The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec)
Online ISSN : 2424-3124
2019
Session ID : 2A1-H07
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Evaluation of AI Obstacle Detection System for Ships
Katsuya HAKOZAKI*Etsuro SHIMIZUAyako UMEDA
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Abstract

Recently, researches related to autonomous ships and decision support system for seafarers are actively carried out. In order to realize autonomous ships and decision support systems, the obstacle detection is one of important technologies. In this paper, YOLOv3 which is one of obstacle detection software using AI has been examined to detect other ships during the navigation. The pre-trained weight file provided by YOLO is applied. VGA camera, HD video camera and 360 degrees camera were tested to compare the obstacles detection performance.

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© 2019 The Japan Society of Mechanical Engineers
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