무인수상정의 해상 이동 표적 추적을 위한 접근 경로 계획 기법

김두영^*

해군 중령(진)/해군사관학교 인공지능학과 부교수

Approach Path Planning for Maritime Moving Target Tracking by Unmanned Surface Vehicles

Dooyoung Kim^*

CDR(Sel.), ROK Navy/Associate Professor, Dept. of Artificial Intelligence, Republic of Korea Naval Academy

Correspondence to: ^*Dooyoung Kim Dept. of Artificial Intelligence, Republic of Korea Naval Academy 1 Jungwon-ro, Jinhae-gu, Changwon-si, Gyungsangnam-do, 51704, Republic of Korea Tel: +82-55-549-5624 E-mail: dykim07@navy.ac.kr

초록

본 연구에서는 무인수상정의 해상 이동 표적 추적을 위한 인공신경망 기반 경로 생성 기법을 제안한다. 제안된 기법은 Hamilton-Jacobi-Bellman (HJB) 방정식을 신경망 모델로 근사하여, 추적자가 목표 선박의 함미 기준으로 제한된 방위 각도와 거리 내에서 접근하는 경로를 생성한다. 시뮬레이션을 통해 제안된 모델이 다양한 시나리오에서 유효하게 작동함을 확인하였다.

Abstract

This study presents a neural network-based path generation method for maritime moving target tracking by unmanned surface vehicles (USVs). The proposed method approximates the Hamilton–Jacobi–Bellman (HJB) equation using a neural network model, which generates the pursuer's trajectory for approaching the target vessel within constrained bearing angles and distance, based on the target vessel's stern. Simulation results confirm that the proposed model operates effectively in various scenarios.

Keywords:

Unmanned Surface Vehicle, Target Tracking, Path Planning, Neural Network Approximation, Differential Game

키워드:

무인수상정, 목표 추적, 경로 계획, 신경망 근사, 미분 게임

Acknowledgments

이 논문은 2025년 해군사관학교 해양연구소 학술연구과제 연구비 지원으로 수행된 연구임.

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