A Robot Environment Identification Method: Image Processing Application in Duct Cleaning Robot

Author

Meng, Bu-Min ; Sun, Wei

Author_Institution

Coll. of Electr. & Inf. Eng., Hunan Univ., Changsha, China

fYear

2010

fDate

17-19 Dec. 2010

Firstpage

1208

Lastpage

1211

Abstract

In order to solve the issue how Duct Cleaning Robot senses the unknown duct environment, an environmental feature extraction method based on visual information is proposed. This method detects the edge of environmental images using the wavelet modulus maximum(wmm), and then extracts the geometric features of those images by Hough transformation. Finally, feed forward Back-Propagation Neural Network(BPNN) is used to environmental status identification. The relevant experimental results are given to prove the effectiveness of the proposed method.

Keywords

Hough transforms; backpropagation; ducts; edge detection; feature extraction; feedforward neural nets; geometry; mobile robots; path planning; robot vision; service robots; Hough transformation; autonomous navigation control; duct cleaning robot; edge detection; environmental feature extraction method; environmental status identification; feed forward back-propagation neural network; geometric feature extraction; image processing application; robot environment identification method; unknown duct environment; wavelet modulus maximum; Ducts; Feature extraction; Image edge detection; Robot sensing systems; Wavelet transforms; Duct Cleaning Robot; Hough Transform; Image Feature Extraction; Neural Network; Wavelet Modulus Maximum;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational and Information Sciences (ICCIS), 2010 International Conference on

Conference_Location

Chengdu

Print_ISBN

978-1-4244-8814-8

Electronic_ISBN

978-0-7695-4270-6

Type

conf

DOI

10.1109/ICCIS.2010.298

Filename

5709498