무인선 충돌회피를 위한 자율운항시스템에 관한 연구

Abstract

An autonomous unmanned surface vehicle (AUSV) has been developed for multipurpose mission such as ocean observation and sea surveillance. The first prototype AUSV has been designed to have the length of about 7 meter and it has single water-jet with diesel engine. An autonomous navigation system is designed for collision avoidance of AUSV against obstacles such as fixed shorelines and moving traffic ships. Navigational information of AUSV is acquired by using Real-time Kinematic (RTK) DGPS and Fiber-optic gyro (FOG). Automatic Identification System (AIS) is also used to recognize obstacle. In this paper, an action space searching algorithm for collision avoidance (ACA) is newly designed by using fuzzy algorithm. The nodes and layers for searching route for collision avoidance are real-timely arranged around AUSV. In each node, collision risk between AUSV and obstacles is real-timely calculated by using fuzzy algorithm. Collision risk (CR) is an index, which is derived from DCPA and TCPA with obstacles through the inference of fuzzy algorithm. Here, main dimensions and velocity of AUSV are also considered. The paths, which are connected from current position of AUSV, node and waypoint are alternative routes for collision avoidance. The optimal path for collision avoidance is real-timely decided considering cost function with collision risk (CR), the time integration of (CR) or the integration of DCPA. Here, Internatio-jet with diesel engine. An autonomous navigation system is designed for collision avoidance of AUSV against obstacles such as fixed shorelines and moving traffic ships. Navigational information of AUSV is acquired by using Real-time Kinematic (RTK) DGPS and Fiber-optic gyro (FOG). Automatic Identification System (AIS) is also used to recognize obstacle. In this paper, an action space searching algorithm for collision avoidance (ACA) is newly designed by using fuzzy algorithm. The nodes and layers for searching route for collision avoidance are real-timely arranged around AUSV. In each node, collision risk between AUSV and obstacles is real-timely calculated by using fuzzy algorithm. Collision risk (CR) is an index, which is derived from DCPA and TCPA with obstacles through the inference of fuzzy algorithm. Here, main dimensions and velocity of AUSV are also considered. The paths, which are connected from current position of AUSV, node and waypoint are alternative routes for collision avoidance. The optimal path for collision avoidance is real-timely decided considering cost function with collision risk (CR), the time integration of (CR) or the integration of DCPA. Here, Internatio