DocumentCode :
1968706
Title :
Estimation of mobile robot orientation using neural networks
Author :
Paulraj, M.P. ; Ahmad, R. Badlishah ; Hema, C.R. ; Hashim, Fadzilah
Author_Institution :
Sch. of Mechatron. Eng., Univ. Malaysia Perlis (UniMAP), Perlis
fYear :
2009
fDate :
6-8 March 2009
Firstpage :
42
Lastpage :
46
Abstract :
The computation of a mobile robot position and orientation is a common task in the area of computer vision and image processing. For a successful application, it is important that the position and orientation of a mobile robot must be determined properly. In this paper, a simple procedure for determining the orientation of the mobile robot using two cameras is presented. The two cameras are used to capture the images of a mobile robot at various orientations. Four simple neural network models are developed to associate the inputs and output (orientation). First and second neural network models are used to estimate the orientation of a mobile robot using only the features derived from the first and second camera. The third neural network model is used for estimating the orientation of a mobile robot using features derived from both the first and second camera. The fourth neural network model is used to estimate the orientation using features derived from the combined images. Simulation results show that the proposed algorithm can be used to estimate the orientation of the mobile robot accurately.
Keywords :
computer vision; image sensors; mobile robots; neurocontrollers; position control; robot vision; computer vision; image processing; mobile robot orientation; neural network model; Application software; Cameras; Computer vision; Floors; Mobile robots; Neural networks; Robot sensing systems; Robot vision systems; Signal processing; Sonar navigation; mobile robot; neural network; orientation; stereo imaging;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing & Its Applications, 2009. CSPA 2009. 5th International Colloquium on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4244-4151-8
Electronic_ISBN :
978-1-4244-4152-5
Type :
conf
DOI :
10.1109/CSPA.2009.5069185
Filename :
5069185
Link To Document :
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