Abstract: A method of underwater simultaneous
localization and mapping (SLAM) based on on-board looking forward
sonar is proposed. The real-time data flow is obtained to form the
underwater acoustic images and these images are pre-processed and
positions of objects are extracted for SLAM. Extended Kalman filter
(EKF) is selected as the kernel approach to enable the underwater
vehicle to construct a feature map, and the EKF can locate the
underwater vehicle through the map. In order to improve the
association efficiency, a novel association method based on ant
colony algorithm is introduced. Results obtained on simulation data
and real acoustic vision data in tank are displayed and discussed.
The proposed method maintains better association efficiency and
reduces navigation error, and is effective and feasible.
ZENG Wen-jing (曾文静), WAN Lei (万 磊), ZHANG Tie-dong (张铁栋), HUANG Shu-ling (黄蜀玲)
. Simultaneous Localization and Mapping of Autonomous Underwater Vehicle Using
Looking Forward Sonar[J]. Journal of Shanghai Jiaotong University(Science), 2012
, 17(1)
: 91
-097
.
DOI: 10.1007/s12204-012-1234-8
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