Autonomous control of shore robotic charging systems based on computer vision

被引:7
|
作者
Guney, Emin [1 ,5 ]
Bayilmis, Cuneyt [2 ]
Cakar, Serap [2 ]
Erol, Erdeniz [3 ]
Atmaca, Ozhan [4 ]
机构
[1] Sakarya Univ Appl Sci, Dept Comp Engn, TR-54050 Sakarya, Turkiye
[2] Sakarya Univ, Dept Comp Engn, TR-54187 Sakarya, Turkiye
[3] Elkon Elekt San Tic AS, Elkon Marine & Elect Technol Res & Dev Ctr, TR-34953 Istanbul, Turkiye
[4] Regbes BV, Johan Huizingalaan 763A, NL-1066 VH Amsterdam, Netherlands
[5] Sakarya Univ, Inst Nat Sci, Dept Comp & Informat Engn, Sakarya, Turkiye
关键词
Autonomous charging systems; Shore-to-ship charging; Electric vehicles; YOLOv5; Computer vision; Object detection; ELECTRIC VEHICLES; POWER-SYSTEM; IDENTIFICATION;
D O I
10.1016/j.eswa.2023.122116
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Recently, there has been a rapid increase in electric vessels as in electric land vehicles. Since vessels such as ferries and ships operate on a specific schedule, the time to be spent for charging on the shore is limited. The charging process involves connecting equipment, transferring energy, and disconnecting equipment. The faster and easier connection and disconnection process is, the more time is for energy transfer. This paper introduces a novel autonomous robotic charging system that combines Programmable Logic Controller (PLC), embedded platform, camera, and lasers to detect the vessel's charging socket in the charging area by computer vision. Initially, the embedded platform detects the charging socket and position of the electric vessel with the camera using You-Only-Look-Once (YOLOv5). After that, when the charging socket is detected, laser sensors control it more precisely to align the robotic charging station and move it closer to the socket on the ship. Finally, the precise location information is transmitted to the PLC, and the robotic charging station transfers energy until the charging process is completed. Consequently, the proposed system achieved 94% accuracy in charging socket detection. This research can be a guide in demonstrating the shore-to-ship socket detection efficiency of autonomous and computer vision-based ship charging systems.
引用
收藏
页数:13
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