A POSITION ESTIMATION SYSTEM FOR MOBILE ROBOTS USING A MONOCULAR IMAGE OF A 3-D LANDMARK

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This paper presents an absolute position estimation system for a mobile robot moving on a flat surface. In this system, a 3-D landmark with four coplanar points and a non-coplanar point is utilized to improve the accuracy of position estimation and to guide the robot during navigation. Applying theoretical analysis, we investigate the image sensitivity of the proposed 3-D landmark compared with the conventional 2-D landmark. In the camera calibration stage of the experiments, we employ a neural network as a computational tool. The neural network is trained from a set of learning data collected at various points around the mark so that the extrinsic and intrinsic parameters of the camera system can be resolved. The overall estimation algorithm from the mark identification to the position determination is implemented in a 32-bit personal computer with an image digitizer and an arithmetic accelerator. To demonstrate the effectiveness of the proposed 3-D landmark and the neural network-based calibration scheme, a series of navigation experiments were performed on a wheeled mobile robot (LCAR) in an indoor environment. The results show the feasibility of the position estimation system applicable to mobile robot's real-time navigation.
Publisher
CAMBRIDGE UNIV PRESS
Issue Date
1994
Language
English
Article Type
Article
Citation

ROBOTICA, v.12, pp.431 - 441

ISSN
0263-5747
URI
http://hdl.handle.net/10203/57085
Appears in Collection
ME-Journal Papers(저널논문)
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