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Advanced Algorithm to Identify Vessels

Advanced Algorithm to Identify Vessels

Researchers from Wuhan University of Technology developed a maritime unmanned aerial vehicle system laced with a high-resolution camera and an Automatic Identification System (AIS)

Unmanned Arial Vehicle (UAV) is an independent and intelligent technology and offers several advantages such as low cost, good flexibility, low risk, and high efficiency. UAVs find application in modern maritime supervision, information collecting, search and rescue, environmental monitoring, exploration, and mapping. An UAV with a camera can be used in maritime supervision to offer live monitoring to provide a broad and steady view and efficient mobility. However, more information such as load, goods, and power system are required in vessel detection. Use of Automatic Identification System (AIS) can be efficient in offering the information by broadcast. Therefore, integration of vision and AIS can lead to efficient identification and tracking system.

Now, a team of researchers from Wuhan University of Technology developed a multi-featured and multi-level matching algorithm for a maritime unmanned aerial vehicle (Mar-UAV) system. The system is based on a multi-rotor copter platform and has two Degree-Of-Freedom (DOF) cameras and an AIS transceiver. The system can acquire videos of the target during flight and the real-time vision and AIS data are transmitted wirelessly to the ground control. The multi-featured and multi-level matching algorithm can be used to detect and identify the vessels in the view. Moreover, the system can be operated in a semiautonomous mode or a fully autonomous mode.

The system can find a target’s GPS coordinates and identify the target. The team found that vehicle configuration and material demonstrated good aerodynamic performance and a reliable structural strength for the missions. Mar-UAV system has an airframe that weighs 1.25 kg and six brushless motors with a collective weight of 2. 7 kg. It is powered by two Lithium-polymer (LiPo) batteries that weigh 4 kg. The team performed field experiments and found that the new algorithm can solve the identification of vessels as well as illegal or dangerous acts. The algorithm can recognize more information about vessels by combining vision and AIS, which can be used to supervise the vessels properly. The research was published in the journal MDPI Sensors on March 15, 2019.


Anagha Kulkarni
Anagha Kulkarni,

Anagha Kulkarni
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