mobile Robots, pp. 61-67, (1996)

[3]

Carlos M., Pedro L., A localization method for a soccer robot using a vision-based omni-directional sensor, Proceedings of RoboCup Workshop, pp. 96-107, (2000)

[4]

RoboCup humanoid soccer official site

[5]

Cheng H.D., Jiang X.H., Sun Y., Et al., Color image segmentation: Advances and prospects, Pattern Recognition, 34, 12, pp. 2259-2281, (2001)

[6]

Celenk M., A color clustering technique for image segmentation, Computer Vision, Graphics, and Image Processing, 52, 2, pp. 145-170, (1990)

[7]

Murch C.L., Chalup S.K., Combining edge detection and color segmentation in the four-legged league, Australasian Conference on Robotics and Automation, (2004)

[8]

Bandlow T., Klupsch M., Hanek R., Et al., Fast image segmentation, object recognition and localization in a RoboCup scenario, Proceedings of the Third RoboCup Workshop, pp. 22-27, (2004)

[9]

Quek F.K.H., An algorithm for the rapid computation of boundaries of run-length encoded regions, Pattern Recognition, 33, 10, pp. 1621-1649, (1999)

[10]

Seysener C.J., Murch C.L., Middleton R.H., Extensions to object recognition in the four-legged league, Proceedings of the RoboCup 2004 Symposium, pp. 274-285, (2005)

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