Journal
JOURNAL OF FIELD ROBOTICS
Volume 37, Issue 6, Pages 987-1002Publisher
WILEY
DOI: 10.1002/rob.21935
Keywords
autonomous navigation; multiple target tracking; sensor fusion; unmanned surface vehicle
Categories
Funding
- Ministry of Oceans and Fisheries, Korea [PMS3870]
- Korea Research Institute of Ships and Ocean Engineering [PES3050]
- Korea Institute of Marine Science & Technology Promotion (KIMST) [PES3050] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
- Ministry of Science & ICT (MSIT), Republic of Korea [KIR01] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
- National Research Foundation of Korea [4120200313733] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
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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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