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CLC number: TP242.6
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
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OBSTACLE DETECTION BY ALV USING TWO 2D LASER RANGE FINDERS
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XIANG Zhi-yu, LIU Ji-lin, GU Wei-kang, TIAN Yuan. OBSTACLE DETECTION BY ALV USING TWO 2D LASER RANGE FINDERS[J]. Journal of Zhejiang University Science A, 2001, 2(4): 388-394.
@article{title="OBSTACLE DETECTION BY ALV USING TWO 2D LASER RANGE FINDERS",
author="XIANG Zhi-yu, LIU Ji-lin, GU Wei-kang, TIAN Yuan",
journal="Journal of Zhejiang University Science A",
volume="2",
number="4",
pages="388-394",
year="2001",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2001.0388"
}
%0 Journal Article
%T OBSTACLE DETECTION BY ALV USING TWO 2D LASER RANGE FINDERS
%A XIANG Zhi-yu
%A LIU Ji-lin
%A GU Wei-kang
%A TIAN Yuan
%J Journal of Zhejiang University SCIENCE A
%V 2
%N 4
%P 388-394
%@ 1869-1951
%D 2001
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2001.0388
TY - JOUR
T1 - OBSTACLE DETECTION BY ALV USING TWO 2D LASER RANGE FINDERS
A1 - XIANG Zhi-yu
A1 - LIU Ji-lin
A1 - GU Wei-kang
A1 - TIAN Yuan
J0 - Journal of Zhejiang University Science A
VL - 2
IS - 4
SP - 388
EP - 394
%@ 1869-1951
Y1 - 2001
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.2001.0388
Abstract: This paper describes an effective method of obstacle detection by ALV (Autonomous Land Vehicle) equipped with two 2D laser range finders (LRF) installed at different locations of the ALV to obtain comprehensive information on the environment. The data processing includes two main steps: (1) data-processing of the current sample; (2) fusion of the former range data and the current one. The rough description of the ALV's environnent via the four sub-steps (Data Filter, Obstacle Extraction, Obstacle Merging, Distinguishing Obstacle from Road-Edge) was not reliable enough for our control system. To overcome the shortcoming of the 2D LRF and the motion noise of the ALV, a kalman Filter was used to estimate the position of the obstacles; then the data of the two LRFs were collated to obtain the height and width of the obstacles. Experiment results attested the feasibility of the detection system.
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