Research

Marine Environment Perception Technology

Image-based Awareness Technology: We investigate the marine environment’s object detection, tracking, and analysis technology using a monocular camera and explore 3D reconstruction technology using images. Our goal is to develop technology that recognizes the surrounding environment’s situation while considering the marine environment’s specific conditions.
Sensor Fusion Technology in the Maritime Domain: We are exploring technology that recognizes the environment more accurately and robustly by combining various sensors. Our research focuses on sensor fusion techniques that reflect the characteristics of different sensors used in the marine environment, such as cameras, radars, lidars, and AIS.
3D Visualization Technology: We are researching visualization technology that effectively conveys the recognized surrounding situation information to the user or operator. By incorporating augmented reality techniques and utilizing 3D rendering technology, we aim to provide valuable information about the operational situation.
Research Based on Real-World Data: Utilizing sensor data from direct experiments, our research on situational awareness technology for the marine environment strives to be more practical and realistic. Data is collected from cameras, AIS, radar information installed at Korea Maritime and Ocean University, and navigation data from large ships through equipment mounted on the university’s training vessel.

Marine Vehicles’ Decision-Making Technology

USV and UUV Collision Avoidance Technology: We are developing technology to prevent collisions with nearby obstacles for the safe operation of unmanned surface and underwater vehicles. The technology makes collision avoidance decisions by considering the motion characteristics of marine bodies, maritime regulations, and terrain information.
Path Planning Technology for Berthing: Our research focuses on path planning technology related to the berthing of ships. We develop safe routes by considering the uncertainty of dynamic characteristics and the effects of environmental disturbances during docking and berthing.
AI-Based Decision-Making Technology: We are creating algorithms that support decision-making for various maritime vehicles using artificial intelligence technology. Our research focuses on developing decision-making technology for the autonomous operation of marine robots through advanced supervised learning and reinforcement learning techniques.

Motion Control Technology for Unmanned Marine Vehicles

Vessel Berthing Control Technology: Departure and berthing control requires technology to compensate for system uncertainty and environmental disturbances such as wind and currents. This is achieved through the use of adaptive control or model predictive control techniques to mitigate the influence of disturbances on the vessel’s motion.
Swarm Control Technology for Multiple Unmanned Marine Vehicles: Swarm control between multiple floating vessels or underwater robots enables a wide range of unmanned tasks that cannot be accomplished by a single vehicle. Our research focuses on swarm control technology for multiple objects and the guidance-navigation-control technology involved.
Marine Vehicle’s System Identification: Precise motion modeling of marine vehicles is necessary to control and simulate marine vehicles. We are developing technologies to acquire precise vehicle motion models through data analysis techniques and AI technology, surpassing the traditional method of estimating parameters through constrained model tests.