Doorplate adaptive detection and recognition for indoor mobile robot self-localization

Author

An, Chengwan ; Li, Guizhi ; Zhang, Yongqian ; Tan, Min

Author_Institution

Inst. of Autom., Chinese Acad. of Sci.

fYear

2004

fDate

22-26 Aug. 2004

Firstpage

339

Lastpage

343

Abstract

Self-localization is key to mobile robot navigation. Among many techniques for self-localization, landmark-based approaches can avoid complex and often memory demanding descriptions of robot surroundings. In this paper, doorplate is selected as visual landmark. For color images captured by robot, adaptive thresholding segmentation based on component color histograms and rival penalized competitive learning (RPCL) are employed to locate doorplate position in these images. Figures within doorplate are detected by edge detection operator and recognized with their geometric features extracted from results by Hilditich thinning algorithm. Experiments on mobile robot CASIA-1 show that this method is effective for indoor mobile robot self-localization

Keywords

edge detection; feature extraction; image colour analysis; image segmentation; image thinning; mobile robots; navigation; path planning; robot vision; CASIA-1; Hilditich thinning; adaptive thresholding segmentation; color histogram; color image; doorplate adaptive detection; doorplate adaptive recognition; edge detection; feature extraction; indoor mobile robot; mobile robot navigation; rival penalized competitive learning; self-localization; visual landmark; Color; Feature extraction; Histograms; Image edge detection; Image segmentation; Layout; Mobile robots; Navigation; Pattern recognition; Pixel; adaptive segmentation; mobile robot; self-localization; visual landmark;

fLanguage

English

Publisher

ieee

Conference_Titel

Robotics and Biomimetics, 2004. ROBIO 2004. IEEE International Conference on

Conference_Location

Shenyang

Print_ISBN

0-7803-8614-8

Type

conf

DOI

10.1109/ROBIO.2004.1521801

Filename

1521801