실시간 항공영상 기반 UAV-USV 간 협응 유도·제어 알고리즘 개발

• Published in: 大韓造船學會 論文集 Vol. 61; no. 5; pp. 324 - 333
• Main Authors: 김도균(Do-Kyun Kim), 김정현(Jeong-Hyeon Kim), 손희훈(Hui-Hun Son), 최시웅(Si-Woong Choi), 김동한(Dong-Han Kim), 여찬영(Chan Young Yeo), 박종용(Jong-Yong Park)
• Format: Journal Article
• Language: Korean
• Published: 대한조선학회 2024
• Subjects: 조선공학; UAV(Unmanned Aerial Vehicle, 무인항공기); USV(Unmanned Surface Vessel, 무인수상선), ROS(Robot Operating System, 로봇운영체제); Path planning(경로 계획); YOLO(You Only Look Once, 딥러닝 모델)
• ISSN: 1225-1143; 2287-7355
• DOI: 10.3744/SNAK.2024.61.5.324

This paper focuses on the cooperation between Unmanned Aerial Vehicle (UAV) and Unmanned Surface Vessel (USV). It aims to develop efficient guidance and control algorithms for USV based on obstacle identification and path planning from aerial images captured by UAV. Various obstacle scenarios were implemented using the Robot Operating System (ROS) and the Gazebo simulation environment. The aerial images transmitted in real-time from UAV to USV are processed using the computer vision-based deep learning model, You Only Look Once (YOLO), to classify and recognize elements such as the water surface, obstacles, and ships. The recognized data is used to create a two-dimensional grid map. Algorithms such as A* and Rapidly-exploring Random Tree star (RRT*) were used for path planning. This process enhances the guidance and control strategies within the UAV-USV collaborative system, especially improving the navigational capabilities of the USV in complex and dynamic environments. This research offers significant insights into obstacle avoidance and path planning in maritime environments and proposes new directions for the integrated operation of UAV and USV.