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Cited 11 time in webofscience Cited 13 time in scopus
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Autonomous collision detection and avoidance for ARAGON USV: Development and field tests

Authors
Han, JungwookCho, YonghoonKim, JonghwiKim, JinwhanSon, Nam-sunKim, Sun Young
Issue Date
9월-2020
Publisher
WILEY
Keywords
autonomous navigation; multiple target tracking; sensor fusion; unmanned surface vehicle
Citation
JOURNAL OF FIELD ROBOTICS, v.37, no.6, pp 987 - 1002
Pages
16
Journal Title
JOURNAL OF FIELD ROBOTICS
Volume
37
Number
6
Start Page
987
End Page
1002
URI
https://www.kriso.re.kr/sciwatch/handle/2021.sw.kriso/217
DOI
10.1002/rob.21935
ISSN
1556-4959
1556-4967
Abstract
This study addresses the development of algorithms for multiple target detection and tracking in the framework of sensor fusion and its application to autonomous navigation and collision avoidance systems for the unmanned surface vehicle (USV) Aragon. To provide autonomous navigation capabilities, various perception sensors such as radar, lidar, and cameras have been mounted on the USV platform and automatic ship detection algorithms are applied to the sensor measurements. The relative position information between the USV and nearby objects is obtained to estimate the motion of the target objects in a sensor-level tracking filter. The estimated motion information from the individual tracking filters is then combined in a central-level fusion tracker to achieve persistent and reliable target tracking performance. For automatic ship collision avoidance, the combined track data are used as obstacle information, and appropriate collision avoidance maneuvers are designed and executed in accordance with the international regulations for preventing collisions at sea (COLREGs). In this paper, the development processes of the vehicle platform and the autonomous navigation algorithms are described, and the results of field experiments are presented and discussed.
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